diff --git a/jsons.zip b/jsons.zip new file mode 100644 index 0000000000000000000000000000000000000000..2b2d6a0c5af012047ab7d145ed460a6347d24c83 --- /dev/null +++ b/jsons.zip @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ab658a97b49c39a60dc5268faee9d24b31156b1ffec3ab4defbcde72efd329f1 +size 38829507 diff --git a/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_intensity_identification.json b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_intensity_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..9ea3d9d084558599b270929d61eb51484a92fda0 --- /dev/null +++ b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_intensity_identification.json @@ -0,0 +1,3351 @@ +[ + { + "Question_id": "Event intensity identification/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Northeast", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Eastward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Northward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southwestward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast", + "(B) Northeast", + "(C) Northwest", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Northeast", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southwest", + "(B) Northeast", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Eastward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Eastward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Northward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Westward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Eastward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Eastward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast", + "(B) Northeast", + "(C) Southwest", + "(D) Northwest", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Northwest", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southeast", + "(C) Southwest", + "(D) Northeast", + "(E) Unable to decide" + ], + "Answer": "Northwest", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Southeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) west", + "(B) east", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Answer": "west", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "South", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Northwest", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast", + "(B) Northwest", + "(C) Northeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) East", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Southwest", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) East", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) West", + "(D) East", + "(E) Unable to decide" + ], + "Answer": "South", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) West", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southeast", + "(C) Northwest", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Northwest", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest then west", + "(B) West then south", + "(C) East then north", + "(D) South then east", + "(E) Unable to decide" + ], + "Answer": "West then south", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) West then North", + "(B) West then South", + "(C) East then North", + "(D) South then East", + "(E) Unable to decide" + ], + "Answer": "West then North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South then West", + "(B) East then North", + "(C) West then North", + "(D) North then West", + "(E) Unable to decide" + ], + "Answer": "West then North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) North", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/70", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) East", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/71", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Southeast", + "(D) Northeast", + "(E) Unable to decide" + ], + "Answer": "Northeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/72", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) South", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/73", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) West", + "(B) South", + "(C) North", + "(D) East", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/74", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South then north", + "(B) West then east", + "(C) East then west", + "(D) North then south", + "(E) Unable to decide" + ], + "Answer": "West then east", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/75", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) South", + "(D) East", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/76", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/77", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) North", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/78", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "East", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/79", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) South", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "South", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/80", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_016.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) East", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/81", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) West", + "(C) East", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "East", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/82", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/83", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) East", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/84", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) West", + "(B) South", + "(C) North", + "(D) East", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/85", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/86", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) South", + "(D) West", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/87", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South", + "(B) West", + "(C) East", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "West", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/88", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) West", + "(D) North", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/89", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "North", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/90", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the evolving direction of center during this period?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) East", + "(D) South", + "(E) Unable to decide" + ], + "Answer": "South", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_localization.json b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_localization.json new file mode 100644 index 0000000000000000000000000000000000000000..4e0012aea4fd26e656eca07274e19b23698cee78 --- /dev/null +++ b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_localization.json @@ -0,0 +1,3432 @@ +[ + { + "Question_id": "Event localization/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/00_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest United States", + "(B) Southeast United States", + "(C) Midwest United States", + "(D) Northeast United States", + "(E) Unable to decide" + ], + "Answer": "Northeast United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/01_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Algeria", + "(B) Morocco", + "(C) Libya", + "(D) Tunisia", + "(E) Unable to decide" + ], + "Answer": "Tunisia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/02_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast Asia", + "(B) Eastern Asia", + "(C) Central Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/03_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast USA", + "(B) Northwest USA", + "(C) Southeast USA", + "(D) Central USA", + "(E) Unable to decide" + ], + "Answer": "Northwest USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/04_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) New Zealand", + "(B) Australia", + "(C) Fiji", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/05_6h/msl_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) United Kingdom", + "(B) Germany", + "(C) Italy", + "(D) France", + "(E) Unable to decide" + ], + "Answer": "France", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/06_6h/msl_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Western Europe", + "(C) Southern Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/07_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) New Zealand", + "(C) Fiji", + "(D) Australia", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/08_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western United States", + "(B) Eastern United States", + "(C) Central Canada", + "(D) Northern Mexico", + "(E) Unable to decide" + ], + "Answer": "Eastern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/09_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Korea", + "(B) Japan", + "(C) China", + "(D) Taiwan", + "(E) Unable to decide" + ], + "Answer": "Japan", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/10_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Morocco", + "(B) South Africa", + "(C) Nigeria", + "(D) Kenya", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/11_6h/msl_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Canada", + "(B) Midwestern United States", + "(C) Pacific Northwest", + "(D) Southeastern United States", + "(E) Unable to decide" + ], + "Answer": "Eastern Canada", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/12_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/13_6h/msl_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Asia", + "(B) Eastern Asia", + "(C) Southeast Asia", + "(D) Central Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/14_6h/msl_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Netherlands", + "(B) France", + "(C) England", + "(D) Germany", + "(E) Unable to decide" + ], + "Answer": "England", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/15_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Southern Europe", + "(C) Eastern Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/16_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern China", + "(B) Western Japan", + "(C) Eastern Russia", + "(D) Southern India", + "(E) Unable to decide" + ], + "Answer": "Northern China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/17_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Morocco", + "(B) Tunisia", + "(C) Algeria", + "(D) Libya", + "(E) Unable to decide" + ], + "Answer": "Tunisia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/18_6h/msl_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast USA", + "(B) Midwest USA", + "(C) Pacific Northwest USA", + "(D) Southeast USA", + "(E) Unable to decide" + ], + "Answer": "Northeast USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/19_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Asia", + "(B) Central Asia", + "(C) Eastern Asia", + "(D) Southeast Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/20_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast USA", + "(B) Northeast USA", + "(C) Pacific Northwest USA", + "(D) Midwest USA", + "(E) Unable to decide" + ], + "Answer": "Northeast USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/21_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Africa", + "(B) Western USA", + "(C) Southern UK", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Answer": "Western USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/22_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) New Zealand", + "(D) Fiji", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/23_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Botswana", + "(B) Zimbabwe", + "(C) Namibia", + "(D) South Africa", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/24_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/25_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Answer": "Eastern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/26_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) New Zealand", + "(B) Papua New Guinea", + "(C) Australia", + "(D) Fiji", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/27_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern India", + "(C) Southeast Asia", + "(D) Northern China", + "(E) Unable to decide" + ], + "Answer": "Northern China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/28_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Libya", + "(B) Chad", + "(C) Egypt", + "(D) Sudan", + "(E) Unable to decide" + ], + "Answer": "Egypt", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/29_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Eastern Europe", + "(C) Western Europe", + "(D) Southern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/30_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast Asia", + "(B) Middle East", + "(C) Central Asia", + "(D) Northern Pacific", + "(E) Unable to decide" + ], + "Answer": "Northern Pacific", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/31_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Asia", + "(B) Southeast Asia", + "(C) Central Asia", + "(D) Eastern Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/32_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Africa", + "(B) Botswana", + "(C) Namibia", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/33_6h/msl_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) France", + "(B) Czech Republic", + "(C) Germany", + "(D) Poland", + "(E) Unable to decide" + ], + "Answer": "Germany", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/34_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Australia", + "(B) New zealand", + "(C) Papua New Guinea", + "(D) Fiji", + "(E) Unable to decide" + ], + "Answer": "New zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/35_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeastern USA", + "(B) Pacific Northwest", + "(C) Northeastern USA", + "(D) Central USA", + "(E) Unable to decide" + ], + "Answer": "Central USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/36_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern India", + "(C) Central Japan", + "(D) Northern China", + "(E) Unable to decide" + ], + "Answer": "Northern China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/37_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Asia", + "(B) Southeast Asia", + "(C) Eastern Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/38_6h/msl_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Africa", + "(B) Botswana", + "(C) Namibia", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/39_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) New Zealand", + "(B) Southern Australia", + "(C) Northern Australia", + "(D) Eastern Indonesia", + "(E) Unable to decide" + ], + "Answer": "Southern Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/40_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Canada", + "(B) Western USA", + "(C) Eastern USA", + "(D) Southeastern Mexico", + "(E) Unable to decide" + ], + "Answer": "Western USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/41_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Western Europe", + "(C) Southern Europe", + "(D) Northern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/42_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/43_6h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Asia", + "(B) Southeast Asia", + "(C) South Asia", + "(D) Eastern Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/44_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Pacific", + "(B) Southeastern Canada", + "(C) Midwest United States", + "(D) Southern California", + "(E) Unable to decide" + ], + "Answer": "Northern Pacific", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/45_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/46_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central USA", + "(B) Southeast USA", + "(C) Northwest USA", + "(D) Northeast USA", + "(E) Unable to decide" + ], + "Answer": "Northwest USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/47_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Botswana", + "(B) South Africa", + "(C) Zimbabwe", + "(D) Namibia", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a extratropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/extratropical_cyclone/48_6h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Germany", + "(B) United Kingdom", + "(C) France", + "(D) Italy", + "(E) Unable to decide" + ], + "Answer": "France", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Vietnam", + "(B) Thailand", + "(C) Japan", + "(D) Philippines", + "(E) Unable to decide" + ], + "Answer": "Japan", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mexico", + "(B) Louisiana", + "(C) Texas", + "(D) Florida", + "(E) Unable to decide" + ], + "Answer": "Mexico", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Fiji", + "(B) Solomon Islands", + "(C) Vanuatu", + "(D) Tonga", + "(E) Unable to decide" + ], + "Answer": "Fiji", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Thailand", + "(B) Philipphines", + "(C) Malaysia", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Answer": "Philipphines", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mozambique", + "(B) Tanzania", + "(C) Madagascar", + "(D) Kenya", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Texas", + "(B) Louisiana", + "(C) Caribbean", + "(D) Florida", + "(E) Unable to decide" + ], + "Answer": "Caribbean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Philippines", + "(B) Vietnam", + "(C) Japan", + "(D) Thailand", + "(E) Unable to decide" + ], + "Answer": "Japan", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Mexico", + "(B) Central Canada", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Answer": "Eastern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Tonga", + "(C) Fiji", + "(D) Samoa", + "(E) Unable to decide" + ], + "Answer": "Fiji", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mozambique", + "(B) Kenya", + "(C) Tanzania", + "(D) Madagascar", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Mediterranean", + "(B) Central Mediterranean", + "(C) Western Europe", + "(D) Northern Balkans", + "(E) Unable to decide" + ], + "Answer": "Central Mediterranean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Madagascar", + "(B) Mozambique", + "(C) Tanzania", + "(D) Kenya", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Fiji", + "(C) Tonga", + "(D) Solomon Islands", + "(E) Unable to decide" + ], + "Answer": "Fiji", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central America", + "(B) Mexico", + "(C) Caribbean Islands", + "(D) Southeastern United States", + "(E) Unable to decide" + ], + "Answer": "Central America", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Thailand", + "(B) Vietnam", + "(C) Bangladesh", + "(D) India", + "(E) Unable to decide" + ], + "Answer": "India", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Madagascar", + "(B) Tanzania", + "(C) Mozambique", + "(D) Kenya", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Kenya", + "(B) Tanzania", + "(C) Madagascar", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Fiji", + "(C) Solomon Islands", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Answer": "Solomon Islands", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Philippines", + "(B) Japan", + "(C) Vietnam", + "(D) Thailand", + "(E) Unable to decide" + ], + "Answer": "Japan", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western USA", + "(B) Eastern Mexico", + "(C) Eastern USA", + "(D) Central Canada", + "(E) Unable to decide" + ], + "Answer": "Eastern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Mexico", + "(B) Central Canada", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Answer": "Eastern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/70", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/71", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Bangladesh", + "(B) Myanmar", + "(C) Thailand", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Answer": "Myanmar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/72", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Fiji", + "(B) Australia", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/73", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Baltic Sea", + "(B) Western Mediterranean", + "(C) Eastern Mediterranean", + "(D) North Sea", + "(E) Unable to decide" + ], + "Answer": "Western Mediterranean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/74", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Madagascar", + "(B) Tanzania", + "(C) Kenya", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Answer": "Madagascar", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/75", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Gulf Coast", + "(B) Yucatan Peninsula", + "(C) Florida", + "(D) Caribbean", + "(E) Unable to decide" + ], + "Answer": "Caribbean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/76", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Philippines", + "(B) Japan", + "(C) Vietnam", + "(D) South Korea", + "(E) Unable to decide" + ], + "Answer": "Japan", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/77", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Philippines", + "(B) Malaysia", + "(C) Vietnam", + "(D) Thailand", + "(E) Unable to decide" + ], + "Answer": "Philippines", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/78", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western Balkans", + "(B) Central Mediterranean", + "(C) Northern Italy", + "(D) Eastern Mediterranean", + "(E) Unable to decide" + ], + "Answer": "Central Mediterranean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/79", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_018.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Fiji", + "(B) Tonga", + "(C) Solomon Islands", + "(D) Vanuatu", + "(E) Unable to decide" + ], + "Answer": "Fiji", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/80", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_016.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southern USA", + "(B) Central America", + "(C) Eastern Mexico", + "(D) Northern USA", + "(E) Unable to decide" + ], + "Answer": "Southern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/81", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in South America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/33_24h/msl_016.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Colombia", + "(B) Dominica", + "(C) Venezuela", + "(D) Brazil", + "(E) Unable to decide" + ], + "Answer": "Dominica", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/82", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Italy", + "(B) Bulgaria", + "(C) Turkey", + "(D) Greece", + "(E) Unable to decide" + ], + "Answer": "Greece", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/83", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Zimbabwe", + "(B) Zambia", + "(C) Botswana", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Answer": "Zimbabwe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/84", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Samoa", + "(B) Tonga", + "(C) Fiji", + "(D) Vanuatu", + "(E) Unable to decide" + ], + "Answer": "Fiji", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/85", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Thailand", + "(B) Myanmar", + "(C) Bangladesh", + "(D) India", + "(E) Unable to decide" + ], + "Answer": "India", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/86", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Aegean Sea", + "(B) Adriatic Sea", + "(C) Ionian Sea", + "(D) Tyrrhenian Sea", + "(E) Unable to decide" + ], + "Answer": "Ionian Sea", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/87", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Malaysia", + "(B) Vietnam", + "(C) Thailand", + "(D) Philippines", + "(E) Unable to decide" + ], + "Answer": "Philippines", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/88", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mozambique", + "(B) Botswana", + "(C) Malawi", + "(D) Zimbabwe", + "(E) Unable to decide" + ], + "Answer": "Zimbabwe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/89", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Midwestern USA", + "(B) Southwestern USA", + "(C) Southeastern USA", + "(D) Northeastern USA", + "(E) Unable to decide" + ], + "Answer": "Southeastern USA", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/90", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/42_6h/msl_019.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Northern Balkans", + "(C) Western Mediterranean", + "(D) Central Mediterranean", + "(E) Unable to decide" + ], + "Answer": "Central Mediterranean", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/91", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Florida", + "(B) Puerto Rico", + "(C) Louisiana", + "(D) Texas", + "(E) Unable to decide" + ], + "Answer": "Puerto Rico", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/92", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania by cyclone center?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) New Zealand", + "(B) East Australia", + "(C) Papua New Guinea", + "(D) Fiji", + "(E) Unable to decide" + ], + "Answer": "East Australia", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_onset_identification.json b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_onset_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..48c87943f35aaeef4479aabc4a2f7fae8f3f020d --- /dev/null +++ b/jsons/Atmosphere/Medium-term_weather_events/Perception/Event_onset_identification.json @@ -0,0 +1,1505 @@ +[ + { + "Question_id": "medium_event-Event onset identification-0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/00_24h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 264 hours", + "(B) 240 hours", + "(C) 192 hours", + "(D) 216 hours", + "(E) Unable to decide" + ], + "Answer": "240 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/01_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 96 hours", + "(C) 144 hours", + "(D) 108 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/02_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 84 hours", + "(C) 72 hours", + "(D) 108 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/03_24h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 60 hours", + "(B) 84 hours", + "(C) 72 hours", + "(D) 48 hours", + "(E) Unable to decide" + ], + "Answer": "72 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/04_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 60 hours", + "(B) 72 hours", + "(C) 48 hours", + "(D) 84 hours", + "(E) Unable to decide" + ], + "Answer": "72 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/05_24h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 192 hours", + "(B) 168 hours", + "(C) 120 hours", + "(D) 144 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/06_24h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 216 hours", + "(B) 192 hours", + "(C) 168 hours", + "(D) 240 hours", + "(E) Unable to decide" + ], + "Answer": "216 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/07_24h/msl_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 168 hours", + "(B) 120 hours", + "(C) 96 hours", + "(D) 144 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/08_24h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 120 hours", + "(C) 192 hours", + "(D) 168 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/09_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 72 hours", + "(C) 108 hours", + "(D) 84 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/10_6h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42 hours", + "(B) 30 hours", + "(C) 24 hours", + "(D) 36 hours", + "(E) Unable to decide" + ], + "Answer": "30 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/11_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 84 hours", + "(B) 120 hours", + "(C) 96 hours", + "(D) 72 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/12_24h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 120 hours", + "(C) 108 hours", + "(D) 144 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/13_24h/msl_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 108 hours", + "(C) 120 hours", + "(D) 144 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/14_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 96 hours", + "(C) 72 hours", + "(D) 60 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/15_24h/msl_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 240 hours", + "(B) 216 hours", + "(C) 288 hours", + "(D) 264 hours", + "(E) Unable to decide" + ], + "Answer": "264 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/16_24h/msl_018.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 120 hours", + "(C) 168 hours", + "(D) 96 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/17_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 168 hours", + "(B) 120 hours", + "(C) 96 hours", + "(D) 144 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/18_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 168 hours", + "(B) 192 hours", + "(C) 144 hours", + "(D) 120 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/19_24h/msl_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 144 hours", + "(C) 96 hours", + "(D) 168 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/20_24h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 168 hours", + "(B) 192 hours", + "(C) 144 hours", + "(D) 216 hours", + "(E) Unable to decide" + ], + "Answer": "192 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/21_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 72 hours", + "(B) 84 hours", + "(C) 48 hours", + "(D) 60 hours", + "(E) Unable to decide" + ], + "Answer": "72 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/23_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 96 hours", + "(C) 120 hours", + "(D) 168 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/24_24h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 72 hours", + "(B) 96 hours", + "(C) 84 hours", + "(D) 120 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/25_6h/msl_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 66 hours", + "(B) 48 hours", + "(C) 72 hours", + "(D) 60 hours", + "(E) Unable to decide" + ], + "Answer": "60 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/26_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 240 hours", + "(B) 216 hours", + "(C) 264 hours", + "(D) 288 hours", + "(E) Unable to decide" + ], + "Answer": "264 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/27_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 168 hours", + "(C) 192 hours", + "(D) 216 hours", + "(E) Unable to decide" + ], + "Answer": "192 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/28_6h/msl_027.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 72 hours", + "(B) 90 hours", + "(C) 96 hours", + "(D) 84 hours", + "(E) Unable to decide" + ], + "Answer": "84 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/29_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 168 hours", + "(C) 144 hours", + "(D) 96 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/30_6h/msl_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 30 hours", + "(B) 36 hours", + "(C) 42 hours", + "(D) 24 hours", + "(E) Unable to decide" + ], + "Answer": "30 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/31_24h/msl_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 108 hours", + "(B) 144 hours", + "(C) 96 hours", + "(D) 120 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/32_24h/msl_016.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 72 hours", + "(C) 120 hours", + "(D) 60 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/34_6h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 30 hours", + "(B) 36 hours", + "(C) 24 hours", + "(D) 48 hours", + "(E) Unable to decide" + ], + "Answer": "36 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/35_24h/msl_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 120 hours", + "(C) 168 hours", + "(D) 192 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/36_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 144 hours", + "(C) 168 hours", + "(D) 192 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/37_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 108 hours", + "(C) 120 hours", + "(D) 102 hours", + "(E) Unable to decide" + ], + "Answer": "108 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/38_6h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 60 hours", + "(B) 48 hours", + "(C) 66 hours", + "(D) 54 hours", + "(E) Unable to decide" + ], + "Answer": "60 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/39_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 72 hours", + "(C) 84 hours", + "(D) 120 hours", + "(E) Unable to decide" + ], + "Answer": "96 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/40_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 96 hours", + "(B) 144 hours", + "(C) 120 hours", + "(D) 108 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/41_24h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 120 hours", + "(B) 144 hours", + "(C) 108 hours", + "(D) 96 hours", + "(E) Unable to decide" + ], + "Answer": "120 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/43_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 168 hours", + "(B) 120 hours", + "(C) 144 hours", + "(D) 192 hours", + "(E) Unable to decide" + ], + "Answer": "168 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_event-Event onset identification-44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a tropical cyclone event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. How long did the msl in the area last for?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/MEDIUM_EVENT/region/tropical_cyclone/44_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Medium-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 144 hours", + "(B) 120 hours", + "(C) 168 hours", + "(D) 96 hours", + "(E) Unable to decide" + ], + "Answer": "144 hours", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/SEVIR_Weather/Reasoning/Event_Type_Prediction.json b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Event_Type_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..cbaeb729bfde3a1c83ae19a842a15279d5263148 --- /dev/null +++ b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Event_Type_Prediction.json @@ -0,0 +1,7202 @@ +[ + { + "Question_id": "Event Type Prediction/0000", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764931_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764931_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764931_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764931_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0001", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745801_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745801_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745801_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745801_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0002", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760792_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760792_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760792_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760792_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0003", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766182_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766182_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766182_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766182_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0004", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754838_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754838_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754838_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754838_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0005", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761780_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761780_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761780_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761780_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0006", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744384_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744384_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744384_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744384_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0007", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763628_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763628_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763628_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763628_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0008", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744002_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744002_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744002_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744002_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0009", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745416_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745416_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745416_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745416_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0010", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761799_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761799_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761799_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761799_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0011", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750773_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750773_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750773_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750773_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0012", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758297_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758297_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758297_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758297_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0013", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769710_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769710_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769710_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769710_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0014", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762188_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762188_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762188_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762188_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0015", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755175_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755175_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755175_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755175_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0016", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751459_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751459_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751459_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751459_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0017", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755587_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755587_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755587_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755587_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0018", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767943_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767943_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767943_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767943_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0019", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771985_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771985_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771985_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771985_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0020", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769506_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769506_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769506_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769506_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0021", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751570_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751570_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751570_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751570_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0022", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766727_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766727_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766727_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766727_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0023", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771178_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771178_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771178_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771178_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Funnel Cloud", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0024", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745883_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745883_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745883_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745883_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0025", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S785916_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S785916_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S785916_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S785916_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0026", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749639_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749639_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749639_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749639_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flash Flood", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0027", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763969_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763969_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763969_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763969_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0028", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S734737_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S734737_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S734737_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S734737_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0029", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764506_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764506_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764506_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764506_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Flash Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0030", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767593_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767593_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767593_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767593_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0031", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765062_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765062_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765062_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765062_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0032", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756788_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756788_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756788_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756788_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0033", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769422_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769422_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769422_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769422_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0034", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748712_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748712_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748712_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748712_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0035", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769602_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769602_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769602_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769602_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0036", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756840_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756840_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756840_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756840_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0037", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760108_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760108_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760108_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760108_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0038", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753280_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753280_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753280_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753280_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0039", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754405_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754405_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754405_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754405_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0040", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749081_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749081_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749081_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749081_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0041", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744575_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744575_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744575_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744575_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0042", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742604_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742604_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742604_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742604_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0043", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756402_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756402_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756402_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756402_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Funnel Cloud", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0044", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759992_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759992_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759992_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759992_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0045", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S746728_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S746728_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S746728_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S746728_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0046", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749693_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749693_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749693_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749693_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0047", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766329_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766329_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766329_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766329_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0048", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764130_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764130_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764130_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764130_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0049", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762945_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762945_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762945_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762945_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0050", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766410_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766410_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766410_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766410_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0051", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745962_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745962_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745962_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745962_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0052", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759286_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759286_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759286_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759286_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0053", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760270_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760270_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760270_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760270_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0054", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770141_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770141_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770141_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770141_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0055", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771047_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771047_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771047_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771047_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0056", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764847_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764847_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764847_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764847_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0057", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750570_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750570_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750570_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750570_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0058", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769518_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769518_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769518_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769518_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0059", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765660_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765660_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765660_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765660_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0060", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768041_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768041_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768041_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768041_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0061", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760511_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760511_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760511_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760511_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0062", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761646_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761646_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761646_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761646_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0063", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756045_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756045_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756045_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756045_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0064", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759043_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759043_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759043_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759043_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0065", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748746_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748746_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748746_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748746_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0066", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754192_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754192_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754192_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754192_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0067", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S740611_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S740611_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S740611_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S740611_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0068", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757375_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757375_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757375_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757375_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0069", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769004_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769004_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769004_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769004_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0070", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S746122_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S746122_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S746122_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S746122_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0071", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748754_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748754_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748754_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748754_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0072", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S731013_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S731013_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S731013_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S731013_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0073", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757388_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757388_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757388_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757388_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0074", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766723_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766723_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766723_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766723_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0075", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S747008_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S747008_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S747008_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S747008_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0076", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765042_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765042_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765042_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765042_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0077", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751853_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751853_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751853_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751853_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0078", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S738786_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S738786_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S738786_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S738786_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0079", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750455_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750455_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750455_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750455_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0080", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757927_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757927_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757927_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757927_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0081", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753605_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753605_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753605_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753605_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0082", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751261_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751261_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751261_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751261_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0083", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760291_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760291_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760291_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760291_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0084", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749599_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749599_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749599_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749599_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0085", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757127_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757127_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757127_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757127_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0086", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764157_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764157_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764157_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764157_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0087", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769567_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769567_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769567_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769567_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0088", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762472_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762472_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762472_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762472_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Thunderstorm Wind", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0089", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768097_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768097_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768097_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768097_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0090", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749653_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749653_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749653_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749653_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0091", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757017_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757017_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757017_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757017_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0092", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760916_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760916_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760916_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760916_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Thunderstorm Wind", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0093", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752213_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752213_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752213_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752213_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0094", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766233_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766233_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766233_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766233_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0095", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744978_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744978_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744978_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744978_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Thunderstorm Wind", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0096", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754123_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754123_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754123_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754123_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0097", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757738_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757738_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757738_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757738_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0098", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754861_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754861_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754861_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754861_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Funnel Cloud", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0099", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750346_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750346_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750346_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750346_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0100", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742766_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742766_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742766_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742766_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0101", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744088_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744088_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744088_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744088_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0102", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757649_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757649_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757649_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757649_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0103", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758848_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758848_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758848_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758848_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0104", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769856_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769856_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769856_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769856_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0105", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750950_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750950_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750950_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750950_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0106", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752394_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752394_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752394_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752394_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0107", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S739905_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S739905_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S739905_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S739905_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0108", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744530_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744530_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744530_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744530_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0109", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750021_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750021_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750021_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750021_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0110", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769468_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769468_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769468_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769468_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0111", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761532_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761532_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761532_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761532_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0112", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769937_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769937_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769937_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769937_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0113", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749126_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749126_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749126_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749126_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0114", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754872_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754872_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754872_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754872_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0115", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766676_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766676_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766676_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766676_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0116", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S733127_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S733127_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S733127_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S733127_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0117", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759980_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759980_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759980_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759980_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0118", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769668_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769668_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769668_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769668_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0119", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752112_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752112_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752112_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752112_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0120", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759434_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759434_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759434_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759434_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0121", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759714_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759714_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759714_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759714_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0122", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762421_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762421_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762421_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762421_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0123", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758747_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758747_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758747_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758747_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0124", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756272_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756272_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756272_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756272_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0125", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755677_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755677_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755677_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755677_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0126", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760698_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760698_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760698_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760698_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0127", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771511_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771511_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771511_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771511_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0128", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767994_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767994_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767994_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767994_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0129", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760604_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760604_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760604_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760604_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0130", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767179_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767179_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767179_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767179_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0131", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758764_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758764_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758764_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758764_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0132", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749592_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749592_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749592_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749592_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0133", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755509_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755509_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755509_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755509_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0134", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752906_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752906_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752906_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752906_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0135", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758694_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758694_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758694_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758694_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0136", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748766_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748766_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748766_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748766_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0137", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755860_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755860_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755860_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755860_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0138", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767563_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767563_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767563_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767563_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0139", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756528_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756528_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756528_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756528_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0140", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754452_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754452_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754452_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754452_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0141", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762295_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762295_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762295_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762295_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0142", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S740708_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S740708_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S740708_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S740708_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0143", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751231_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751231_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751231_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751231_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0144", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767348_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767348_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767348_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767348_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Funnel Cloud", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0145", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759131_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759131_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759131_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759131_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0146", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768057_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768057_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768057_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768057_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0147", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749422_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749422_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749422_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749422_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0148", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S743854_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S743854_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S743854_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S743854_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0149", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769149_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769149_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769149_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769149_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0150", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745039_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745039_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745039_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745039_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0151", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766812_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766812_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766812_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766812_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0152", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768321_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768321_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768321_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768321_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0153", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749386_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749386_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749386_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749386_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0154", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749284_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749284_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749284_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749284_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0155", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756127_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756127_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756127_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756127_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0156", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S739981_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S739981_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S739981_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S739981_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0157", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771060_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771060_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771060_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771060_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0158", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742199_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742199_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742199_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742199_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0159", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763669_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763669_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763669_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763669_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Funnel Cloud", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0160", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756680_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756680_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756680_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756680_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0161", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765408_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765408_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765408_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765408_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0162", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765037_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765037_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765037_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765037_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0163", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762604_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762604_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762604_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762604_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0164", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756785_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756785_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756785_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756785_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0165", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755304_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755304_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755304_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755304_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flash Flood", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0166", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769206_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769206_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769206_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769206_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0167", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756873_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756873_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756873_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756873_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0168", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753202_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753202_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753202_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753202_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0169", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S747519_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S747519_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S747519_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S747519_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0170", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771187_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771187_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771187_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771187_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Funnel Cloud", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0171", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748000_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748000_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748000_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748000_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0172", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770137_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770137_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770137_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770137_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0173", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760874_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760874_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760874_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760874_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flash Flood", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0174", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S743130_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S743130_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S743130_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S743130_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0175", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770467_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770467_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770467_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770467_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0176", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S730443_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S730443_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S730443_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S730443_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0177", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753251_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753251_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753251_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753251_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0178", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S747224_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S747224_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S747224_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S747224_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0179", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762212_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762212_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762212_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762212_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0180", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S783229_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S783229_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S783229_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S783229_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0181", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761995_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761995_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761995_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761995_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0182", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754751_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754751_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754751_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754751_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0183", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S785989_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S785989_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S785989_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S785989_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0184", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744758_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744758_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744758_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744758_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0185", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754015_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754015_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754015_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754015_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0186", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764784_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764784_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764784_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764784_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0187", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S735411_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S735411_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S735411_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S735411_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0188", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768164_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768164_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768164_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768164_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0189", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762933_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762933_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762933_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762933_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0190", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754056_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754056_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754056_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754056_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0191", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751404_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751404_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751404_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751404_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0192", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S746579_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S746579_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S746579_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S746579_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0193", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742832_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742832_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742832_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742832_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0194", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768971_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768971_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768971_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768971_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0195", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768472_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768472_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768472_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768472_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0196", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749525_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749525_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749525_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749525_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0197", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768883_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768883_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768883_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768883_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0198", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748696_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748696_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748696_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748696_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0199", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744737_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744737_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744737_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744737_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0200", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763404_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763404_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763404_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763404_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0201", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756049_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756049_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756049_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756049_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0202", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763749_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763749_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763749_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763749_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0203", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S738540_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S738540_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S738540_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S738540_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0204", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S737909_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S737909_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S737909_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S737909_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0205", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751773_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751773_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751773_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751773_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0206", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762932_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762932_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762932_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762932_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0207", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762797_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762797_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762797_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762797_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0208", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744568_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744568_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744568_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744568_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0209", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766669_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766669_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766669_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766669_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0210", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763164_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763164_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763164_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763164_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0211", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770853_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770853_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770853_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770853_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0212", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748333_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748333_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748333_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748333_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0213", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757094_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757094_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757094_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757094_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Funnel Cloud", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0214", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762580_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762580_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762580_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762580_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0215", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S748131_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S748131_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S748131_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S748131_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0216", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S738485_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S738485_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S738485_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S738485_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0217", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770257_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770257_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770257_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770257_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0218", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745683_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745683_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745683_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745683_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0219", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757510_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757510_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757510_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757510_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0220", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755299_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755299_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755299_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755299_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0221", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761115_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761115_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761115_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761115_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Heavy Rain", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0222", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751941_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751941_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751941_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751941_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0223", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765649_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765649_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765649_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765649_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0224", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756357_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756357_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756357_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756357_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0225", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768023_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768023_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768023_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768023_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0226", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742641_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742641_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742641_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742641_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0227", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S742431_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S742431_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S742431_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S742431_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0228", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768792_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768792_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768792_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768792_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0229", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766966_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766966_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766966_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766966_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0230", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769414_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769414_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769414_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769414_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0231", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752826_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752826_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752826_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752826_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0232", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744990_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744990_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744990_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744990_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0233", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750933_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750933_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750933_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750933_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Flood", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0234", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753447_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753447_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753447_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753447_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0235", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S766900_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S766900_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S766900_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S766900_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Funnel Cloud", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0236", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762931_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762931_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762931_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762931_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Funnel Cloud", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0237", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S738334_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S738334_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S738334_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S738334_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0238", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750448_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750448_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750448_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750448_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0239", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757071_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757071_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757071_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757071_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0240", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S738019_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S738019_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S738019_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S738019_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0241", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752349_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752349_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752349_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752349_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0242", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768901_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768901_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768901_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768901_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0243", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751445_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751445_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751445_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751445_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0244", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749055_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749055_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749055_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749055_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0245", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770088_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770088_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770088_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770088_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0246", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S750463_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S750463_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S750463_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S750463_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0247", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771610_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771610_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771610_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771610_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0248", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757633_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757633_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757633_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757633_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0249", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751338_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751338_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751338_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751338_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0250", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757237_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757237_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757237_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757237_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0251", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S732621_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S732621_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S732621_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S732621_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0252", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760858_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760858_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760858_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760858_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0253", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S768999_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S768999_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S768999_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S768999_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0254", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763278_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763278_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763278_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763278_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0255", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S736588_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S736588_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S736588_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S736588_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0256", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763122_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763122_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763122_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763122_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Heavy Rain", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0257", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S749762_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S749762_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S749762_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S749762_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0258", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770374_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770374_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770374_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770374_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0259", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771924_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771924_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771924_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771924_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0260", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S746750_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S746750_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S746750_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S746750_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0261", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S753388_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S753388_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S753388_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S753388_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0262", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S765304_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S765304_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S765304_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S765304_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0263", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752594_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752594_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752594_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752594_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0264", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759832_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759832_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759832_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759832_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0265", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759406_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759406_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759406_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759406_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0266", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S758748_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S758748_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S758748_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S758748_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0267", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752326_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752326_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752326_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752326_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Flash Flood", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0268", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S754288_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S754288_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S754288_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S754288_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Flood", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0269", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755225_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755225_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755225_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755225_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0270", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761456_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761456_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761456_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761456_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0271", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759224_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759224_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759224_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759224_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0272", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770396_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770396_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770396_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770396_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm Wind", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0273", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764481_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764481_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764481_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764481_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0274", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S757563_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S757563_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S757563_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S757563_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0275", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744403_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744403_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744403_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744403_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0276", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S763791_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S763791_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S763791_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S763791_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Flood", + "(C) Hail", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0277", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S770295_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S770295_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S770295_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S770295_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0278", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S746777_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S746777_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S746777_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S746777_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Heavy Rain", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0279", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744513_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744513_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744513_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744513_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0280", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760389_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760389_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760389_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760389_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Hail", + "(C) Tornado", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0281", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S745915_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S745915_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S745915_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S745915_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Thunderstorm Wind", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0282", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S732990_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S732990_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S732990_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S732990_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flash Flood", + "(B) Flood", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0283", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S767057_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S767057_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S767057_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S767057_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0284", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S769858_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S769858_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S769858_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S769858_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Tornado", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0285", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761570_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761570_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761570_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761570_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Hail", + "(D) Heavy Rain", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0286", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S751048_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S751048_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S751048_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S751048_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Flood", + "(C) Thunderstorm Wind", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0287", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S761692_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S761692_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S761692_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S761692_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0288", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755616_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755616_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755616_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755616_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Tornado", + "(C) Flood", + "(D) Thunderstorm Wind", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0289", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S759396_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S759396_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S759396_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S759396_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Thunderstorm Wind", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0290", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S760358_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S760358_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S760358_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S760358_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Tornado", + "(B) Hail", + "(C) Flood", + "(D) Funnel Cloud", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0291", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S752020_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S752020_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S752020_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S752020_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0292", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744037_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744037_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744037_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744037_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Heavy Rain", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0293", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S731511_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S731511_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S731511_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S731511_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Heavy Rain", + "(C) Tornado", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0294", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S756228_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S756228_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S756228_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S756228_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Tornado", + "(C) Hail", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0295", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S771148_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S771148_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S771148_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S771148_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0296", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S764780_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S764780_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S764780_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S764780_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Flood", + "(B) Tornado", + "(C) Thunderstorm Wind", + "(D) Hail", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0297", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S755427_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S755427_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S755427_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S755427_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0298", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S762626_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S762626_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S762626_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S762626_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Heavy Rain", + "(B) Hail", + "(C) Tornado", + "(D) Flood", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event Type Prediction/0299", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir069/S744401_ir069.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/ir107/S744401_ir107.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vil/S744401_vil.png", + "raw/Atmosphere/SEVIR_Weather/SEVIR_event_prediction/dataset/vis/S744401_vis.png" + ], + "Text": "The first image is the IR069 image, the second image is the IR107 image, the third image is the VIL image, and the fourth image is the VIS image. What is the storm event type based on the information in provided images?", + "Answer Choices": [ + "(A) Hail", + "(B) Heavy Rain", + "(C) Flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Event Type Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/SEVIR_Weather/Reasoning/Miss_Alarm_Estimation.json b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Miss_Alarm_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..2e888de6ace5d9d17564090d8c22f83a9c6358b0 --- /dev/null +++ b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Miss_Alarm_Estimation.json @@ -0,0 +1,6602 @@ +[ + { + "Question_id": "Miss Alarm Estimation/0000", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 10.09", + "(B) 19.58", + "(C) 12.58", + "(D) 2.03", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0001", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-1-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-1-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.74", + "(B) 15.73", + "(C) 16.29", + "(D) 16.74", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0002", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-2-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-2-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.15", + "(B) 13.38", + "(C) 4.45", + "(D) 21.31", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0003", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-3-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-3-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.75", + "(B) 1.31", + "(C) 16.07", + "(D) 8.55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0004", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-4-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-4-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 29.85", + "(B) 11.83", + "(C) 19.14", + "(D) 27.27", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0005", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-6-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-6-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.03", + "(B) 22.45", + "(C) 4.83", + "(D) 4.91", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0006", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-7-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-7-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.86", + "(B) 22.89", + "(C) 20.73", + "(D) 31.26", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0007", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-8-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-8-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.61", + "(B) 31.24", + "(C) 35.08", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0008", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-9-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-9-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.82", + "(B) 16.81", + "(C) 5.28", + "(D) 36.37", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0009", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-10-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-10-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.37", + "(B) 12.97", + "(C) 0.0", + "(D) 0.52", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0010", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-11-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-11-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.5", + "(B) 16.4", + "(C) 8.45", + "(D) 18.84", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0011", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-13-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-13-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.82", + "(B) 32.28", + "(C) 23.95", + "(D) 26.37", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0012", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-14-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-14-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.48", + "(B) 10.99", + "(C) 22.73", + "(D) 3.15", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0013", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-15-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-15-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.58", + "(B) 12.02", + "(C) 31.29", + "(D) 25.91", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0014", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-16-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-16-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.31", + "(B) 19.83", + "(C) 8.9", + "(D) 0.34", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0015", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-17-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-17-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 51.97", + "(B) 71.24", + "(C) 88.69", + "(D) 78.95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0016", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-18-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-18-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 7.23", + "(B) 25.36", + "(C) 0.03", + "(D) 19.62", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0017", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-19-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-19-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.84", + "(B) 39.07", + "(C) 33.46", + "(D) 23.39", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0018", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-20-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-20-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 31.69", + "(B) 25.23", + "(C) 9.51", + "(D) 17.83", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0019", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-21-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-21-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.65", + "(B) 13.52", + "(C) 19.19", + "(D) 4.82", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0020", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-22-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-22-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.65", + "(B) 20.8", + "(C) 24.98", + "(D) 5.14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0021", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-23-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-23-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 29.47", + "(B) 18.76", + "(C) 5.77", + "(D) 11.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0022", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 8.94", + "(B) 1.43", + "(C) 1.68", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0023", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-25-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-25-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 63.37", + "(B) 54.45", + "(C) 66.01", + "(D) 43.75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0024", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.72", + "(B) 23.21", + "(C) 23.19", + "(D) 19.04", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0025", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-27-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-27-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.76", + "(B) 5.83", + "(C) 25.41", + "(D) 17.77", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0026", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-28-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-28-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.18", + "(B) 4.42", + "(C) 23.04", + "(D) 12.45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0027", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-29-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-29-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.8", + "(B) 20.03", + "(C) 22.5", + "(D) 18.57", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0028", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.16", + "(B) 21.42", + "(C) 22.43", + "(D) 17.68", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0029", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-32-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-32-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.52", + "(B) 23.99", + "(C) 16.03", + "(D) 20.72", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0030", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-33-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-33-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.85", + "(B) 34.29", + "(C) 43.34", + "(D) 21.07", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0031", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-34-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-34-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 79.13", + "(B) 63.02", + "(C) 44.96", + "(D) 70.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0032", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-35-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-35-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.86", + "(B) 23.58", + "(C) 23.6", + "(D) 23.03", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0033", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-38-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-38-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 7.69", + "(B) 10.34", + "(C) 3.62", + "(D) 17.48", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0034", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-39-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-39-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.19", + "(B) 11.52", + "(C) 4.4", + "(D) 16.73", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0035", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-40-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-40-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.85", + "(B) 18.81", + "(C) 20.04", + "(D) 15.16", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0036", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.05", + "(B) 12.14", + "(C) 16.72", + "(D) 2.44", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0037", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-43-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-43-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.32", + "(B) 1.93", + "(C) 12.25", + "(D) 19.88", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0038", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-44-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-44-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.34", + "(B) 37.28", + "(C) 16.7", + "(D) 39.05", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0039", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 7.27", + "(B) 0.25", + "(C) 22.3", + "(D) 0.11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0040", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-47-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-47-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.31", + "(B) 26.98", + "(C) 1.82", + "(D) 16.14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0041", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-48-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-48-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 8.28", + "(B) 0.22", + "(C) 0.17", + "(D) 20.87", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0042", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-49-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-49-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.48", + "(B) 5.06", + "(C) 19.47", + "(D) 14.37", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0043", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-50-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-50-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 31.94", + "(B) 14.15", + "(C) 24.9", + "(D) 36.86", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0044", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-51-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-51-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 33.83", + "(B) 5.25", + "(C) 5.77", + "(D) 14.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0045", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-52-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-52-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.92", + "(B) 9.55", + "(C) 2.53", + "(D) 17.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0046", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-53-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-53-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 35.19", + "(B) 25.21", + "(C) 42.3", + "(D) 16.59", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0047", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 27.83", + "(B) 11.62", + "(C) 23.17", + "(D) 1.46", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0048", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.76", + "(B) 17.29", + "(C) 14.73", + "(D) 3.43", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0049", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.31", + "(B) 11.84", + "(C) 11.28", + "(D) 20.61", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0050", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.35", + "(B) 23.1", + "(C) 4.69", + "(D) 11.82", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0051", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-60-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-60-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.41", + "(B) 18.25", + "(C) 3.54", + "(D) 12.93", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0052", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.01", + "(B) 3.4", + "(C) 1.28", + "(D) 10.82", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0053", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-63-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-63-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.25", + "(B) 5.85", + "(C) 16.27", + "(D) 20.85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0054", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-64-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-64-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 27.13", + "(B) 9.34", + "(C) 1.43", + "(D) 17.76", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0055", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-65-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-65-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.24", + "(B) 5.19", + "(C) 23.83", + "(D) 20.85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0056", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-66-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-66-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 28.1", + "(B) 28.41", + "(C) 14.64", + "(D) 7.51", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0057", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-67-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-67-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 34.33", + "(B) 39.06", + "(C) 19.18", + "(D) 29.61", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0058", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.95", + "(B) 3.76", + "(C) 17.18", + "(D) 20.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0059", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-69-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-69-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.56", + "(B) 9.58", + "(C) 1.63", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0060", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-70-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-70-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.02", + "(B) 25.61", + "(C) 5.86", + "(D) 23.89", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0061", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.34", + "(B) 14.0", + "(C) 16.0", + "(D) 18.94", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0062", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-72-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-72-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.86", + "(B) 19.33", + "(C) 2.07", + "(D) 17.13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0063", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-73-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-73-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.04", + "(B) 24.7", + "(C) 4.75", + "(D) 15.57", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0064", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-74-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-74-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.26", + "(B) 26.08", + "(C) 0.71", + "(D) 9.67", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0065", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-77-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-77-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.28", + "(B) 0.05", + "(C) 7.35", + "(D) 0.06", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0066", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-78-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-78-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.28", + "(B) 33.82", + "(C) 43.61", + "(D) 15.65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0067", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-79-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-79-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.31", + "(B) 7.22", + "(C) 30.53", + "(D) 12.04", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0068", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-80-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-80-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.63", + "(B) 9.85", + "(C) 2.47", + "(D) 23.53", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0069", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-81-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-81-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 39.39", + "(B) 43.38", + "(C) 44.65", + "(D) 29.09", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0070", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-82-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-82-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 29.43", + "(B) 0.83", + "(C) 9.57", + "(D) 25.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0071", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 29.12", + "(B) 7.58", + "(C) 17.31", + "(D) 30.48", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0072", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.71", + "(B) 12.23", + "(C) 13.32", + "(D) 9.15", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0073", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-87-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-87-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.35", + "(B) 19.15", + "(C) 16.72", + "(D) 16.72", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0074", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-88-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-88-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.99", + "(B) 20.43", + "(C) 21.94", + "(D) 3.04", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0075", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.58", + "(B) 2.3", + "(C) 10.24", + "(D) 17.04", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0076", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-90-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-90-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.26", + "(B) 20.63", + "(C) 16.15", + "(D) 6.77", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0077", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-91-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-91-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.62", + "(B) 6.99", + "(C) 19.52", + "(D) 16.43", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0078", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-92-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-92-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.93", + "(B) 11.81", + "(C) 3.4", + "(D) 17.18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0079", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-93-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-93-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.44", + "(B) 26.85", + "(C) 41.7", + "(D) 35.45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0080", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-94-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-94-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.04", + "(B) 8.35", + "(C) 0.7", + "(D) 0.14", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0081", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-95-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-95-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.0", + "(B) 1.4", + "(C) 24.75", + "(D) 8.83", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0082", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-96-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-96-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.6", + "(B) 22.91", + "(C) 10.33", + "(D) 26.33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0083", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-97-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-97-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.93", + "(B) 10.91", + "(C) 0.74", + "(D) 0.85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0084", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-98-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-98-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.04", + "(B) 10.17", + "(C) 19.58", + "(D) 8.95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0085", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.01", + "(B) 26.7", + "(C) 6.91", + "(D) 24.33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0086", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-100-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-100-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.64", + "(B) 4.11", + "(C) 13.25", + "(D) 14.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0087", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-101-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-101-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.48", + "(B) 15.0", + "(C) 17.7", + "(D) 20.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0088", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-102-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-102-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 8.8", + "(B) 11.91", + "(C) 0.98", + "(D) 8.94", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0089", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-103-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-103-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 44.57", + "(B) 61.45", + "(C) 34.22", + "(D) 29.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0090", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.14", + "(B) 29.31", + "(C) 4.57", + "(D) 15.05", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0091", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-105-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-105-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.96", + "(B) 14.52", + "(C) 34.09", + "(D) 25.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0092", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-106-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-106-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.26", + "(B) 19.25", + "(C) 38.54", + "(D) 33.73", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0093", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-109-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-109-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.02", + "(B) 20.74", + "(C) 13.92", + "(D) 5.37", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0094", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-111-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-111-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.9", + "(B) 28.76", + "(C) 2.07", + "(D) 11.12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0095", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.12", + "(B) 13.57", + "(C) 17.1", + "(D) 2.63", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0096", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-114-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-114-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.14", + "(B) 2.99", + "(C) 19.96", + "(D) 12.13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0097", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-116-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-116-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.66", + "(B) 12.08", + "(C) 24.0", + "(D) 4.93", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0098", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-117-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-117-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.09", + "(B) 2.88", + "(C) 17.85", + "(D) 22.48", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0099", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.19", + "(B) 10.86", + "(C) 1.97", + "(D) 3.55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0100", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-119-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-119-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.02", + "(B) 2.99", + "(C) 33.45", + "(D) 14.83", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0101", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.32", + "(B) 18.78", + "(C) 5.06", + "(D) 17.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0102", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-121-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-121-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.2", + "(B) 11.02", + "(C) 11.19", + "(D) 9.18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0103", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-122-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-122-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.62", + "(B) 28.95", + "(C) 4.87", + "(D) 21.39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0104", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-123-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-123-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.82", + "(B) 1.41", + "(C) 0.29", + "(D) 9.85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0105", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-124-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-124-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.81", + "(B) 18.88", + "(C) 29.73", + "(D) 35.82", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0106", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-125-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-125-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.97", + "(B) 26.87", + "(C) 20.04", + "(D) 9.21", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0107", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-126-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-126-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.49", + "(B) 14.49", + "(C) 7.43", + "(D) 21.77", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0108", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-127-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-127-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.04", + "(B) 14.89", + "(C) 12.51", + "(D) 9.53", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0109", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-128-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-128-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.32", + "(B) 9.77", + "(C) 0.17", + "(D) 1.98", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0110", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-130-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-130-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.2", + "(B) 14.7", + "(C) 22.11", + "(D) 23.35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0111", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.51", + "(B) 12.29", + "(C) 23.89", + "(D) 4.79", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0112", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.68", + "(B) 22.48", + "(C) 21.72", + "(D) 6.59", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0113", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.63", + "(B) 17.46", + "(C) 6.8", + "(D) 15.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0114", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-135-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-135-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.55", + "(B) 32.36", + "(C) 32.07", + "(D) 13.54", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0115", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 27.87", + "(B) 0.62", + "(C) 13.99", + "(D) 1.79", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0116", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-137-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-137-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 10.65", + "(B) 1.78", + "(C) 0.59", + "(D) 19.02", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0117", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-138-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-138-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.79", + "(B) 25.33", + "(C) 9.24", + "(D) 19.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0118", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.81", + "(B) 17.81", + "(C) 12.91", + "(D) 11.98", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0119", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-141-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-141-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.63", + "(B) 14.93", + "(C) 5.04", + "(D) 13.22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0120", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-142-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-142-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.73", + "(B) 17.46", + "(C) 13.71", + "(D) 17.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0121", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-143-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-143-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.77", + "(B) 11.61", + "(C) 23.49", + "(D) 3.64", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0122", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-144-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-144-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.05", + "(B) 8.1", + "(C) 0.78", + "(D) 0.58", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0123", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.07", + "(B) 4.66", + "(C) 19.0", + "(D) 12.56", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0124", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-146-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-146-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.38", + "(B) 19.39", + "(C) 15.81", + "(D) 1.63", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0125", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-147-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-147-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 49.55", + "(B) 40.3", + "(C) 32.2", + "(D) 56.17", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0126", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-148-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-148-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.96", + "(B) 17.87", + "(C) 14.96", + "(D) 2.56", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0127", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.72", + "(B) 1.17", + "(C) 13.9", + "(D) 6.79", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0128", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-150-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-150-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 9.67", + "(B) 9.69", + "(C) 32.25", + "(D) 17.17", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0129", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-151-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-151-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.41", + "(B) 25.13", + "(C) 10.57", + "(D) 1.14", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0130", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-152-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-152-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.66", + "(B) 13.84", + "(C) 13.32", + "(D) 3.41", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0131", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-153-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-153-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.14", + "(B) 4.88", + "(C) 22.17", + "(D) 18.18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0132", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-155-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-155-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.94", + "(B) 8.74", + "(C) 8.78", + "(D) 1.35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0133", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.54", + "(B) 22.13", + "(C) 8.51", + "(D) 0.15", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0134", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.81", + "(B) 20.65", + "(C) 22.49", + "(D) 14.28", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0135", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.65", + "(B) 4.8", + "(C) 29.98", + "(D) 11.85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0136", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.29", + "(B) 7.32", + "(C) 16.5", + "(D) 0.23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0137", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-161-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-161-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 27.6", + "(B) 19.75", + "(C) 5.65", + "(D) 12.73", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0138", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-162-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-162-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.62", + "(B) 23.58", + "(C) 16.87", + "(D) 21.94", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0139", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-163-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-163-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.08", + "(B) 22.26", + "(C) 4.12", + "(D) 13.24", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0140", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-164-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-164-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.99", + "(B) 25.22", + "(C) 38.43", + "(D) 44.96", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0141", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-165-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-165-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.42", + "(B) 3.52", + "(C) 17.23", + "(D) 18.06", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0142", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-166-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-166-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.43", + "(B) 1.14", + "(C) 1.79", + "(D) 9.25", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0143", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-168-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-168-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.09", + "(B) 21.04", + "(C) 15.06", + "(D) 4.27", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0144", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-169-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-169-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.39", + "(B) 16.27", + "(C) 10.27", + "(D) 12.55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0145", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-170-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-170-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.36", + "(B) 5.6", + "(C) 20.71", + "(D) 18.56", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0146", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-171-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-171-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.01", + "(B) 7.05", + "(C) 0.02", + "(D) 0.02", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0147", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-172-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-172-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.86", + "(B) 10.96", + "(C) 0.66", + "(D) 2.44", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0148", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-173-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-173-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.65", + "(B) 22.59", + "(C) 37.59", + "(D) 29.81", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0149", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-175-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-175-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.35", + "(B) 8.16", + "(C) 19.47", + "(D) 15.29", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0150", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-177-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-177-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.54", + "(B) 27.22", + "(C) 7.96", + "(D) 17.91", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0151", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-178-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-178-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.65", + "(B) 23.57", + "(C) 16.27", + "(D) 3.95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0152", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-179-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-179-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.35", + "(B) 29.85", + "(C) 11.5", + "(D) 2.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0153", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-180-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-180-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 40.64", + "(B) 28.35", + "(C) 38.32", + "(D) 38.65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0154", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-181-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-181-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 82.91", + "(B) 56.07", + "(C) 82.88", + "(D) 71.07", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0155", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-183-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-183-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.38", + "(B) 18.38", + "(C) 18.53", + "(D) 24.67", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0156", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.29", + "(B) 3.76", + "(C) 16.88", + "(D) 12.37", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0157", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.17", + "(B) 10.95", + "(C) 3.69", + "(D) 14.99", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0158", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-186-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-186-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.97", + "(B) 23.55", + "(C) 26.18", + "(D) 6.85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0159", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-187-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-187-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 22.82", + "(B) 4.21", + "(C) 21.39", + "(D) 12.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0160", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-188-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-188-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.95", + "(B) 16.63", + "(C) 17.13", + "(D) 24.57", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0161", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-189-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-189-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.1", + "(B) 10.53", + "(C) 11.49", + "(D) 11.67", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0162", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 38.23", + "(B) 23.83", + "(C) 16.13", + "(D) 32.93", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0163", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-192-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-192-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.94", + "(B) 7.85", + "(C) 25.52", + "(D) 22.52", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0164", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-193-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-193-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.5", + "(B) 30.49", + "(C) 31.76", + "(D) 15.81", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0165", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-194-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-194-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.39", + "(B) 4.07", + "(C) 14.31", + "(D) 22.15", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0166", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-196-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-196-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 28.42", + "(B) 39.91", + "(C) 46.47", + "(D) 9.29", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0167", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-197-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-197-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.06", + "(B) 16.01", + "(C) 6.34", + "(D) 20.04", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0168", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-198-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-198-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.79", + "(B) 4.68", + "(C) 15.23", + "(D) 20.63", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0169", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.88", + "(B) 16.4", + "(C) 12.13", + "(D) 18.94", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0170", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-200-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-200-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.74", + "(B) 0.0", + "(C) 7.0", + "(D) 21.03", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0171", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-201-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-201-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 39.18", + "(B) 37.27", + "(C) 24.86", + "(D) 41.19", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0172", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-203-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-203-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.02", + "(B) 29.39", + "(C) 15.65", + "(D) 2.98", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0173", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-204-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-204-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.83", + "(B) 15.74", + "(C) 6.01", + "(D) 18.43", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0174", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-205-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-205-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.52", + "(B) 5.65", + "(C) 25.01", + "(D) 13.77", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0175", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-206-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-206-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.41", + "(B) 2.51", + "(C) 19.09", + "(D) 2.45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0176", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-207-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-207-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.0", + "(B) 33.74", + "(C) 9.43", + "(D) 16.81", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0177", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-208-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-208-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.4", + "(B) 14.49", + "(C) 14.25", + "(D) 3.19", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0178", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-209-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-209-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 10.74", + "(B) 3.39", + "(C) 0.27", + "(D) 22.23", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0179", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-210-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-210-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.39", + "(B) 1.29", + "(C) 1.44", + "(D) 8.63", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0180", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-211-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-211-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.73", + "(B) 20.35", + "(C) 10.63", + "(D) 3.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0181", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-213-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-213-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.31", + "(B) 11.86", + "(C) 4.98", + "(D) 20.55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0182", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-215-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-215-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.71", + "(B) 6.38", + "(C) 26.07", + "(D) 21.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0183", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-218-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-218-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.14", + "(B) 22.48", + "(C) 18.3", + "(D) 3.51", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0184", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-219-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-219-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.59", + "(B) 19.33", + "(C) 22.68", + "(D) 23.69", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0185", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-220-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-220-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.6", + "(B) 4.95", + "(C) 18.4", + "(D) 15.35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0186", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-221-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-221-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.34", + "(B) 10.96", + "(C) 21.05", + "(D) 3.29", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0187", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-222-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-222-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.31", + "(B) 18.9", + "(C) 0.07", + "(D) 2.48", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0188", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-223-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-223-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 34.93", + "(B) 33.93", + "(C) 16.75", + "(D) 23.92", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0189", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-224-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-224-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.83", + "(B) 19.5", + "(C) 12.3", + "(D) 3.34", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0190", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-225-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-225-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 7.3", + "(B) 16.77", + "(C) 23.96", + "(D) 21.32", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0191", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-226-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-226-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 100.0", + "(B) 87.52", + "(C) 90.8", + "(D) 83.25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0192", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-228-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-228-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.02", + "(B) 18.63", + "(C) 19.86", + "(D) 11.03", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0193", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-229-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-229-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.36", + "(B) 21.93", + "(C) 3.99", + "(D) 13.17", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0194", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-230-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-230-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.57", + "(B) 4.78", + "(C) 23.39", + "(D) 21.38", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0195", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-231-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-231-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.89", + "(B) 16.92", + "(C) 2.69", + "(D) 9.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0196", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-232-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-232-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.26", + "(B) 23.25", + "(C) 12.81", + "(D) 16.75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0197", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.83", + "(B) 29.25", + "(C) 29.68", + "(D) 10.49", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0198", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-234-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-234-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.91", + "(B) 24.54", + "(C) 16.96", + "(D) 15.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0199", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-235-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-235-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.5", + "(B) 7.93", + "(C) 22.73", + "(D) 0.73", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0200", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-236-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-236-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.14", + "(B) 40.4", + "(C) 15.49", + "(D) 6.62", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0201", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-238-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-238-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.88", + "(B) 7.98", + "(C) 5.98", + "(D) 25.24", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0202", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-240-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-240-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.75", + "(B) 20.97", + "(C) 38.91", + "(D) 10.36", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0203", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 28.34", + "(B) 0.42", + "(C) 17.91", + "(D) 28.98", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0204", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.12", + "(B) 21.14", + "(C) 17.22", + "(D) 5.08", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0205", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-243-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-243-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.6", + "(B) 14.13", + "(C) 5.18", + "(D) 25.28", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0206", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-244-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-244-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.07", + "(B) 7.08", + "(C) 26.3", + "(D) 0.05", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0207", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-245-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-245-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.01", + "(B) 19.14", + "(C) 4.01", + "(D) 17.37", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0208", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-246-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-246-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.32", + "(B) 3.12", + "(C) 22.48", + "(D) 14.15", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0209", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-247-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-247-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.53", + "(B) 10.01", + "(C) 19.93", + "(D) 20.81", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0210", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-248-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-248-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.82", + "(B) 29.98", + "(C) 21.17", + "(D) 30.91", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0211", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 37.99", + "(B) 38.5", + "(C) 33.13", + "(D) 23.85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0212", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-250-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-250-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.17", + "(B) 7.62", + "(C) 0.38", + "(D) 22.74", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0213", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-251-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-251-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.35", + "(B) 6.68", + "(C) 20.39", + "(D) 14.51", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0214", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-252-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-252-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.72", + "(B) 0.58", + "(C) 8.28", + "(D) 22.38", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0215", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-254-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-254-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.21", + "(B) 33.91", + "(C) 22.46", + "(D) 32.92", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0216", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-255-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-255-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.01", + "(B) 0.58", + "(C) 7.67", + "(D) 16.77", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0217", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-256-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-256-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.19", + "(B) 19.98", + "(C) 15.42", + "(D) 14.48", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0218", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-257-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-257-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.4", + "(B) 34.31", + "(C) 5.04", + "(D) 16.88", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0219", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-258-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-258-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.79", + "(B) 25.23", + "(C) 5.61", + "(D) 18.25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0220", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-259-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-259-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.16", + "(B) 0.25", + "(C) 0.37", + "(D) 7.65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0221", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-260-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-260-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.35", + "(B) 14.26", + "(C) 9.68", + "(D) 1.07", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0222", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-261-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-261-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.65", + "(B) 22.63", + "(C) 23.49", + "(D) 19.38", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0223", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.87", + "(B) 18.25", + "(C) 29.32", + "(D) 8.41", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0224", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-263-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-263-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.19", + "(B) 24.93", + "(C) 35.77", + "(D) 13.28", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0225", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-265-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-265-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.77", + "(B) 22.08", + "(C) 6.48", + "(D) 22.33", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0226", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-266-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-266-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.84", + "(B) 14.53", + "(C) 15.44", + "(D) 2.28", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0227", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-267-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-267-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.51", + "(B) 23.34", + "(C) 16.03", + "(D) 20.01", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0228", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-268-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-268-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.55", + "(B) 16.72", + "(C) 20.36", + "(D) 19.39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0229", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-269-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-269-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 5.12", + "(B) 16.79", + "(C) 21.17", + "(D) 24.47", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0230", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-270-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-270-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.01", + "(B) 19.03", + "(C) 7.01", + "(D) 16.42", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0231", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-271-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-271-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.11", + "(B) 1.22", + "(C) 8.93", + "(D) 18.72", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0232", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-272-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-272-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 10.72", + "(B) 18.68", + "(C) 1.36", + "(D) 3.43", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0233", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-274-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-274-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.13", + "(B) 3.09", + "(C) 10.56", + "(D) 2.66", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0234", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-275-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-275-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 84.54", + "(B) 100.0", + "(C) 85.45", + "(D) 87.47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0235", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-276-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-276-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.81", + "(B) 4.55", + "(C) 4.49", + "(D) 2.74", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0236", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-277-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-277-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 45.59", + "(B) 48.18", + "(C) 33.08", + "(D) 24.98", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0237", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-278-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-278-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 10.25", + "(B) 0.08", + "(C) 19.01", + "(D) 1.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0238", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-279-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-279-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.29", + "(B) 12.32", + "(C) 5.07", + "(D) 4.18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0239", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-280-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-280-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 22.71", + "(B) 14.67", + "(C) 17.11", + "(D) 6.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0240", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-281-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-281-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.22", + "(B) 19.65", + "(C) 4.37", + "(D) 20.41", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0241", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-282-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-282-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.01", + "(B) 5.21", + "(C) 20.62", + "(D) 17.04", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0242", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-284-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-284-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.77", + "(B) 21.93", + "(C) 25.28", + "(D) 6.45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0243", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-285-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-285-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.46", + "(B) 15.74", + "(C) 18.97", + "(D) 2.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0244", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-286-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-286-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.44", + "(B) 11.23", + "(C) 16.69", + "(D) 3.54", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0245", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-287-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-287-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.26", + "(B) 8.19", + "(C) 18.51", + "(D) 22.72", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0246", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-288-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-288-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 38.05", + "(B) 18.77", + "(C) 10.36", + "(D) 27.02", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0247", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-289-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-289-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 36.94", + "(B) 24.17", + "(C) 24.6", + "(D) 26.45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0248", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-290-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-290-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 9.72", + "(B) 43.55", + "(C) 17.88", + "(D) 27.94", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0249", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-291-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-291-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 46.32", + "(B) 27.22", + "(C) 39.17", + "(D) 50.15", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0250", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-292-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-292-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.69", + "(B) 5.13", + "(C) 12.13", + "(D) 18.44", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0251", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.56", + "(B) 29.84", + "(C) 3.24", + "(D) 29.38", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0252", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-295-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-295-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.09", + "(B) 17.8", + "(C) 16.29", + "(D) 25.45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0253", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-297-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-297-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.86", + "(B) 23.56", + "(C) 26.19", + "(D) 26.82", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0254", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-298-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-298-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 13.87", + "(B) 23.11", + "(C) 3.37", + "(D) 19.19", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0255", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-299-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-299-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 7.46", + "(B) 3.01", + "(C) 0.12", + "(D) 15.16", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0256", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-300-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-300-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 15.06", + "(B) 23.68", + "(C) 5.84", + "(D) 12.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0257", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.2", + "(B) 23.27", + "(C) 3.61", + "(D) 12.07", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0258", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-302-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-302-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.01", + "(B) 33.39", + "(C) 15.5", + "(D) 4.77", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0259", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-303-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-303-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.07", + "(B) 2.26", + "(C) 4.95", + "(D) 13.11", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0260", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-305-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-305-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.04", + "(B) 23.83", + "(C) 12.05", + "(D) 20.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0261", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 8.81", + "(B) 18.45", + "(C) 0.6", + "(D) 26.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0262", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-308-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-308-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.96", + "(B) 35.57", + "(C) 18.32", + "(D) 37.33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0263", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-309-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-309-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.35", + "(B) 5.66", + "(C) 20.37", + "(D) 20.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0264", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-310-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-310-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.81", + "(B) 17.88", + "(C) 22.67", + "(D) 3.36", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0265", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-312-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-312-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.84", + "(B) 12.52", + "(C) 4.96", + "(D) 15.73", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0266", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-313-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-313-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.53", + "(B) 21.84", + "(C) 5.0", + "(D) 23.22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0267", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-314-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-314-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.51", + "(B) 2.94", + "(C) 6.0", + "(D) 8.51", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0268", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-315-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-315-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 21.18", + "(B) 14.26", + "(C) 14.89", + "(D) 5.05", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0269", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-316-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-316-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 25.96", + "(B) 5.14", + "(C) 16.43", + "(D) 30.05", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0270", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-317-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-317-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 9.58", + "(B) 2.1", + "(C) 15.77", + "(D) 21.13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0271", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-318-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-318-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 34.35", + "(B) 17.45", + "(C) 24.83", + "(D) 27.45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0272", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-319-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-319-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.5", + "(B) 1.36", + "(C) 8.66", + "(D) 28.19", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0273", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-322-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-322-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.71", + "(B) 3.83", + "(C) 14.61", + "(D) 16.96", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0274", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-323-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-323-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.65", + "(B) 29.64", + "(C) 43.68", + "(D) 15.03", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0275", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-324-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-324-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.76", + "(B) 0.63", + "(C) 9.39", + "(D) 18.17", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0276", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-325-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-325-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 16.67", + "(B) 8.22", + "(C) 17.11", + "(D) 0.11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0277", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-326-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-326-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 20.91", + "(B) 24.77", + "(C) 23.1", + "(D) 6.84", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0278", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-327-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-327-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 19.05", + "(B) 16.86", + "(C) 24.35", + "(D) 6.84", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0279", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-328-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-328-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 14.2", + "(B) 1.45", + "(C) 21.16", + "(D) 13.57", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0280", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-329-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-329-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.58", + "(B) 21.46", + "(C) 0.81", + "(D) 8.59", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0281", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-330-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-330-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 11.5", + "(B) 16.5", + "(C) 4.11", + "(D) 14.33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0282", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-331-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-331-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 29.83", + "(B) 13.66", + "(C) 4.87", + "(D) 3.96", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0283", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-332-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-332-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.24", + "(B) 7.51", + "(C) 27.22", + "(D) 26.07", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0284", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-334-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-334-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 18.45", + "(B) 1.88", + "(C) 30.61", + "(D) 7.28", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0285", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-335-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-335-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 3.69", + "(B) 29.04", + "(C) 28.08", + "(D) 17.37", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0286", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-336-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-336-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 23.83", + "(B) 16.28", + "(C) 39.29", + "(D) 33.54", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0287", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-337-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-337-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 26.02", + "(B) 2.74", + "(C) 28.21", + "(D) 12.22", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0288", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-338-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-338-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.73", + "(B) 4.63", + "(C) 16.64", + "(D) 23.84", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0289", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-340-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-340-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.55", + "(B) 19.86", + "(C) 32.27", + "(D) 12.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0290", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-341-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-341-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 1.43", + "(B) 3.59", + "(C) 3.06", + "(D) 11.77", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0291", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-343-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-343-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 24.46", + "(B) 5.92", + "(C) 19.31", + "(D) 21.79", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0292", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-344-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-344-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 2.52", + "(B) 9.9", + "(C) 11.99", + "(D) 18.55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0293", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-345-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-345-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.49", + "(B) 1.0", + "(C) 9.05", + "(D) 28.17", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0294", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-346-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-346-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.07", + "(B) 0.63", + "(C) 25.6", + "(D) 11.71", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0295", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-347-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-347-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 17.13", + "(B) 5.0", + "(C) 21.31", + "(D) 14.67", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0296", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-348-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-348-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 6.2", + "(B) 15.15", + "(C) 19.01", + "(D) 13.31", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0297", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-349-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-349-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 0.49", + "(B) 27.48", + "(C) 0.16", + "(D) 9.97", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0298", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-350-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-350-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 12.29", + "(B) 23.23", + "(C) 20.82", + "(D) 2.66", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Miss Alarm Estimation/0299", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/gt/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-2.npy_raw.png", + "raw/Atmosphere/SEVIR_Weather/miss_alarm_estimation/dataset/EarthFormer/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-2.npy_EarthFormer.png" + ], + "Text": "The first image is the ground truth image of precipitation, the second image is the predicted image of precipitation. Each color represents dfferent precipitation levels.the gray area means a sunny weather.What is the miss alarm rate of the precipitation in predicted image compared to ground truth?", + "Answer Choices": [ + "(A) 4.34", + "(B) 24.33", + "(C) 15.02", + "(D) 33.43", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Miss Alarm Estimation", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/SEVIR_Weather/Reasoning/Movement_Prediction.json b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Movement_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..0d5677b433169e89e7dbaf67f09964afb42848b5 --- /dev/null +++ b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Movement_Prediction.json @@ -0,0 +1,6402 @@ +[ + { + "Question_id": "Movement Prediction/0000", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-314-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0001", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-461-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0002", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-330-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0003", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-533-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0004", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-758-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0005", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-457-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0006", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-24-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0007", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-367-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0008", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-635-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to northeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0009", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-771-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0010", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-659-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to northeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0011", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-119-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0012", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-426-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to southeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0013", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-244-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0014", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-723-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to east", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0015", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-184-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0016", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-416-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0017", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-608-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0018", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-223-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0019", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-26-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to east", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0020", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-717-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to east", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0021", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-134-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to southeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0022", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-209-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to east", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0023", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-138-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0024", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-274-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0025", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-185-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to northeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0026", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-726-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0027", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-136-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0028", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-233-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0029", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-233-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0030", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-252-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to northwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0031", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-156-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to southeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0032", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-61-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to east", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0033", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-748-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0034", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-482-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0035", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-307-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0036", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-175-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0037", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-760-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0038", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-89-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0039", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-726-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0040", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-167-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0041", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-271-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to east", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0042", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-528-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0043", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-834-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0044", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-589-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0045", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-526-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0046", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-315-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0047", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-31-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0048", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-473-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0049", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-673-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0050", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-584-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0051", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-101-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0052", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-370-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0053", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-524-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to east", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0054", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-322-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0055", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-266-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0056", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-352-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0057", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-285-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0058", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-241-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to southeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0059", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-389-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to northeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0060", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-593-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to northeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0061", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-418-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0062", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-312-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0063", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-242-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to southeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0064", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-518-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0065", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-765-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0066", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-833-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0067", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-418-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0068", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-166-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0069", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-559-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0070", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-733-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0071", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-670-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0072", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-771-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0073", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-448-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0074", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-120-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0075", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-256-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0076", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-262-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0077", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-513-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0078", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-219-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0079", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-555-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0080", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-254-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0081", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-116-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to east", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0082", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-54-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0083", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-3-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0084", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-220-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0085", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-348-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0086", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-97-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0087", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-830-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0088", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-788-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0089", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-42-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0090", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-552-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0091", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-281-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0092", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-266-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0093", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-645-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0094", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-711-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0095", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-404-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0096", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-631-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0097", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-179-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0098", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-8-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0099", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-644-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0100", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-149-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0101", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-599-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0102", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-463-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0103", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-331-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0104", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-533-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0105", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-366-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0106", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-525-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0107", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-241-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0108", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-189-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0109", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-584-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0110", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-137-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0111", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-160-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0112", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-786-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to east", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0113", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-661-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to east", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0114", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-305-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0115", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-498-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0116", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-262-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0117", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-679-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0118", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-28-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0119", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-599-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to east", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0120", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-318-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0121", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-594-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southwest", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0122", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-529-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0123", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-85-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to southeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0124", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-281-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to northeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0125", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-145-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0126", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-353-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0127", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-382-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0128", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-301-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0129", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-71-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to west", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0130", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-373-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0131", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-755-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0132", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-273-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0133", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-102-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0134", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-4-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to west", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0135", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-681-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northwest", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0136", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-80-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0137", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-159-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0138", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-428-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to east", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0139", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-374-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0140", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-577-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to southeast", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0141", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-43-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0142", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-91-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northwest", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0143", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-45-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to north", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0144", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-158-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to east", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0145", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-188-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0146", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-334-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0147", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-378-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0148", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-782-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to southeast", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0149", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-485-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to east", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0150", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-475-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0151", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-133-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to southeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0152", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-686-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0153", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-157-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0154", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-720-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0155", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-55-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0156", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-653-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0157", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-272-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0158", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-242-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0159", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-120-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to east", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0160", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-425-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0161", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-746-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to east", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0162", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-817-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0163", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-59-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to southeast", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0164", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-406-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to east", + "(C) to west", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0165", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-258-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0166", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-584-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southeast", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0167", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-99-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0168", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-22-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0169", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-377-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0170", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-404-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0171", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-32-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to east", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0172", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-2-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to northeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0173", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-692-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0174", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-434-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to southeast", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0175", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-414-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0176", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-611-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to west", + "(C) to northeast", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0177", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-581-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to east", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0178", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-686-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to northeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0179", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-168-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to northeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0180", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-339-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0181", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-625-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0182", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-263-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to east", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0183", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-433-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to northeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0184", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-85-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to east", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0185", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-117-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0186", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-53-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to south", + "(B) to north", + "(C) to southeast", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0187", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-287-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to east", + "(C) to south", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0188", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-66-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to south", + "(C) to north", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0189", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-838-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0190", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-647-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to west", + "(B) to north", + "(C) to south", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0191", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-90-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to east", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0192", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-79-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to south", + "(C) to west", + "(D) to north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0193", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-350-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to northeast", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0194", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-494-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to south", + "(C) to west", + "(D) to northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0195", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-46-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to southwest", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0196", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-159-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to west", + "(C) to north", + "(D) to south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0197", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-245-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to north", + "(B) to west", + "(C) to south", + "(D) to southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0198", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-446-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to east", + "(B) to south", + "(C) to north", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Movement Prediction/0199", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_0.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_1.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_2.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_3.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_4.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_5.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_6.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_7.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_8.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_9.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_10.png", + "raw/Atmosphere/SEVIR_Weather/movement_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-112-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the moving direction of the convective system in the sequence?", + "Answer Choices": [ + "(A) to northeast", + "(B) to north", + "(C) to south", + "(D) to west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Movement Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/SEVIR_Weather/Reasoning/Rotate_Center_Prediction.json b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Rotate_Center_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..ccdc64ccd29263582f1fa350ba6b76ae84cfb68f --- /dev/null +++ b/jsons/Atmosphere/SEVIR_Weather/Reasoning/Rotate_Center_Prediction.json @@ -0,0 +1,2978 @@ +[ + { + "Question_id": "Rotate Center Prediction/0000", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-176-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) south", + "(D) southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0001", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-508-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0002", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-539-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) southeast", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0003", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-721-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0004", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-262-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southeast", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0005", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-534-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0006", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-514-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) southeast", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0007", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-765-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) south", + "(D) southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0008", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-212-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) southeast", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0009", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-132-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) southwest", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0010", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-187-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0011", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-740-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) northeast", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0012", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-494-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) southeast", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0013", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-291-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0014", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-221-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) cente", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0015", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-315-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) north", + "(C) south", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0016", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-131-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) southwest", + "(C) south", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0017", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-643-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) northeast", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0018", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-199-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) south", + "(D) southeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0019", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-114-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) cente", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0020", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-724-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) south", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0021", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-0-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) cente", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0022", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-41-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) southeast", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0023", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-822-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) southeast", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0024", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-850-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) west", + "(C) north", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0025", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-537-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) east", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0026", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-141-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) east", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0027", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-100-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) west", + "(C) north", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0028", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-553-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0029", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-136-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) northeast", + "(B) south", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0030", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-163-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0031", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-821-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0032", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-650-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) southwest", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0033", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-118-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) north", + "(C) northeast", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0034", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-6-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) cente", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0035", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-128-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) south", + "(D) northwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0036", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-492-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) northwest", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0037", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-56-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0038", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-378-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) cente", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0039", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-769-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0040", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-68-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) north", + "(C) west", + "(D) southwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0041", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-780-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) west", + "(C) north", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0042", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-50-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) southeast", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0043", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-272-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0044", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-30-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southeast", + "(B) west", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0045", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-75-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) east", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0046", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-555-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) west", + "(C) north", + "(D) northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0047", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-363-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) east", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0048", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-351-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) northwest", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0049", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-136-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0050", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-491-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0051", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-298-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0052", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-515-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) southeast", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0053", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-414-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) cente", + "(B) south", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0054", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-104-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) southeast", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0055", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-135-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0056", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-257-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) west", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0057", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-761-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) northeast", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0058", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-191-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) west", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0059", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-807-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) southwest", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0060", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-430-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) southeast", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0061", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-678-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0062", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-846-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) north", + "(C) south", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0063", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-126-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0064", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-152-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) east", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0065", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-54-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) cente", + "(B) west", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0066", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-84-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) west", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0067", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-845-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0068", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-436-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) west", + "(C) east", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0069", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-297-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) southwest", + "(C) west", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0070", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-249-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) cente", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0071", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-226-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) northwest", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0072", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-98-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0073", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-140-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) south", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0074", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-543-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) north", + "(C) southwest", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0075", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-329-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) southwest", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0076", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-482-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0077", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-535-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) south", + "(C) west", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0078", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-116-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) west", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0079", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-57-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) east", + "(B) west", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0080", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-520-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southeast", + "(B) north", + "(C) west", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0081", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-454-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) southwest", + "(C) south", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0082", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-708-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) southwest", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0083", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0101_0630.h5-589-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) east", + "(B) north", + "(C) south", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0084", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2019-SEVIR_VIL_STORMEVENTS_2019_0701_1231.h5-151-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) north", + "(C) cente", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0085", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-465-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) south", + "(C) north", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0086", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-468-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) southwest", + "(B) west", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0087", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-386-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) south", + "(B) north", + "(C) west", + "(D) northeast", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0088", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-84-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) northwest", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0089", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0101_0630.h5-736-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) north", + "(B) south", + "(C) northwest", + "(D) west", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0090", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-451-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) east", + "(B) west", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0091", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-830-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) northeast", + "(B) west", + "(C) north", + "(D) south", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + }, + { + "Question_id": "Rotate Center Prediction/0092", + "Images": [ + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_0/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_0.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_1/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_1.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_2/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_2.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_3/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_3.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_4/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_4.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_5/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_5.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_6/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_6.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_7/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_7.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_8/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_8.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_9/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_9.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_10/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_10.png", + "raw/Atmosphere/SEVIR_Weather/rotate_center_prediction/dataset/TimeStep_11/vil-2018-SEVIR_VIL_STORMEVENTS_2018_0701_1231.h5-293-0_11.png" + ], + "Text": "The provided image sequence represent the evolution of a convective system. What is the rotate center of the convective system in the sequence?", + "Answer Choices": [ + "(A) west", + "(B) south", + "(C) north", + "(D) east", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "SEVIR Weather", + "L3-task": "Reasoning", + "L4-task": "Rotate Center Prediction", + "Dataset": "SEVIR", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Short-term_weather_events/Perception/Event_intensity_identification.json b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_intensity_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..78b0eab6ad189e4e8a572f75d0abcc29d30372e2 --- /dev/null +++ b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_intensity_identification.json @@ -0,0 +1,3498 @@ +[ + { + "Question_id": "Event intensity identification/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42", + "(B) 51", + "(C) 39", + "(D) 47", + "(E) Unable to decide" + ], + "Answer": "47", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 53", + "(D) 42", + "(E) Unable to decide" + ], + "Answer": "50", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 47", + "(B) 35", + "(C) 38", + "(D) 42", + "(E) Unable to decide" + ], + "Answer": "42", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 45", + "(B) 42", + "(C) 39", + "(D) 48", + "(E) Unable to decide" + ], + "Answer": "45", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42", + "(B) 46", + "(C) 48", + "(D) 39", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 39", + "(B) 48", + "(C) 42", + "(D) 46", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 44", + "(B) 47", + "(C) 41", + "(D) 38", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 43", + "(B) 41", + "(C) 39", + "(D) 47", + "(E) Unable to decide" + ], + "Answer": "43", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 47", + "(D) 42", + "(E) Unable to decide" + ], + "Answer": "40", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 39", + "(B) 42", + "(C) 47", + "(D) 51", + "(E) Unable to decide" + ], + "Answer": "47", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 46", + "(B) 48", + "(C) 42", + "(D) 39", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 41", + "(B) 47", + "(C) 38", + "(D) 44", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 46", + "(B) 42", + "(C) 40", + "(D) 38", + "(E) Unable to decide" + ], + "Answer": "42", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 47", + "(B) 39", + "(C) 43", + "(D) 41", + "(E) Unable to decide" + ], + "Answer": "43", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 41", + "(B) 39", + "(C) 43", + "(D) 47", + "(E) Unable to decide" + ], + "Answer": "43", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 35", + "(B) 47", + "(C) 42", + "(D) 38", + "(E) Unable to decide" + ], + "Answer": "42", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 47", + "(B) 39", + "(C) 44", + "(D) 41", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 38", + "(B) 41", + "(C) 47", + "(D) 44", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 39", + "(B) 45", + "(C) 48", + "(D) 42", + "(E) Unable to decide" + ], + "Answer": "45", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 48", + "(B) 40", + "(C) 52", + "(D) 45", + "(E) Unable to decide" + ], + "Answer": "45", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 53", + "(B) 47", + "(C) 42", + "(D) 50", + "(E) Unable to decide" + ], + "Answer": "50", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42", + "(B) 46", + "(C) 48", + "(D) 39", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 47", + "(B) 51", + "(C) 45", + "(D) 49", + "(E) Unable to decide" + ], + "Answer": "49", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 39", + "(B) 48", + "(C) 42", + "(D) 46", + "(E) Unable to decide" + ], + "Answer": "42", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42", + "(B) 46", + "(C) 51", + "(D) 48", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 43", + "(B) 39", + "(C) 45", + "(D) 47", + "(E) Unable to decide" + ], + "Answer": "45", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 41", + "(B) 38", + "(C) 47", + "(D) 44", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 48", + "(B) 39", + "(C) 46", + "(D) 42", + "(E) Unable to decide" + ], + "Answer": "46", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 42", + "(B) 46", + "(C) 38", + "(D) 40", + "(E) Unable to decide" + ], + "Answer": "42", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum temperature during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 41", + "(B) 44", + "(C) 38", + "(D) 47", + "(E) Unable to decide" + ], + "Answer": "44", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) From West to East", + "(B) From North to South", + "(C) From East to West", + "(D) From South to North", + "(E) Unable to decide" + ], + "Answer": "From West to East", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) From West to East", + "(B) From East to West", + "(C) From South to North", + "(D) From North to South", + "(E) Unable to decide" + ], + "Answer": "From North to South", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Towards Northeast", + "(B) Towards Northwest", + "(C) Towards Southwest", + "(D) Towards Southeast", + "(E) Unable to decide" + ], + "Answer": "Towards Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Southward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Westward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Southward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Southward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_019.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Eastward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Westward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Argentina", + "(B) Peru", + "(C) Brazil", + "(D) Colombia", + "(E) Unable to decide" + ], + "Answer": "Brazil", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Southward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Portugal", + "(B) Morocco", + "(C) France", + "(D) Spain", + "(E) Unable to decide" + ], + "Answer": "Spain", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast", + "(B) Southeast", + "(C) Southwest", + "(D) Northwest", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Northward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_035.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mexico", + "(B) United States", + "(C) Canada", + "(D) Greenland", + "(E) Unable to decide" + ], + "Answer": "Canada", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Brazil", + "(B) Argentina", + "(C) Peru", + "(D) Colombia", + "(E) Unable to decide" + ], + "Answer": "Brazil", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_031.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Westward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Northeast", + "(D) Southeast", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Algeria", + "(B) Libya", + "(C) Tunisia", + "(D) Egypt", + "(E) Unable to decide" + ], + "Answer": "Libya", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeast", + "(B) Southwest", + "(C) Northwest", + "(D) Northeast", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northwest", + "(B) Southeast", + "(C) Northeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Answer": "Southeast", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Peru", + "(B) Brazil", + "(C) Argentina", + "(D) Colombia", + "(E) Unable to decide" + ], + "Answer": "Brazil", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event intensity identification/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the direction of the front system during this period?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northwestward", + "(D) Westward", + "(E) Unable to decide" + ], + "Answer": "Eastward", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Short-term_weather_events/Perception/Event_localization.json b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_localization.json new file mode 100644 index 0000000000000000000000000000000000000000..b5e7962d79f01b4db305d43df956efcff4999349 --- /dev/null +++ b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_localization.json @@ -0,0 +1,3642 @@ +[ + { + "Question_id": "Event localization/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Germany", + "(B) Spain", + "(C) Italy", + "(D) France", + "(E) Unable to decide" + ], + "Answer": "Spain", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southwest United States", + "(C) Midwest United States", + "(D) Northeast United States", + "(E) Unable to decide" + ], + "Answer": "Southwest United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Midwestern United States", + "(B) Northeastern United States", + "(C) Pacific Northwest", + "(D) Southern United States", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mid South United States", + "(B) Pacific Northwest", + "(C) Northeast United States", + "(D) Southwest Canada", + "(E) Unable to decide" + ], + "Answer": "Mid South United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Greenland", + "(B) Mexico", + "(C) Canada", + "(D) United States", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Great Lakes Region", + "(B) Northeast United States", + "(C) Southwest United States", + "(D) Pacific Northwest", + "(E) Unable to decide" + ], + "Answer": "Southwest United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Greenland", + "(B) Mexico", + "(C) Canada", + "(D) United States", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Eastern United States", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mexico", + "(B) California", + "(C) Texas", + "(D) Arizona", + "(E) Unable to decide" + ], + "Answer": "Mexico", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeast United States", + "(B) Midwest United States", + "(C) Southwest United States", + "(D) Southeast United States", + "(E) Unable to decide" + ], + "Answer": "Southwest United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) United States", + "(B) Mexico", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Iberian Peninsula", + "(B) Balkans", + "(C) Central Europe", + "(D) Sahel region", + "(E) Unable to decide" + ], + "Answer": "Sahel region", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Northeastern United States", + "(C) Southern United States", + "(D) Midwestern United States", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Mexico", + "(B) Southeastern United States", + "(C) Eastern Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Canada", + "(B) United States", + "(C) Mexico", + "(D) Greenland", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Central Canada", + "(C) Northern Mexico", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western Canada", + "(B) Southern Mexico", + "(C) Northeastern United States", + "(D) Middle United States", + "(E) Unable to decide" + ], + "Answer": "Middle United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Central Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Western United States", + "(D) Central Canada", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southeastern Mexico", + "(B) Central Canada", + "(C) Western United States", + "(D) Eastern United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Eastern Europe", + "(C) Northern Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Eastern United States", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Central Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Answer": "Western United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Midwestern United States", + "(B) Pacific Northwest", + "(C) Northeastern United States", + "(D) Southern United States", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Mexico", + "(B) California", + "(C) Florida", + "(D) Texas", + "(E) Unable to decide" + ], + "Answer": "Mexico", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southern United States", + "(C) Great Lakes Region", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southern United States", + "(C) Northeastern United States", + "(D) Great Lakes region", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Southern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Northeastern Canada", + "(C) Southern Mexico", + "(D) Middle United States", + "(E) Unable to decide" + ], + "Answer": "Middle United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) United States", + "(B) Mexico", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/00_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Northern Australia", + "(C) Southern Australia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Southern Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/01_6h/t-850_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) U.S. & Canada", + "(B) Mexico", + "(C) Cuba", + "(D) Greenland", + "(E) Unable to decide" + ], + "Answer": "U.S. & Canada", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/02_6h/t-850_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Asia", + "(B) East Asia", + "(C) Southeast Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Answer": "East Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/03_6h/t-850_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Maghreb", + "(B) Horn of Africa", + "(C) Southern Africa", + "(D) Sahel", + "(E) Unable to decide" + ], + "Answer": "Sahel", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/04_6h/t-850_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western Europe", + "(B) Central Europe", + "(C) Eastern Europe", + "(D) Northern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/05_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southwestern U.S.", + "(B) Eastern U.S.", + "(C) Western Canada", + "(D) Pacific Northwest", + "(E) Unable to decide" + ], + "Answer": "Eastern U.S.", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/12_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Asia", + "(B) Central Asia", + "(C) Western Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/13_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Australia", + "(B) Papua New Guinea", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/14_6h/t-850_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern U.S.", + "(B) Western Canada", + "(C) Southwestern U.S.", + "(D) Central Mexico", + "(E) Unable to decide" + ], + "Answer": "Eastern U.S.", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/15_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Nigeria", + "(B) South Africa", + "(C) Morocco", + "(D) Kenya", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/16_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) India", + "(B) China", + "(C) South Korea", + "(D) Japan", + "(E) Unable to decide" + ], + "Answer": "China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/17_6h/tp1h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) France", + "(B) Italy", + "(C) Spain", + "(D) Germany", + "(E) Unable to decide" + ], + "Answer": "France", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/18_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Nigeria", + "(B) Morocco", + "(C) Kenya", + "(D) South Africa", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/19_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Eastern Europe", + "(C) Central Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/20_6h/t-850_039.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Indonesia", + "(B) China", + "(C) India", + "(D) Thailand", + "(E) Unable to decide" + ], + "Answer": "India", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/21_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southern Australia", + "(B) New Zealand", + "(C) Eastern Indonesia", + "(D) Northern Australia", + "(E) Unable to decide" + ], + "Answer": "Southern Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/22_6h/t-850_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Germany", + "(B) UK", + "(C) France", + "(D) Netherlands", + "(E) Unable to decide" + ], + "Answer": "UK", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in South America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/23_6h/t-850_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Uruguay", + "(B) Argentina", + "(C) Chile", + "(D) Brazil", + "(E) Unable to decide" + ], + "Answer": "Argentina", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/24_6h/t-850_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Northern India", + "(C) Southeast Asia", + "(D) Southern and Central China", + "(E) Unable to decide" + ], + "Answer": "Southern and Central China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/25_6h/t-850_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Souther United States", + "(B) Pacific Northwest", + "(C) Great Lakes region", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Answer": "Souther United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/26_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Africa", + "(B) Morocco", + "(C) Kenya", + "(D) Nigeria", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/27_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/28_6h/t-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) France", + "(B) Italy", + "(C) United Kingdom", + "(D) Germany", + "(E) Unable to decide" + ], + "Answer": "France", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/29_6h/t-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Western Australia", + "(B) Tasmania", + "(C) Eastern Australia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Western Australia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/30_6h/t-850_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Central Asia", + "(B) Eastern Asia", + "(C) South Asia", + "(D) Southeast Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/31_6h/t-850_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Sahel region", + "(B) Horn of Africa", + "(C) Southern Africa", + "(D) Central Africa", + "(E) Unable to decide" + ], + "Answer": "Sahel region", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/32_6h/t-850_035.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Canada", + "(B) Greenland", + "(C) Mexico", + "(D) United States", + "(E) Unable to decide" + ], + "Answer": "United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in South America?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/33_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Paraguay", + "(B) Chile", + "(C) Brazil", + "(D) Argentina", + "(E) Unable to decide" + ], + "Answer": "Argentina", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/34_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) New Zealand", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/35_6h/t-850_031.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/36_6h/t-850_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern China", + "(C) Northern India", + "(D) Central Mongolia", + "(E) Unable to decide" + ], + "Answer": "Southern China", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/37_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Kenya", + "(B) Nigeria", + "(C) Egypt", + "(D) South Africa", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_043.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_044.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_045.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_046.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_047.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_048.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_049.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_050.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_051.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_052.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_053.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_054.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_055.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_056.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_057.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_058.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/38_6h/t-850_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Pakistan", + "(B) China", + "(C) India", + "(D) Thailand", + "(E) Unable to decide" + ], + "Answer": "India", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Asia?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/39_6h/t-850_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Eastern Asia", + "(B) Southeast Asia", + "(C) South Asia", + "(D) Central Asia", + "(E) Unable to decide" + ], + "Answer": "Eastern Asia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/40_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Nigeria", + "(B) Morocco", + "(C) Libya", + "(D) Algeria", + "(E) Unable to decide" + ], + "Answer": "Algeria", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in North America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_023.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_024.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_025.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_026.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_027.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_028.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_029.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_030.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_031.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_032.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_033.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_034.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_035.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_036.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_037.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_038.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_039.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_040.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_041.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_042.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/41_6h/t-850_043.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northeastern United States", + "(B) Pacific Northwest", + "(C) Southern United States", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Answer": "Southern United States", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/42_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Northern Australia", + "(B) Southern Anstralia", + "(C) Eastern Indonesia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "Southern Anstralia", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/43_6h/t-850_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) UK", + "(B) Netherlands", + "(C) France", + "(D) Germany", + "(E) Unable to decide" + ], + "Answer": "UK", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in South America?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/44_6h/t-850_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Argentina", + "(B) Paraguay", + "(C) Chile", + "(D) Brazil", + "(E) Unable to decide" + ], + "Answer": "Argentina", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Africa?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/45_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) South Africa", + "(B) Nigeria", + "(C) Kenya", + "(D) Egypt", + "(E) Unable to decide" + ], + "Answer": "South Africa", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/70", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Oceania?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/46_6h/t-850_019.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Answer": "New Zealand", + "Question Type": "Single Choice" + }, + { + "Question_id": "Event localization/71", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a front passage event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Which areas are most affected in Europe?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/front_passage/47_6h/t-850_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Answer": "Western Europe", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Short-term_weather_events/Perception/Event_onset_identification.json b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_onset_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..542c8b8a80adb25acbf8e8c443ea89b6ec713a0a --- /dev/null +++ b/jsons/Atmosphere/Short-term_weather_events/Perception/Event_onset_identification.json @@ -0,0 +1,1382 @@ +[ + { + "Question_id": "short_event-Event onset identification-0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 6 hours", + "(B) 24 hours", + "(C) 18 hours", + "(D) 12 hours", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 40.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 10", + "(B) 14 hours", + "(C) 18", + "(D) 22", + "(E) Unable to decide" + ], + "Answer": "14 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 15", + "(B) 21 hours", + "(C) 18", + "(D) 24", + "(E) Unable to decide" + ], + "Answer": "21 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 16 hours", + "(C) 20", + "(D) 8", + "(E) Unable to decide" + ], + "Answer": "16 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 24", + "(C) 20 hours", + "(D) 16", + "(E) Unable to decide" + ], + "Answer": "20 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 18 hours", + "(B) 24", + "(C) 15", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 18 hours", + "(B) 30 hours", + "(C) 12 hours", + "(D) 24 hours", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 30", + "(C) 18", + "(D) 24 hours", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 18 hours", + "(B) 12", + "(C) 30", + "(D) 24", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 19 hours", + "(C) 22", + "(D) 15", + "(E) Unable to decide" + ], + "Answer": "19 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 19 hours", + "(B) 15", + "(C) 22", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "19 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 26", + "(B) 22 hours", + "(C) 18", + "(D) 30", + "(E) Unable to decide" + ], + "Answer": "22 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 30", + "(B) 18 hours", + "(C) 24", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 24 hours", + "(B) 18", + "(C) 12", + "(D) 30", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12 hours", + "(B) 24 hours", + "(C) 18 hours", + "(D) 30 hours", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 27", + "(B) 24", + "(C) 21 hours", + "(D) 18", + "(E) Unable to decide" + ], + "Answer": "21 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 15 hours", + "(B) 12", + "(C) 10", + "(D) 18", + "(E) Unable to decide" + ], + "Answer": "15 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 24", + "(B) 18 hours", + "(C) 30", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 15", + "(B) 21 hours", + "(C) 18", + "(D) 24", + "(E) Unable to decide" + ], + "Answer": "21 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 24", + "(B) 18", + "(C) 21 hours", + "(D) 15", + "(E) Unable to decide" + ], + "Answer": "21 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 40.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 20", + "(B) 12", + "(C) 17 hours", + "(D) 25", + "(E) Unable to decide" + ], + "Answer": "17 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 20", + "(C) 17 hours", + "(D) 14", + "(E) Unable to decide" + ], + "Answer": "17 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 26", + "(B) 30", + "(C) 18", + "(D) 23 hours", + "(E) Unable to decide" + ], + "Answer": "23 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 19 hours", + "(B) 24", + "(C) 12", + "(D) 30", + "(E) Unable to decide" + ], + "Answer": "19 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 20", + "(C) 10", + "(D) 16 hours", + "(E) Unable to decide" + ], + "Answer": "16 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 12", + "(B) 9", + "(C) 24", + "(D) 18 hours", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 17 hours", + "(B) 20", + "(C) 12", + "(D) 14", + "(E) Unable to decide" + ], + "Answer": "17 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 30", + "(B) 18", + "(C) 26", + "(D) 23 hours", + "(E) Unable to decide" + ], + "Answer": "23 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 30.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 18", + "(B) 30", + "(C) 24 hours", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "24 hours", + "Question Type": "Single Choice" + }, + { + "Question_id": "short_event-Event onset identification-29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a heat burst event. Temporal resolution of 1 hours and starting time is 00:00:00 UTC, variable names are noted in image title. How long did the t2m in the area last for more than 35.0 celcius degree?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/OmniEarth_Atmosphere_ERA5/SHORT_EVENT/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Short-term weather events", + "L3-task": "Perception", + "L4-task": "Event onset identification", + "Dataset": "ERA5", + "Answer Choices": [ + "(A) 24", + "(B) 30", + "(C) 18 hours", + "(D) 12", + "(E) Unable to decide" + ], + "Answer": "18 hours", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Pressure_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Pressure_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..d24697afd3bc0507363684bb40b56875e7e0a92d --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Pressure_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Pressure Estimation/0001", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0002", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1006", + "(D) 1008", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0003", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1002", + "(C) 1004", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0004", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0005", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0006", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1000", + "(C) 1002", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0007", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0008", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 994", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0009", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 990", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0010", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 986", + "(C) 992", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0011", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 984", + "(C) 985", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0012", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 972", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0013", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0014", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 966", + "(C) 964", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0015", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 956", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0016", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0017", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 945", + "(C) 940", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0018", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0019", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 925", + "(C) 915", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0020", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 900", + "(B) 895", + "(C) 905", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0021", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 895", + "(B) 900", + "(C) 910", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0022", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 900", + "(C) 905", + "(D) 895", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0023", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 905", + "(C) 900", + "(D) 895", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0024", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 905", + "(C) 910", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0025", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 905", + "(C) 915", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0026", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 900", + "(C) 915", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0027", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 915", + "(C) 920", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0028", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 920", + "(C) 915", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0029", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 925", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0030", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 940", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0031", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0032", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 930", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0033", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 930", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0034", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 940", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0035", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 940", + "(C) 944", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0036", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0037", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 945", + "(C) 948", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0038", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 945", + "(C) 948", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0039", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 940", + "(C) 948", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0040", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 950", + "(C) 952", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0041", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 960", + "(B) 956", + "(C) 964", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0042", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0043", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 972", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0044", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 982", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0045", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 982", + "(C) 985", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0046", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 984", + "(C) 985", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0047", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 990", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0048", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 990", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0049", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0050", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0051", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0052", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0053", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0054", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 985", + "(C) 986", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0055", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 980", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0056", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 970", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0057", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0058", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0059", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 950", + "(C) 945", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0060", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 955", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0061", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 956", + "(C) 955", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0062", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 965", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0063", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0064", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 975", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0065", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0066", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 978", + "(C) 976", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0067", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 982", + "(C) 986", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0068", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 988", + "(C) 985", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0069", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 990", + "(C) 992", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0070", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0071", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0072", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 994", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0073", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0074", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1008", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0075", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0076", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 1004", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0077", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1000", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0078", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1006", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0079", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0080", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1000", + "(C) 1002", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0081", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1000", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0082", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0083", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 994", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0084", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0085", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 998", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0086", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0087", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 986", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0088", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 990", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0089", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 986", + "(C) 992", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0090", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 990", + "(C) 986", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0091", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 984", + "(C) 986", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0092", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 986", + "(C) 982", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0093", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 978", + "(C) 980", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0094", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 980", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0095", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 972", + "(C) 975", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0096", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 972", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0097", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 970", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0098", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0099", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 965", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0100", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 964", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0101", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0102", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 964", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0103", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 952", + "(C) 954", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0104", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0105", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 952", + "(C) 950", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0106", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 948", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0107", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0108", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0109", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0110", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 952", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0111", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0112", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 956", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0113", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 956", + "(C) 960", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0114", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0115", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 956", + "(C) 960", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0116", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 955", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0117", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0118", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0119", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 960", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0120", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 966", + "(C) 964", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0121", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0122", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 964", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0123", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0124", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 964", + "(C) 956", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0125", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 964", + "(C) 956", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0126", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 960", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0127", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 956", + "(C) 955", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0128", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 960", + "(B) 964", + "(C) 956", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0129", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0130", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 970", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0131", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 978", + "(C) 972", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0132", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 980", + "(C) 982", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0133", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 986", + "(C) 985", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0134", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 984", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0135", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 985", + "(C) 984", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0136", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 984", + "(C) 985", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0137", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 984", + "(C) 982", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0138", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 984", + "(C) 985", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0139", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 982", + "(C) 984", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0140", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 992", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0141", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 990", + "(C) 986", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0142", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 986", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0143", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 986", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0144", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0145", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 986", + "(C) 988", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0146", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 988", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0147", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 994", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0148", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0149", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0150", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0151", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 996", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0152", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0153", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0154", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 990", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0155", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1008", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0156", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 1006", + "(D) 1008", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0157", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0158", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1000", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0159", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 998", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0160", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0161", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1000", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0162", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0163", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 994", + "(C) 992", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0164", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 986", + "(C) 982", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0165", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0166", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 955", + "(C) 956", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0167", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 955", + "(C) 956", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0168", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 952", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0169", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0170", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 915", + "(C) 925", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0171", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 925", + "(C) 910", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0172", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 910", + "(C) 915", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0173", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 940", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0174", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0175", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 950", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0176", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 948", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0177", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 954", + "(C) 952", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0178", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 952", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0179", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 952", + "(C) 950", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0180", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 945", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0181", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 948", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0182", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 935", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0183", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 940", + "(C) 935", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0184", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 944", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0185", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 930", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0186", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 948", + "(C) 940", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0187", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 948", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0188", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 940", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0189", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 944", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0190", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 948", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0191", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0192", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0193", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 964", + "(C) 955", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0194", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 960", + "(C) 964", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0195", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 965", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0196", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 966", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0197", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 975", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0198", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0199", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 972", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0200", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 978", + "(C) 980", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0201", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 978", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0202", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 978", + "(C) 972", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0203", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 965", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0204", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 960", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0205", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 965", + "(C) 960", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0206", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 966", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0207", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 965", + "(C) 960", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0208", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 966", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0209", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 970", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0210", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 978", + "(C) 976", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0211", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 976", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0212", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 998", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0213", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1000", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0214", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1004", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0215", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0216", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1000", + "(C) 1002", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0217", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0218", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0219", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0220", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 988", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0221", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 986", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0222", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 986", + "(C) 982", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0223", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 982", + "(C) 976", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0224", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0225", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 966", + "(C) 968", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0226", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 954", + "(C) 956", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0227", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 954", + "(C) 956", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0228", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0229", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 920", + "(C) 925", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0230", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 920", + "(C) 915", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0231", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0232", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0233", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 952", + "(C) 954", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0234", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 956", + "(C) 954", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0235", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 954", + "(C) 952", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0236", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 956", + "(C) 955", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0237", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0238", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0239", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 930", + "(C) 925", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0240", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 905", + "(B) 920", + "(C) 910", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0241", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 915", + "(C) 905", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0242", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 925", + "(C) 930", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0243", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0244", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 955", + "(C) 956", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0245", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0246", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 985", + "(C) 986", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0247", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0248", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1006", + "(C) 1008", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0249", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0250", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1008", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0251", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0252", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0253", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 1000", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0254", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0255", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0256", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0257", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1004", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0258", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0259", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0260", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0261", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0262", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0263", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 996", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0264", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0265", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0266", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0267", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 994", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0268", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 990", + "(C) 986", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0269", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 990", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0270", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 988", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0271", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 990", + "(C) 986", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0272", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 984", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0273", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 980", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0274", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 975", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0275", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 970", + "(C) 972", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0276", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 955", + "(C) 952", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0277", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 956", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0278", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 952", + "(C) 954", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0279", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 952", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0280", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0281", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 948", + "(C) 944", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0282", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 948", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0283", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 948", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0284", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 950", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0285", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 950", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0286", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 956", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0287", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 956", + "(C) 952", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0288", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 960", + "(C) 956", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0289", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 968", + "(C) 966", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0290", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0291", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0292", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 975", + "(C) 972", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0293", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 975", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0294", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 975", + "(C) 972", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0295", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0296", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 978", + "(C) 976", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0297", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 975", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0298", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 968", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0299", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0300", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0301", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 970", + "(C) 965", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0302", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 970", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0303", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0304", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0305", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1000", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0306", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0307", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 998", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0308", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 980", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0309", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 978", + "(C) 980", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0310", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 972", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0311", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0312", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 964", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0313", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 955", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0314", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 948", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0315", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 945", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0316", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0317", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 910", + "(C) 925", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0318", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 915", + "(C) 925", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0319", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 925", + "(C) 915", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0320", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 925", + "(C) 920", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0321", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0322", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0323", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 944", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0324", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0325", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0326", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 940", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0327", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 925", + "(C) 920", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0328", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 915", + "(C) 930", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0329", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 920", + "(C) 930", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0330", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 940", + "(C) 935", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0331", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 935", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0332", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 948", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0333", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0334", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 956", + "(C) 952", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0335", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 960", + "(C) 955", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0336", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 960", + "(C) 956", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0337", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 955", + "(C) 960", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0338", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 955", + "(C) 964", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0339", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 964", + "(C) 955", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0340", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 952", + "(C) 950", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0342", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 948", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0343", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0344", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 945", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0345", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0346", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0347", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 945", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0348", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 940", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0349", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0350", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0351", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 948", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0352", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0353", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 952", + "(C) 954", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0354", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0355", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 960", + "(B) 956", + "(C) 955", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0356", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 964", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0357", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 968", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0358", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 970", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0359", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 970", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0360", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0361", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 978", + "(C) 976", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0362", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 980", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0363", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 980", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0364", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 965", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0365", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0366", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 970", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0367", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 975", + "(C) 972", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0368", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 978", + "(C) 976", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0369", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 982", + "(C) 985", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0370", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 988", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0371", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 994", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0372", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0373", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 1000", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0374", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0375", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0376", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0377", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0378", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 992", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0379", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0380", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 994", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0381", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 990", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0382", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 986", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0383", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 982", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0384", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 968", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0385", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 960", + "(B) 955", + "(C) 964", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0386", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 940", + "(C) 944", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0387", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 944", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0388", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 930", + "(C) 915", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0389", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 910", + "(C) 920", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0390", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 900", + "(B) 905", + "(C) 915", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0391", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 905", + "(B) 915", + "(C) 910", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0392", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 905", + "(C) 915", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0393", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 900", + "(B) 915", + "(C) 905", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0394", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 905", + "(B) 915", + "(C) 910", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0395", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 900", + "(C) 905", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0396", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 910", + "(C) 900", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0397", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 905", + "(B) 920", + "(C) 910", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0398", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 910", + "(C) 920", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0399", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 915", + "(C) 925", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0400", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 925", + "(C) 930", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0401", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 920", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0402", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 935", + "(C) 920", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0403", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 930", + "(C) 935", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0404", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 945", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0405", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 945", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0406", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0407", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0408", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 964", + "(C) 955", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0409", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 966", + "(C) 968", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0410", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0411", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 972", + "(C) 975", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0412", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 972", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0413", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 975", + "(C) 976", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0414", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 978", + "(C) 976", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0415", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 982", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0416", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 982", + "(C) 984", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0417", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 985", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0418", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 994", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0419", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1000", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0420", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1002", + "(C) 1004", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0421", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1002", + "(C) 1006", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0422", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1006", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0423", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 1004", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0424", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1004", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0425", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 996", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0426", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0427", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 996", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0428", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 992", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0429", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 988", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0430", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 982", + "(C) 986", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0431", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0432", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 956", + "(C) 955", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0433", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 952", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0434", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 940", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0435", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 935", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0436", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 952", + "(C) 955", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0437", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0438", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0439", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 982", + "(C) 980", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0440", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0441", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 964", + "(C) 968", + "(D) 965", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0442", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 952", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0443", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0444", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 950", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0445", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 965", + "(C) 966", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0446", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 980", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0447", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 986", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0448", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 992", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0449", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0450", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1000", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0451", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0452", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1000", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0453", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0454", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1006", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0455", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1000", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0456", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 998", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0457", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1000", + "(C) 1002", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0458", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1002", + "(C) 1004", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0459", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0460", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0461", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 996", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0462", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 986", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0463", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 982", + "(C) 986", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0464", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 982", + "(C) 980", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0465", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 978", + "(C) 982", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0466", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 970", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0467", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 965", + "(B) 968", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0468", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 950", + "(C) 952", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0469", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0470", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 925", + "(C) 920", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0471", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 930", + "(C) 925", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0472", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 915", + "(C) 920", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0473", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 930", + "(C) 920", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0474", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 915", + "(C) 925", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0475", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0476", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 954", + "(C) 952", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0477", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0478", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 956", + "(C) 952", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0479", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0480", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0481", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0482", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0483", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 966", + "(C) 965", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0484", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 984", + "(B) 985", + "(C) 986", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0485", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0486", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0487", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1000", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0488", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0489", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 1000", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0490", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 994", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0491", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0492", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1000", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0493", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0494", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0495", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1008", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0496", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1002", + "(C) 1000", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0497", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0498", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1000", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0499", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0500", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0501", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0502", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0503", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0504", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 994", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0505", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 985", + "(C) 982", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0506", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 982", + "(C) 978", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0507", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0508", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 965", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0509", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 956", + "(C) 960", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0510", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 950", + "(C) 948", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0511", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 948", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0512", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 948", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0513", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 944", + "(C) 940", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0514", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 940", + "(C) 948", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0515", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 940", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0516", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 930", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0517", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 930", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0518", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0519", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0520", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 925", + "(C) 935", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0521", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 925", + "(C) 930", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0522", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 920", + "(C) 925", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0523", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 925", + "(C) 930", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0524", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 935", + "(C) 925", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0525", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 935", + "(C) 925", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0526", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0527", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 930", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0528", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0529", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0530", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0531", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 940", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0532", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 930", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0533", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0534", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 935", + "(C) 944", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0535", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0536", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 940", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0537", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 940", + "(C) 945", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0538", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 948", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0539", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 944", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0540", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 960", + "(B) 955", + "(C) 956", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0541", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 964", + "(C) 956", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0542", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 965", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0543", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 965", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0544", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0545", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0546", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 970", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0547", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0548", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0549", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 970", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0550", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0551", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 970", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0552", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0553", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0554", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0555", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0556", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 968", + "(C) 972", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0557", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0558", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0559", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 966", + "(C) 972", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0560", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 970", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0561", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0562", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0563", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0564", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0565", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0566", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 970", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0567", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0568", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 970", + "(C) 972", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0569", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 968", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0570", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 966", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0571", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 970", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0572", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 972", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0573", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 975", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0574", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 972", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0575", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 975", + "(C) 978", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0576", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 976", + "(C) 975", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0577", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 978", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0578", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 966", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0579", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 966", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0580", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0581", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 970", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0582", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0583", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 970", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0584", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 970", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0585", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 970", + "(C) 966", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0586", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0587", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0588", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 975", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0589", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 972", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0590", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 972", + "(C) 975", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0591", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 978", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0592", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 976", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0593", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 986", + "(C) 988", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0594", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0595", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0596", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 992", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0597", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0598", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 1000", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0599", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0600", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1008", + "(C) 1004", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0601", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 1006", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0602", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1000", + "(C) 1006", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0603", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1002", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0604", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1006", + "(D) 1008", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0605", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0606", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 1006", + "(D) 1008", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0607", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1006", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0608", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1008", + "(C) 1006", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0609", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0610", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0611", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0612", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0613", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0614", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 982", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0615", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 978", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0616", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 966", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0617", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 954", + "(C) 952", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0618", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 948", + "(C) 952", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0619", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 935", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0620", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 940", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0621", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 945", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0622", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 945", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0623", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 952", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0624", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 960", + "(C) 964", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0625", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 954", + "(C) 955", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0626", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 955", + "(C) 956", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0627", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 954", + "(C) 955", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0628", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 954", + "(C) 952", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0629", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0630", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 944", + "(C) 945", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0631", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 930", + "(C) 940", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0632", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 910", + "(C) 925", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0633", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 910", + "(C) 920", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0634", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 910", + "(C) 925", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0635", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 920", + "(C) 925", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0636", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 925", + "(C) 910", + "(D) 915", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0637", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 910", + "(C) 915", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0638", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 944", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0639", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 945", + "(C) 940", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0640", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 944", + "(C) 940", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0641", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0642", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0643", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 966", + "(C) 972", + "(D) 968", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0644", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 982", + "(C) 980", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0645", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 986", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0646", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0647", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 996", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0648", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0649", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0650", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 996", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0651", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0652", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1008", + "(C) 1006", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0653", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1006", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0654", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1006", + "(C) 1000", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0655", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 998", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0656", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0657", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1000", + "(C) 998", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0658", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0659", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 998", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0660", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 996", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0661", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0662", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 988", + "(C) 992", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0663", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 992", + "(C) 988", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0664", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 986", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0665", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 985", + "(C) 984", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0666", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 980", + "(C) 982", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0667", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 978", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0668", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0669", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 955", + "(C) 954", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0670", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 930", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0671", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 905", + "(B) 915", + "(C) 900", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0672", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 900", + "(B) 905", + "(C) 910", + "(D) 895", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0673", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 900", + "(B) 905", + "(C) 910", + "(D) 895", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0674", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 905", + "(C) 895", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0675", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 895", + "(B) 905", + "(C) 910", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0676", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 900", + "(C) 905", + "(D) 895", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0677", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 915", + "(C) 925", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0678", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 925", + "(B) 915", + "(C) 920", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0679", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0680", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 944", + "(C) 940", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0681", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 948", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0682", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 952", + "(C) 954", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0683", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 948", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0684", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 948", + "(C) 950", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0685", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 948", + "(C) 954", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0686", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 952", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0687", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 954", + "(B) 952", + "(C) 955", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0688", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 954", + "(C) 952", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0689", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 952", + "(C) 956", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0690", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0691", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1006", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0692", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1008", + "(B) 1006", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0693", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1006", + "(C) 1004", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0694", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0695", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0696", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0697", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 994", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0698", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0699", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 988", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0700", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 990", + "(C) 988", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0701", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 984", + "(C) 986", + "(D) 985", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0702", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 980", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0703", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 980", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0704", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 976", + "(C) 978", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0705", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 976", + "(C) 975", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0706", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 972", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0707", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 966", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0708", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 964", + "(B) 968", + "(C) 965", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0709", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 956", + "(C) 955", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0710", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 952", + "(C) 954", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0711", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 948", + "(C) 944", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0712", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 945", + "(D) 948", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0713", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 935", + "(C) 944", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0714", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 940", + "(C) 935", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0715", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 952", + "(C) 954", + "(D) 950", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0716", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 956", + "(C) 960", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0717", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 972", + "(C) 968", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0718", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 972", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0719", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 968", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0720", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 972", + "(C) 976", + "(D) 975", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0721", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 982", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0722", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 980", + "(C) 982", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0723", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 982", + "(C) 985", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0724", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 985", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0725", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 990", + "(C) 986", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0726", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 994", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0727", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0728", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0729", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0730", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0731", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0732", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0733", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 996", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0734", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0735", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1004", + "(C) 1002", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0736", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1006", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0737", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 1004", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0738", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 996", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0739", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1002", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0740", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0741", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0742", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 990", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0743", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 998", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0744", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 1002", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0745", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0746", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 994", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0747", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 986", + "(B) 988", + "(C) 992", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0748", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 982", + "(C) 978", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0749", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 972", + "(C) 966", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0750", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 954", + "(C) 956", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0751", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 935", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0752", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 925", + "(C) 915", + "(D) 930", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0753", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 905", + "(C) 920", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0754", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 915", + "(C) 905", + "(D) 910", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0755", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 910", + "(C) 915", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0756", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 905", + "(C) 910", + "(D) 920", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0757", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 915", + "(C) 910", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0758", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 910", + "(B) 915", + "(C) 920", + "(D) 905", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0759", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 920", + "(B) 935", + "(C) 930", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0760", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 945", + "(C) 948", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0761", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 935", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0762", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 930", + "(C) 944", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0763", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 980", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0764", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0765", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 996", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0766", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0767", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 998", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0768", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0769", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0770", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0771", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 998", + "(C) 996", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0772", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 998", + "(C) 1000", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0773", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0774", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1000", + "(C) 1002", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0775", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 996", + "(C) 994", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0776", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0777", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 998", + "(C) 996", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0778", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 998", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0779", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 992", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0780", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 996", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0781", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0782", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 988", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0783", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 994", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0784", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 988", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0785", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0786", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 986", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0787", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 992", + "(C) 986", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0788", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 985", + "(C) 986", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0789", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 984", + "(C) 986", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0790", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 982", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0791", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 976", + "(C) 982", + "(D) 980", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0792", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 978", + "(C) 976", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0793", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 972", + "(C) 976", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0794", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 975", + "(C) 976", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0795", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 966", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0796", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 965", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0797", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 968", + "(B) 965", + "(C) 964", + "(D) 966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0798", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 966", + "(B) 968", + "(C) 965", + "(D) 964", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0799", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 972", + "(B) 966", + "(C) 968", + "(D) 970", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0800", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 982", + "(B) 976", + "(C) 980", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0801", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 984", + "(C) 986", + "(D) 982", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0802", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 992", + "(B) 994", + "(C) 990", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0803", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0804", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1004", + "(C) 1000", + "(D) 1006", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0805", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1002", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0806", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1008", + "(C) 1002", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0807", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1006", + "(C) 1008", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0808", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 1002", + "(C) 1006", + "(D) 1008", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0809", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1008", + "(C) 1006", + "(D) 1004", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0810", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1004", + "(B) 998", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0811", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1002", + "(B) 1000", + "(C) 998", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0812", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 1002", + "(C) 996", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0813", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 998", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0814", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 998", + "(B) 994", + "(C) 1000", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0815", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 994", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0816", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 994", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0817", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 998", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0818", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 992", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0819", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 994", + "(B) 996", + "(C) 990", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0820", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 992", + "(C) 990", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0821", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 996", + "(C) 992", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0822", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 994", + "(D) 996", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0823", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 988", + "(C) 986", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0824", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 986", + "(C) 982", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0825", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 985", + "(B) 984", + "(C) 982", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0826", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 980", + "(B) 976", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0827", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 978", + "(B) 975", + "(C) 972", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0828", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 975", + "(B) 976", + "(C) 978", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0829", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 970", + "(B) 966", + "(C) 968", + "(D) 972", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0830", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 955", + "(B) 960", + "(C) 964", + "(D) 956", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0831", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 948", + "(B) 950", + "(C) 952", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0832", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 948", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0833", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 930", + "(B) 944", + "(C) 935", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0834", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 915", + "(B) 930", + "(C) 920", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0835", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 935", + "(B) 930", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0836", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 940", + "(B) 945", + "(C) 935", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0837", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 944", + "(B) 935", + "(C) 945", + "(D) 940", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0838", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 945", + "(B) 935", + "(C) 940", + "(D) 944", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0839", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 950", + "(B) 954", + "(C) 948", + "(D) 952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0840", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 952", + "(B) 950", + "(C) 948", + "(D) 954", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0841", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 956", + "(B) 960", + "(C) 964", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0842", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 976", + "(B) 980", + "(C) 982", + "(D) 978", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0843", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 988", + "(B) 990", + "(C) 992", + "(D) 986", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0844", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 990", + "(B) 992", + "(C) 996", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0845", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 998", + "(C) 994", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0846", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 996", + "(B) 994", + "(C) 1000", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0847", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1000", + "(B) 1002", + "(C) 996", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Pressure Estimation/0848", + "Text": "The provided image represents a typhoon. What is its pressure (hpa)?", + "Answer Choices": [ + "(A) 1006", + "(B) 1004", + "(C) 1000", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Pressure Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Gale_Axis_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Gale_Axis_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..a8d52a781f14c3c51e5796564a58fe95ac181d58 --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Gale_Axis_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Radius of Major Gale Axis Estimation/0001", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0002", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0003", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0004", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0005", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0006", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0007", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0008", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 130", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0009", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0010", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0011", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 130", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0012", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 130", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0013", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0014", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0015", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0016", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0017", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0018", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0019", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0020", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0021", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0022", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0023", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0024", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0025", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0026", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0027", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0028", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0029", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0030", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0031", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0032", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0033", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0034", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0035", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0036", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 190", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0037", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0038", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 190", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0039", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 190", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0040", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0041", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 150", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0042", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0043", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 190", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0044", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0045", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0046", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0047", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0048", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0049", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0050", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0051", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0052", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0053", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0054", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0055", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0056", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0057", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0058", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0059", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0060", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0061", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0062", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0063", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0064", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0065", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0066", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0067", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0068", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0069", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0070", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0071", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0072", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0073", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0074", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0075", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0076", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0077", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0078", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0079", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0080", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0081", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0082", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0083", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0084", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0085", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0086", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0087", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0088", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0089", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0090", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0091", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0092", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0093", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0094", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0095", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0096", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0097", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0098", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0099", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0100", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0101", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0102", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0103", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0104", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0105", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0106", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0107", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0108", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0109", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0110", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0111", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0112", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0113", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0114", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0115", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0116", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0117", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0118", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0119", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0120", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0121", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0122", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0123", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0124", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0125", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0126", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0127", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0128", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0129", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0130", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0131", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0132", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0133", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0134", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 190", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0135", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0136", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0137", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0138", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0139", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0140", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0141", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0142", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0143", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0144", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0145", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0146", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0147", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0148", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0149", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0150", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0151", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0152", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0153", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0154", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0155", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0156", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0157", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0158", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0159", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0160", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 190", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0161", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0162", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0163", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0164", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0165", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0166", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0167", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 190", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0168", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0169", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0170", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0171", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0172", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0173", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0174", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0175", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0176", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0177", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0178", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0179", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0180", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0181", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0182", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0183", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0184", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0185", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0186", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0187", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0188", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0189", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 425", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0190", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0191", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0192", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0193", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0194", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0195", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0196", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 500", + "(B) 450", + "(C) 425", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0197", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0198", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0199", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0200", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0201", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0202", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0203", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0204", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0205", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0206", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0207", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0208", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0209", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0210", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0211", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0212", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0213", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0214", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0215", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0216", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0217", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0218", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 190", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0219", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0220", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 190", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0221", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0222", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0223", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0224", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 190", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0225", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0226", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0227", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0228", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0229", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0230", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0231", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0232", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0233", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0234", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0235", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0236", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0237", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0238", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0239", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0240", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0241", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0242", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0243", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0244", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0245", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0246", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0247", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0248", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0249", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0250", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0251", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0252", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0253", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0254", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0255", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0256", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0257", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0258", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0259", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0260", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 190", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0261", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0262", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0263", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0264", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0265", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0266", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0267", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0268", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0269", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0270", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0271", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0272", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0273", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0274", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0275", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0276", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0277", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0278", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 425", + "(C) 400", + "(D) 450", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0279", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 400", + "(C) 375", + "(D) 450", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0280", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 425", + "(D) 450", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0281", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 450", + "(C) 425", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0282", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 450", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0283", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 500", + "(C) 425", + "(D) 450", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0284", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 400", + "(C) 500", + "(D) 450", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0285", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 500", + "(C) 450", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0286", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 450", + "(B) 400", + "(C) 425", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0287", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 450", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0288", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 500", + "(C) 450", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0289", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 500", + "(C) 450", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0290", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 450", + "(B) 425", + "(C) 500", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0291", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 450", + "(C) 425", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0292", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0293", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0294", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0295", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0296", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0297", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0298", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0299", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0300", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0301", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0302", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0303", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0304", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0305", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0306", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0307", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 90", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0308", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0309", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0310", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 130", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0311", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0312", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0313", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0314", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0315", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 90", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0316", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0317", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0318", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 90", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0319", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0320", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0321", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 130", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0322", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 90", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0323", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0324", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 90", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0325", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0326", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0327", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 190", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0328", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0329", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0330", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0331", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0332", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0333", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0334", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0335", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0336", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0337", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0338", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0339", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0340", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0342", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0343", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0344", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0345", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0346", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0347", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0348", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0349", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0350", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0351", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0352", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0353", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0354", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0355", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0356", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0357", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0358", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0359", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0360", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0361", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0362", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0363", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0364", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0365", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0366", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0367", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0368", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0369", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0370", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0371", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0372", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0373", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0374", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0375", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0376", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0377", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 190", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0378", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0379", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0380", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0381", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0382", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0383", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0384", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0385", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0386", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0387", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0388", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 375", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0389", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 375", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0390", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 425", + "(C) 375", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0391", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 375", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0392", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0393", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 400", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0394", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 425", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0395", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0396", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 425", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0397", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0398", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 425", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0399", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 425", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0400", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0401", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0402", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 425", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0403", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 400", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0404", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0405", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0406", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0407", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0408", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0409", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0410", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0411", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0412", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0413", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0414", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 425", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0415", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0416", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 350", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0417", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0418", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0419", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0420", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0421", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0422", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0423", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0424", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0425", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0426", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0427", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 130", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0428", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0429", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 90", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0430", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 150", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0431", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0432", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 90", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0433", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0434", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 90", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0435", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0436", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0437", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0438", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0439", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 150", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0440", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0441", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0442", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 190", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0443", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 190", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0444", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0445", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0446", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0447", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0448", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0449", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0450", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0451", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0452", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0453", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0454", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0455", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0456", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0457", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0458", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0459", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0460", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0461", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0462", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0463", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0464", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0465", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0466", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0467", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0468", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0469", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0470", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0471", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0472", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0473", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0474", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0475", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0476", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0477", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0478", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0479", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0480", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0481", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0482", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0483", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 400", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0484", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0485", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0486", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0487", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0488", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0489", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0490", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0491", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0492", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0493", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0494", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0495", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0496", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0497", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0498", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0499", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0500", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0501", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0502", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0503", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0504", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0505", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0506", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0507", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0508", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0509", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0510", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0511", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0512", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0513", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0514", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0515", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0516", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0517", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0518", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0519", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0520", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0521", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0522", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0523", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0524", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0525", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0526", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0527", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0528", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0529", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0530", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0531", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0532", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0533", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0534", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0535", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0536", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 375", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0537", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0538", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0539", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0540", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0541", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 400", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0542", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0543", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0544", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0545", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0546", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0547", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0548", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0549", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0550", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0551", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0552", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0553", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0554", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0555", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0556", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0557", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0558", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0559", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0560", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0561", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0562", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0563", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0564", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0565", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0566", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0567", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0568", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0569", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0570", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0571", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0572", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0573", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0574", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0575", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0576", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0577", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0578", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0579", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0580", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0581", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0582", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0583", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0584", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0585", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0586", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0587", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0588", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0589", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0590", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0591", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0592", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0593", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0594", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0595", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0596", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0597", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0598", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0599", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0600", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0601", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0602", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0603", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0604", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0605", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0606", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0607", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0608", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0609", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0610", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0611", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0612", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0613", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0614", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0615", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0616", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 130", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0617", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0618", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0619", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0620", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0621", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0622", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 180", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0623", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 130", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0624", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 130", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0625", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0626", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0627", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0628", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0629", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 130", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0630", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0631", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0632", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0633", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0634", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0635", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0636", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0637", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0638", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0639", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0640", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0641", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0642", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0643", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 130", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0644", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0645", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0646", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0647", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0648", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0649", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0650", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0651", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0652", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0653", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0654", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0655", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0656", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 150", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0657", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0658", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0659", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0660", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0661", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0662", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0663", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0664", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0665", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0666", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0667", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0668", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0669", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0670", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0671", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0672", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0673", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0674", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0675", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0676", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0677", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0678", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0679", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 425", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0680", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 375", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0681", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0682", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 375", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0683", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 425", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0684", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0685", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0686", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0687", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0688", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0689", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0690", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0691", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0692", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0693", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0694", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0695", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 190", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0696", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 190", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0697", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0698", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0699", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 190", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0700", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 200", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0701", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0702", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0703", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0704", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0705", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0706", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0707", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0708", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0709", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0710", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0711", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0712", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 350", + "(C) 325", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0713", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0714", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0715", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 325", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0716", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0717", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0718", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0719", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0720", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0721", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 425", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0722", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 425", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0723", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 425", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0724", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 375", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0725", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 375", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0726", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0727", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0728", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0729", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0730", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0731", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0732", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0733", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0734", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0735", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0736", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0737", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0738", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 130", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0739", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0740", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0741", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0742", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 130", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0743", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0744", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 130", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0745", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0746", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 130", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0747", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 130", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0748", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0749", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0750", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0751", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 190", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0752", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0753", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 190", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0754", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 190", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0755", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 190", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0756", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0757", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0758", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0759", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0760", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0761", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0762", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 190", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0763", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0764", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0765", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0766", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 150", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0767", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0768", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0769", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0770", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0771", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0772", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0773", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0774", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0775", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 90", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0776", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0777", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0778", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0779", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0780", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0781", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0782", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0783", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 375", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0784", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0785", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0786", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0787", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0788", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0789", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0790", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 190", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0791", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 180", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0792", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0793", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 190", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0794", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 190", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0795", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0796", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0797", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 130", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0798", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 130", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0799", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 90", + "(C) 120", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0800", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 130", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0801", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0802", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 130", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0803", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0804", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0805", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0806", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0807", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0808", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0809", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0810", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0811", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0812", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0813", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0814", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0815", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 400", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0816", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0817", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 375", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0818", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 425", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0819", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 400", + "(C) 425", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0820", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 400", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0821", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0822", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 375", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0823", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0824", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0825", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0826", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0827", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0828", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0829", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0830", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0831", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0832", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0833", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0834", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 375", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0835", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0836", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 375", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0837", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0838", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0839", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0840", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 375", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0841", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0842", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0843", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0844", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 375", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0845", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 375", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0846", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0847", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Gale Axis Estimation/0848", + "Text": "The provided image represents a typhoon. What is its radius of major gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Storm_Axis_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Storm_Axis_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..ec3484ff4e70eada923f28d54746f68b6ccaaa28 --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Major_Storm_Axis_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Radius of Major Storm Axis Estimation/0001", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0002", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0003", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0004", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0005", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0006", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0007", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0008", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0009", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0010", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0011", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 35", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0012", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0013", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0014", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0015", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0016", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0017", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0018", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0019", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0020", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0021", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0022", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0023", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 140", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0024", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0025", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0026", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0027", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0028", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0029", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0030", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0031", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0032", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0033", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0034", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0035", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0036", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0037", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0038", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0039", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0040", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0041", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0042", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0043", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0044", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0045", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0046", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0047", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0048", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0049", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0050", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0051", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0052", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0053", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0054", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0055", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0056", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0057", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0058", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0059", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0060", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0061", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0062", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0063", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0064", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0065", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0066", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0067", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0068", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0069", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0070", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0071", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0072", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0073", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0074", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0075", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0076", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0077", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0078", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0079", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0080", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0081", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0082", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0083", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0084", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0085", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0086", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0087", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0088", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0089", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0090", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0091", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0092", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0093", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0094", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0095", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0096", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0097", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0098", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0099", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0100", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0101", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0102", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0103", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0104", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0105", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0106", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0107", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0108", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0109", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0110", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0111", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0112", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0113", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0114", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0115", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0116", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0117", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0118", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0119", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0120", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0121", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0122", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0123", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0124", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0125", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0126", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0127", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0128", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0129", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0130", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0131", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0132", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0133", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0134", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0135", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0136", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0137", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0138", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0139", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0140", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0141", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0142", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0143", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0144", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0145", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0146", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0147", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0148", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0149", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0150", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0151", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0152", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0153", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0154", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0155", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0156", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0157", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0158", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0159", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0160", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0161", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0162", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0163", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0164", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0165", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0166", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0167", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0168", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0169", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0170", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0171", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0172", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0173", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0174", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0175", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0176", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0177", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 110", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0178", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0179", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0180", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0181", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0182", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0183", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0184", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0185", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0186", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0187", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0188", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0189", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0190", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0191", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0192", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0193", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0194", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0195", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0196", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0197", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0198", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0199", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0200", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0201", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0202", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0203", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0204", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0205", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0206", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0207", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0208", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0209", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0210", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0211", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0212", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0213", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0214", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0215", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0216", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0217", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0218", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0219", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0220", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0221", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0222", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0223", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0224", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0225", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0226", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0227", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0228", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0229", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0230", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0231", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0232", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0233", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0234", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0235", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0236", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0237", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0238", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0239", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0240", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0241", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0242", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0243", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0244", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0245", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0246", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0247", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0248", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0249", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0250", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0251", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0252", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0253", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0254", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0255", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0256", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0257", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0258", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0259", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0260", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0261", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0262", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0263", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0264", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0265", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0266", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0267", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0268", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0269", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0270", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0271", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0272", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0273", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0274", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0275", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0276", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0277", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0278", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0279", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0280", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0281", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0282", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0283", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0284", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0285", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0286", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 110", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0287", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0288", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0289", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0290", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0291", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0292", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0293", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0294", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0295", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0296", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0297", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0298", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0299", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0300", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0301", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0302", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0303", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0304", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0305", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0306", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0307", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0308", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0309", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 35", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0310", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 30", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0311", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0312", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0313", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 30", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0314", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0315", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0316", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0317", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0318", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0319", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0320", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0321", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0322", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0323", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0324", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0325", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0326", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0327", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0328", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0329", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0330", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0331", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0332", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0333", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0334", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0335", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0336", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0337", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0338", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0339", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0340", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0342", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 150", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0343", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 110", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0344", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0345", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 140", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0346", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0347", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0348", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0349", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0350", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0351", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0352", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0353", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0354", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 140", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0355", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0356", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0357", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0358", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0359", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0360", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0361", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0362", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0363", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0364", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0365", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0366", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0367", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0368", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0369", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0370", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0371", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0372", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0373", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0374", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0375", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0376", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0377", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0378", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0379", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0380", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0381", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0382", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0383", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0384", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0385", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0386", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0387", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0388", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 70", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0389", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0390", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0391", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0392", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0393", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0394", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0395", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0396", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0397", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 110", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0398", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0399", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0400", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0401", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0402", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0403", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0404", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0405", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0406", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 110", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0407", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0408", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0409", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0410", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0411", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0412", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0413", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0414", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0415", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0416", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0417", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0418", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0419", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0420", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0421", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0422", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0423", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0424", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0425", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0426", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0427", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0428", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0429", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0430", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0431", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0432", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 30", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0433", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0434", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0435", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0436", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0437", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0438", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0439", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 40", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0440", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0441", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0442", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0443", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0444", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0445", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0446", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0447", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0448", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0449", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0450", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0451", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0452", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0453", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0454", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0455", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0456", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0457", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0458", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0459", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0460", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0461", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0462", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0463", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0464", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0465", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 55", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0466", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0467", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0468", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0469", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0470", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0471", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0472", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0473", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 110", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0474", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0475", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0476", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0477", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0478", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0479", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0480", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 55", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0481", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0482", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0483", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0484", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0485", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0486", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0487", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0488", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0489", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0490", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0491", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0492", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0493", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0494", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0495", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0496", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0497", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0498", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0499", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0500", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0501", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0502", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0503", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0504", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0505", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0506", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0507", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0508", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0509", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0510", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0511", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0512", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0513", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0514", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0515", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0516", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0517", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0518", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0519", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0520", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0521", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 150", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0522", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0523", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0524", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0525", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0526", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0527", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0528", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0529", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0530", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0531", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0532", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0533", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0534", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0535", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0536", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0537", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0538", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0539", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0540", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0541", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0542", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0543", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0544", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0545", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0546", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0547", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0548", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 110", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0549", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0550", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0551", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0552", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0553", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 140", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0554", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0555", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0556", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0557", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0558", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0559", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0560", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0561", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0562", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0563", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0564", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0565", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0566", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0567", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0568", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0569", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0570", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0571", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0572", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0573", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0574", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0575", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0576", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0577", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0578", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0579", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0580", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0581", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0582", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0583", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0584", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0585", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0586", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0587", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0588", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0589", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0590", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0591", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0592", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0593", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0594", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0595", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0596", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0597", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0598", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0599", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0600", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0601", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0602", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0603", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0604", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0605", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0606", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0607", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0608", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0609", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0610", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0611", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0612", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0613", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0614", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0615", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0616", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0617", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0618", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0619", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0620", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0621", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0622", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0623", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0624", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0625", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0626", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0627", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0628", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0629", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 30", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0630", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0631", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0632", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0633", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0634", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0635", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0636", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0637", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0638", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0639", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0640", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0641", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0642", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0643", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0644", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0645", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0646", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0647", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0648", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0649", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0650", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0651", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0652", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0653", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0654", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0655", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0656", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0657", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0658", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0659", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0660", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0661", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0662", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0663", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0664", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0665", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 35", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0666", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0667", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0668", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0669", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0670", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0671", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0672", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 55", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0673", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0674", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 70", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0675", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0676", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0677", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0678", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0679", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0680", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 110", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0681", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 110", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0682", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0683", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0684", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0685", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0686", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0687", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0688", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0689", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0690", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0691", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0692", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0693", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0694", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0695", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0696", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0697", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0698", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0699", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0700", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0701", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0702", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0703", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0704", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0705", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0706", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 65", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0707", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0708", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0709", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0710", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0711", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0712", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0713", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0714", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0715", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0716", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0717", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0718", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0719", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0720", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0721", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0722", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0723", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0724", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0725", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0726", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0727", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0728", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0729", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0730", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0731", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0732", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0733", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0734", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0735", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0736", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0737", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0738", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0739", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0740", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0741", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0742", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0743", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0744", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0745", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0746", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0747", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0748", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0749", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0750", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0751", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0752", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0753", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0754", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0755", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 70", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0756", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0757", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0758", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0759", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0760", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0761", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0762", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0763", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0764", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0765", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0766", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0767", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0768", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0769", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0770", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0771", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0772", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0773", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0774", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0775", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0776", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0777", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0778", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0779", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0780", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0781", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0782", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0783", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0784", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0785", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0786", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0787", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0788", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0789", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0790", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0791", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0792", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0793", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0794", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0795", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0796", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0797", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0798", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0799", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0800", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0801", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0802", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0803", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0804", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0805", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0806", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0807", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0808", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0809", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0810", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0811", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0812", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0813", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0814", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0815", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0816", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0817", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0818", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0819", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0820", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0821", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0822", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0823", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0824", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0825", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0826", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0827", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0828", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0829", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0830", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0831", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0832", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0833", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0834", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0835", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0836", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0837", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0838", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0839", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0840", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0841", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0842", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0843", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0844", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0845", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0846", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0847", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Major Storm Axis Estimation/0848", + "Text": "The provided image represents a typhoon. What is its radius of major storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Major Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Gale_Axis_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Gale_Axis_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..e5f6669efd391515b7736f333c6fc2d8877acd5d --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Gale_Axis_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Radius of Minor Gale Axis Estimation/0001", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0002", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0003", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0004", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0005", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0006", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 140", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0007", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 150", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0008", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0009", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0010", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0011", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0012", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0013", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0014", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0015", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0016", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0017", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0018", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0019", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0020", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0021", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0022", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0023", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0024", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0025", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0026", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0027", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0028", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0029", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0030", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0031", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0032", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0033", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0034", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0035", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0036", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0037", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0038", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0039", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0040", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0041", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0042", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0043", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0044", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0045", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0046", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0047", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0048", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0049", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0050", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0051", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0052", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0053", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0054", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0055", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0056", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0057", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0058", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0059", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0060", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0061", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0062", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0063", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0064", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0065", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0066", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0067", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0068", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0069", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0070", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0071", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0072", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0073", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0074", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0075", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0076", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0077", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0078", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0079", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0080", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0081", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0082", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0083", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0084", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0085", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0086", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0087", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0088", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0089", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0090", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0091", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0092", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0093", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0094", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0095", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0096", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0097", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0098", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0099", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0100", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0101", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0102", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0103", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0104", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0105", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0106", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0107", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0108", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0109", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0110", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0111", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0112", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0113", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0114", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0115", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0116", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0117", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0118", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0119", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0120", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0121", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0122", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0123", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0124", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0125", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0126", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0127", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0128", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0129", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0130", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0131", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0132", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0133", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0134", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0135", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0136", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0137", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0138", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0139", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0140", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0141", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0142", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0143", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0144", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0145", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0146", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0147", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0148", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0149", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0150", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0151", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0152", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0153", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0154", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0155", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0156", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0157", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0158", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0159", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0160", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0161", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0162", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0163", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0164", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0165", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0166", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 140", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0167", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0168", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0169", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0170", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0171", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0172", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0173", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0174", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0175", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0176", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0177", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0178", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0179", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0180", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0181", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0182", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0183", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0184", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0185", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0186", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0187", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0188", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0189", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0190", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0191", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0192", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0193", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0194", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0195", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0196", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0197", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0198", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0199", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0200", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0201", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0202", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0203", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0204", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0205", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0206", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0207", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0208", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0209", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0210", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0211", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0212", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0213", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0214", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0215", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0216", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0217", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0218", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0219", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0220", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0221", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0222", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0223", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0224", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0225", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0226", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0227", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0228", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0229", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 180", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0230", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0231", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0232", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0233", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 120", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0234", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0235", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0236", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 140", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0237", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0238", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 180", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0239", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0240", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0241", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0242", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0243", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0244", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0245", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0246", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0247", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0248", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0249", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0250", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0251", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0252", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0253", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0254", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0255", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0256", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0257", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0258", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0259", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0260", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0261", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0262", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 180", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0263", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0264", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0265", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0266", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0267", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0268", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0269", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0270", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0271", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0272", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 400", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0273", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0274", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 400", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0275", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 400", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0276", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0277", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0278", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0279", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0280", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0281", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0282", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0283", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0284", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0285", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0286", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0287", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0288", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0289", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0290", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0291", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0292", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0293", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0294", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0295", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0296", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0297", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0298", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0299", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0300", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0301", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0302", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0303", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0304", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0305", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0306", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0307", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0308", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0309", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0310", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0311", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0312", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0313", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0314", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0315", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0316", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0317", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0318", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0319", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0320", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0321", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0322", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0323", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0324", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0325", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0326", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0327", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0328", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0329", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0330", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 150", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0331", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0332", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0333", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0334", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0335", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0336", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0337", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0338", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0339", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0340", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0342", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 400", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0343", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0344", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 400", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0345", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 400", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0346", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0347", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0348", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0349", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0350", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0351", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0352", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0353", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0354", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0355", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0356", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0357", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0358", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0359", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0360", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0361", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0362", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0363", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0364", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0365", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0366", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0367", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0368", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0369", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0370", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0371", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0372", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0373", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0374", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0375", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0376", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0377", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 120", + "(C) 180", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0378", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0379", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0380", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 180", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0381", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0382", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0383", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0384", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0385", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0386", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0387", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0388", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 400", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0389", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0390", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0391", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0392", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0393", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0394", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0395", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0396", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0397", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0398", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0399", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0400", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0401", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0402", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0403", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0404", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0405", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0406", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0407", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0408", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0409", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0410", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0411", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0412", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0413", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0414", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 400", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0415", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0416", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 300", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0417", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0418", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0419", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0420", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0421", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0422", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0423", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0424", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0425", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0426", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0427", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0428", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0429", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0430", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0431", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0432", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0433", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0434", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0435", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0436", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0437", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0438", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0439", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0440", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0441", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0442", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0443", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0444", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0445", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0446", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0447", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0448", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0449", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0450", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0451", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0452", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0453", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0454", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0455", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0456", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0457", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0458", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0459", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0460", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0461", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0462", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0463", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0464", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0465", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0466", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0467", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0468", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0469", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0470", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0471", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0472", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0473", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0474", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0475", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0476", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0477", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0478", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0479", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0480", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0481", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0482", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0483", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0484", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0485", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0486", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0487", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0488", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0489", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0490", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0491", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0492", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0493", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0494", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0495", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0496", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0497", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0498", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0499", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0500", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0501", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0502", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 400", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0503", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 325", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0504", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0505", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0506", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 400", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0507", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0508", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0509", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 400", + "(B) 350", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0510", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 400", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0511", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 400", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0512", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0513", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 325", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0514", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0515", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0516", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0517", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0518", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 350", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0519", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0520", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0521", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0522", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0523", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0524", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0525", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0526", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0527", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0528", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0529", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0530", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0531", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0532", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0533", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0534", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0535", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0536", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0537", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0538", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0539", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0540", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 270", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0541", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0542", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0543", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0544", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0545", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0546", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0547", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0548", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0549", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0550", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0551", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0552", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0553", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0554", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0555", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0556", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0557", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0558", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0559", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0560", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0561", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0562", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0563", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0564", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0565", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0566", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 180", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0567", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0568", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0569", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0570", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0571", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0572", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0573", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0574", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0575", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0576", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0577", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0578", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0579", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0580", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0581", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 240", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0582", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0583", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0584", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0585", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0586", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0587", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0588", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0589", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 150", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0590", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0591", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0592", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0593", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0594", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0595", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0596", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0597", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0598", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0599", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0600", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0601", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0602", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0603", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0604", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0605", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0606", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0607", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0608", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0609", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0610", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0611", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0612", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0613", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0614", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 60", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0615", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0616", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0617", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0618", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0619", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0620", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0621", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 60", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0622", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0623", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0624", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0625", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0626", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0627", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0628", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0629", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0630", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 140", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0631", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0632", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0633", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0634", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0635", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0636", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0637", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0638", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0639", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0640", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0641", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0642", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0643", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0644", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0645", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0646", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0647", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0648", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0649", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0650", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0651", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0652", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0653", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0654", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0655", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0656", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0657", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0658", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0659", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0660", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0661", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0662", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0663", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0664", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0665", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0666", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 180", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0667", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0668", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0669", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0670", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0671", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 180", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0672", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0673", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0674", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0675", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0676", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 200", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0677", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0678", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0679", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0680", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 240", + "(C) 270", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0681", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0682", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0683", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0684", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0685", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 0", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0686", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0687", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0688", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0689", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0690", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0691", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0692", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0693", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0694", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0695", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 210", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0696", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0697", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0698", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0699", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0700", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0701", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0702", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0703", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 270", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0704", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0705", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0706", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0707", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 325", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0708", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0709", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0710", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0711", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0712", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0713", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0714", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0715", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0716", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0717", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0718", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0719", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0720", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0721", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 240", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0722", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 300", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0723", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 325", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0724", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0725", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0726", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0727", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0728", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0729", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0730", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 90", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0731", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0732", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0733", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 40", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0734", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0735", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0736", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0737", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0738", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0739", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0740", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0741", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0742", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0743", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0744", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0745", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0746", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0747", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0748", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0749", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0750", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0751", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 210", + "(C) 180", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0752", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 180", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0753", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0754", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 180", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0755", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0756", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 240", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0757", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 210", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0758", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0759", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 270", + "(C) 240", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0760", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 200", + "(C) 240", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0761", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 200", + "(C) 210", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0762", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 150", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0763", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 150", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0764", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0765", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0766", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 140", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0767", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 90", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0768", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 90", + "(C) 60", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0769", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 60", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0770", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0771", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 0", + "(C) 40", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0772", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0773", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0774", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0775", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 60", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0776", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 120", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0777", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0778", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0779", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 140", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0780", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0781", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 140", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0782", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 140", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0783", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0784", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0785", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 210", + "(B) 150", + "(C) 200", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0786", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 180", + "(D) 150", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0787", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 200", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0788", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0789", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0790", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0791", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0792", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0793", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0794", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 140", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0795", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 140", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0796", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 140", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0797", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 140", + "(B) 120", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0798", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0799", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 140", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0800", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 140", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0801", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0802", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 60", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0803", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0804", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 60", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0805", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0806", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0807", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0808", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 60", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0809", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 40", + "(C) 0", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0810", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 90", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0811", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0812", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 60", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0813", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0814", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 300", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0815", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 240", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0816", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0817", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 300", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0818", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 300", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0819", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 240", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0820", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 300", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0821", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 240", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0822", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 240", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0823", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 240", + "(B) 270", + "(C) 325", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0824", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0825", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0826", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 325", + "(C) 350", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0827", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 350", + "(C) 300", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0828", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 270", + "(B) 325", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0829", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0830", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0831", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0832", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 270", + "(C) 350", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0833", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0834", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0835", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 350", + "(C) 270", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0836", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0837", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 350", + "(C) 270", + "(D) 325", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0838", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0839", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 300", + "(D) 350", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0840", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 325", + "(B) 270", + "(C) 350", + "(D) 300", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0841", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 300", + "(B) 240", + "(C) 325", + "(D) 270", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0842", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 200", + "(B) 210", + "(C) 270", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0843", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 210", + "(C) 200", + "(D) 240", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0844", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 200", + "(C) 180", + "(D) 210", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0845", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 180", + "(C) 140", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0846", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 40", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0847", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 60", + "(C) 90", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Gale Axis Estimation/0848", + "Text": "The provided image represents a typhoon. What is its radius of minor gale axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 0", + "(C) 90", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Gale Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Storm_Axis_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Storm_Axis_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..41d6e506157f818869a548edf4f28ce56d44eff6 --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Radius_of_Minor_Storm_Axis_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Radius of Minor Storm Axis Estimation/0001", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0002", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0003", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0004", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0005", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0006", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0007", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0008", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0009", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0010", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0011", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0012", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0013", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0014", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0015", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0016", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0017", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0018", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0019", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0020", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0021", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0022", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0023", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0024", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0025", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0026", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0027", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0028", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0029", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0030", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0031", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0032", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0033", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0034", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0035", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0036", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0037", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0038", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0039", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0040", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0041", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0042", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0043", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0044", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0045", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0046", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0047", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0048", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0049", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0050", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0051", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0052", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0053", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0054", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0055", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0056", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0057", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0058", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0059", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0060", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0061", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0062", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0063", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0064", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0065", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0066", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0067", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0068", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0069", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0070", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0071", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0072", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0073", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0074", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0075", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0076", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0077", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0078", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0079", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0080", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0081", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0082", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0083", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0084", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0085", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0086", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0087", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0088", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0089", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0090", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0091", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0092", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0093", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0094", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0095", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0096", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0097", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0098", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0099", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0100", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0101", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0102", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0103", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0104", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0105", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0106", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0107", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0108", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0109", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0110", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0111", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0112", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0113", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0114", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0115", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0116", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0117", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0118", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0119", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0120", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0121", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0122", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0123", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0124", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0125", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0126", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0127", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0128", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0129", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0130", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0131", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 65", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0132", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0133", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0134", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0135", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0136", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0137", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0138", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0139", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0140", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0141", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0142", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0143", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0144", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0145", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0146", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0147", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0148", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0149", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0150", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0151", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0152", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0153", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0154", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0155", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0156", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0157", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0158", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0159", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0160", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0161", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0162", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0163", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0164", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0165", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0166", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0167", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0168", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0169", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0170", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0171", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0172", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0173", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0174", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0175", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0176", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0177", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0178", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0179", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0180", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0181", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0182", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0183", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0184", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0185", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0186", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 150", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0187", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0188", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 150", + "(B) 110", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0189", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 180", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0190", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0191", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 150", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0192", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 150", + "(C) 180", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0193", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 180", + "(C) 150", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0194", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 150", + "(C) 120", + "(D) 180", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0195", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 180", + "(B) 120", + "(C) 150", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0196", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 150", + "(C) 180", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0197", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0198", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0199", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0200", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0201", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0202", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0203", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0204", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0205", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0206", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0207", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0208", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0209", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0210", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0211", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0212", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0213", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0214", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0215", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0216", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0217", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0218", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0219", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0220", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0221", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0222", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0223", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 30", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0224", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0225", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0226", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0227", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0228", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0229", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0230", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0231", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0232", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0233", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0234", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0235", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0236", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0237", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0238", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0239", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0240", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0241", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0242", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0243", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0244", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0245", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0246", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0247", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0248", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0249", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0250", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0251", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0252", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0253", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0254", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0255", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0256", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0257", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0258", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0259", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0260", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0261", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0262", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0263", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0264", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0265", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0266", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0267", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0268", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0269", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0270", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0271", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0272", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0273", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0274", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0275", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0276", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0277", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0278", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0279", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0280", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0281", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0282", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0283", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0284", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0285", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0286", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0287", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0288", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0289", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0290", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0291", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0292", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0293", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0294", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0295", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0296", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0297", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0298", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0299", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0300", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0301", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0302", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0303", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0304", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0305", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0306", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0307", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0308", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0309", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0310", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 30", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0311", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 30", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0312", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 30", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0313", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0314", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0315", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0316", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0317", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0318", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0319", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0320", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0321", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0322", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0323", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0324", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0325", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0326", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0327", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0328", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0329", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0330", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0331", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0332", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0333", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0334", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0335", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0336", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 65", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0337", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0338", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0339", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0340", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0342", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0343", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0344", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0345", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0346", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0347", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0348", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0349", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0350", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0351", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0352", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0353", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0354", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0355", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0356", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0357", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0358", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0359", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0360", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0361", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0362", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0363", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0364", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0365", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0366", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0367", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0368", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0369", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0370", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0371", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0372", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0373", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0374", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0375", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0376", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0377", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0378", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0379", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0380", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0381", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0382", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0383", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0384", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0385", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0386", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0387", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0388", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0389", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0390", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0391", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0392", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0393", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0394", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0395", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0396", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0397", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0398", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0399", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 80", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0400", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0401", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0402", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0403", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0404", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0405", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0406", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0407", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0408", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0409", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0410", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0411", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0412", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0413", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0414", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0415", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0416", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0417", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0418", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0419", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0420", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0421", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0422", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0423", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0424", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0425", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0426", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0427", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0428", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0429", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0430", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0431", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0432", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0433", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0434", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0435", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0436", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0437", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0438", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0439", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0440", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 30", + "(C) 40", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0441", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0442", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0443", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0444", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0445", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0446", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0447", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0448", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0449", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0450", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0451", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0452", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0453", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0454", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0455", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0456", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0457", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0458", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0459", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0460", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0461", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0462", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0463", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0464", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0465", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 60", + "(C) 55", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0466", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0467", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0468", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0469", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0470", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0471", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0472", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0473", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0474", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 80", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0475", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0476", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0477", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0478", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0479", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0480", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0481", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0482", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0483", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0484", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0485", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0486", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0487", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0488", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0489", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0490", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0491", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0492", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0493", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0494", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0495", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0496", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0497", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0498", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0499", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0500", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0501", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0502", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0503", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0504", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0505", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0506", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0507", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0508", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0509", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0510", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0511", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0512", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0513", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0514", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0515", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0516", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0517", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0518", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0519", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0520", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0521", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0522", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0523", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0524", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0525", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0526", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0527", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0528", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0529", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0530", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0531", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0532", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0533", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0534", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0535", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 110", + "(C) 100", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0536", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0537", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0538", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0539", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 100", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0540", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0541", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0542", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 100", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0543", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0544", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0545", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0546", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0547", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0548", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0549", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0550", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0551", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0552", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0553", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 100", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0554", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0555", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0556", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0557", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0558", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0559", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0560", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0561", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0562", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0563", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0564", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0565", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0566", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0567", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0568", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0569", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0570", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0571", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0572", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0573", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0574", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0575", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0576", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0577", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0578", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0579", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0580", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0581", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0582", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0583", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0584", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0585", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0586", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0587", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0588", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0589", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0590", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0591", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0592", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0593", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0594", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0595", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0596", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0597", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0598", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0599", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0600", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0601", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0602", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0603", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0604", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0605", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0606", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0607", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0608", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0609", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0610", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0611", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0612", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0613", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0614", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0615", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0616", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0617", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0618", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0619", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0620", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0621", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0622", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0623", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0624", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0625", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0626", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0627", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 30", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0628", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0629", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0630", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0631", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0632", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0633", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0634", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0635", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0636", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0637", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0638", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0639", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0640", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0641", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0642", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0643", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0644", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0645", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0646", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0647", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0648", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0649", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0650", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0651", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0652", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0653", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0654", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0655", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0656", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0657", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0658", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0659", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0660", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0661", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0662", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 35", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0663", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0664", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 35", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0665", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 35", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0666", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0667", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 35", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0668", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0669", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0670", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0671", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 60", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0672", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0673", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0674", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0675", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0676", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0677", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0678", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 110", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0679", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 90", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0680", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0681", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 90", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0682", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0683", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0684", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0685", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0686", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0687", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0688", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0689", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0690", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0691", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0692", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0693", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0694", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0695", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0696", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0697", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0698", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0699", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0700", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0701", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 35", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0702", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0703", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 30", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0704", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0705", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0706", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0707", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0708", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0709", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0710", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0711", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0712", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0713", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0714", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0715", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0716", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0717", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0718", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0719", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0720", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0721", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0722", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0723", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0724", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0725", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0726", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0727", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0728", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0729", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0730", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0731", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0732", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0733", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0734", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0735", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0736", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0737", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0738", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0739", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0740", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0741", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0742", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0743", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0744", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0745", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0746", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0747", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0748", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0749", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0750", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0751", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0752", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 60", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0753", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0754", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0755", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0756", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0757", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0758", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0759", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0760", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0761", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0762", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0763", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0764", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0765", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0766", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0767", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0768", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0769", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0770", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0771", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0772", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0773", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0774", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0775", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0776", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0777", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0778", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0779", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0780", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0781", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0782", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0783", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0784", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0785", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0786", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0787", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0788", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0789", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 0", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0790", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 35", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0791", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0792", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 35", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0793", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0794", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0795", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0796", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0797", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0798", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0799", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0800", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0801", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 35", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0802", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0803", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0804", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0805", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 25", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0806", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 30", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0807", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 20", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0808", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0809", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 20", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0810", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0811", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0812", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0813", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0814", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0815", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0816", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 20", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0817", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 25", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0818", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0819", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 20", + "(C) 30", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0820", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0821", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 25", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0822", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0823", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 0", + "(B) 30", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0824", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 25", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0825", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 0", + "(C) 30", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0826", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0827", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0828", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0829", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0830", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0831", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0832", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 110", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0833", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0834", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 120", + "(B) 100", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0835", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0836", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0837", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 90", + "(C) 120", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0838", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 100", + "(B) 120", + "(C) 110", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0839", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 90", + "(B) 120", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0840", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 120", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0841", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 75", + "(B) 100", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0842", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0843", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 0", + "(C) 20", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0844", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0845", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 0", + "(C) 25", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0846", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 30", + "(B) 25", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0847", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 0", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Radius of Minor Storm Axis Estimation/0848", + "Text": "The provided image represents a typhoon. What is its radius of minor storm axis (nm)?", + "Answer Choices": [ + "(A) 25", + "(B) 30", + "(C) 0", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Radius of Minor Storm Axis Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/Typhoon/Reasoning/Wind_Estimation.json b/jsons/Atmosphere/Typhoon/Reasoning/Wind_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..68fecfe044227dac8f6d9e556b96067d4c7ce6a8 --- /dev/null +++ b/jsons/Atmosphere/Typhoon/Reasoning/Wind_Estimation.json @@ -0,0 +1,17789 @@ +[ + { + "Question_id": "Wind Estimation/0001", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0002", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0003", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0004", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0005", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0006", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0007", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0008", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0009", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0010", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0011", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 60", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0012", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 55", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0013", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0014", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0015", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0016", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0017", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0018", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0019", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0020", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 115", + "(C) 110", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0021", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 115", + "(B) 105", + "(C) 110", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0022", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 115", + "(B) 105", + "(C) 120", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0023", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 120", + "(C) 115", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0024", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 105", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0025", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 105", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0026", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 110", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0027", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 105", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0028", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0029", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021041918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0030", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0031", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0032", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0033", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0034", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 80", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0035", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0036", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0037", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0038", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0039", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0040", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0041", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0042", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0043", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 65", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0044", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0045", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0046", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0047", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0048", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0049", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0050", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0051", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0052", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0053", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0054", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0055", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0056", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0057", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0058", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0059", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0060", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0061", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0062", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0063", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0064", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0065", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0066", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0067", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0068", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0069", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021042918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0070", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0071", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0072", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0073", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202102/jpg/region/2021043018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0074", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0075", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0076", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0077", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0078", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0079", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0080", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0081", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0082", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0083", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0084", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0085", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0086", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0087", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0088", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0089", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0090", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0091", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0092", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072003/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0093", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0094", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072009/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0095", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 55", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0096", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0097", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0098", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0099", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0100", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0101", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0102", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0103", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0104", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0105", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0106", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0107", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0108", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0109", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0110", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0111", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0112", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0113", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0114", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0115", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0116", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0117", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0118", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0119", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0120", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0121", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0122", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0123", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0124", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0125", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0126", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0127", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0128", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0129", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 55", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0130", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 55", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0131", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 60", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0132", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 60", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0133", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0134", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0135", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0136", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0137", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0138", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0139", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0140", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0141", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0142", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0143", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0144", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0145", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0146", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0147", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0148", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0149", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0150", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0151", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0152", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0153", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0154", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202106/jpg/region/2021073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0155", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0156", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0157", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0158", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0159", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0160", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0161", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0162", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0163", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0164", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 65", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0165", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0166", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0167", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0168", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0169", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0170", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 110", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0171", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0172", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0173", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0174", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0175", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0176", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0177", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0178", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0179", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0180", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0181", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0182", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 95", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0183", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0184", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021092918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0185", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 95", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0186", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0187", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0188", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0189", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0190", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021093021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0191", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0192", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0193", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0194", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0195", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0196", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0197", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0198", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0199", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0200", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0201", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0202", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0203", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0204", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0205", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0206", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0207", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0208", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0209", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0210", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0211", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202116/jpg/region/2021100512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0212", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0213", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0214", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0215", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0216", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0217", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0218", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0219", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0220", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0221", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0222", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0223", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 55", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0224", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0225", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0226", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0227", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0228", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0229", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 105", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0230", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 105", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0231", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 100", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0232", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0233", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0234", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0235", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0236", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0237", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0238", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0239", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 105", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0240", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0241", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0242", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 90", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0243", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0244", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021121918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0245", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0246", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0247", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0248", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0249", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0250", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2021/202122/jpg/region/2021122106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0251", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0252", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0253", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0254", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0255", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0256", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0257", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0258", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0259", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0260", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0261", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0262", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0263", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0264", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0265", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022040918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0266", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0267", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0268", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0269", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0270", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0271", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0272", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0273", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0274", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0275", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0276", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0277", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0278", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0279", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0280", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0281", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0282", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0283", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0284", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0285", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0286", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0287", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0288", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0289", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0290", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0291", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0292", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0293", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0294", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0295", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0296", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0297", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0298", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0299", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0300", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0301", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0302", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202201/jpg/region/2022041800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0303", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0304", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0305", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0306", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0307", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0308", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0309", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0310", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0311", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 70", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0312", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0313", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0314", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0315", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 85", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0316", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0317", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0318", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083015/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0319", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 105", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0320", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 95", + "(C) 110", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0321", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 105", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0322", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 105", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0323", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0324", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0325", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0326", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0327", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 90", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0328", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0329", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 90", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0330", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0331", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0332", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0333", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0334", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0335", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0336", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0337", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0338", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0339", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0340", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0342", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0343", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0344", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0345", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0346", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 95", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0347", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 95", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0348", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0349", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0350", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0351", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0352", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0353", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0354", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0355", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0356", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0357", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0358", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0359", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0360", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0361", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0362", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0363", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0364", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0365", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0366", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0367", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0368", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0369", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0370", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0371", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202211/jpg/region/2022090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0372", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0373", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0374", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0375", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0376", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0377", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0378", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0379", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0380", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0381", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0382", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0383", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0384", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0385", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 80", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0386", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0387", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0388", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0389", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0390", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0391", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 105", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0392", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 110", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0393", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 110", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0394", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0395", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 100", + "(C) 105", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0396", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 95", + "(C) 105", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0397", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0398", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0399", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 85", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0400", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 95", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0401", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 80", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0402", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 80", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091804/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0403", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0404", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091808/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0405", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0406", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091810/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0407", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0408", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0409", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 75", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0410", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 55", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0411", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0412", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 65", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0413", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0414", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0415", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 55", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0416", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0417", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022091918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0418", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202214/jpg/region/2022092000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0419", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0420", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0421", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0422", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0423", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0424", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0425", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0426", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0427", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0428", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0429", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0430", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0431", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0432", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0433", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0434", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0435", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0436", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0437", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0438", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0439", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0440", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0441", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0442", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0443", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0444", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0445", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 65", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0446", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0447", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0448", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0449", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0450", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0451", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2022/202216/jpg/region/2022092906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0452", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0453", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0454", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0455", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0456", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0457", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0458", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0459", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0460", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0461", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0462", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0463", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0464", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0465", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 65", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0466", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0467", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0468", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0469", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0470", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 105", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0471", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 105", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0472", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 105", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0473", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 90", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0474", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0475", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0476", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0477", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0478", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0479", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0480", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0481", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0482", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0483", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0484", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0485", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0486", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0487", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0488", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0489", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0490", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0491", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0492", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0493", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202305/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0494", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0495", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0496", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0497", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0498", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0499", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0500", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0501", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0502", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0503", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0504", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0505", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0506", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023072918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0507", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0508", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0509", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0510", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0511", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 70", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0512", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0513", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0514", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0515", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0516", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0517", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0518", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 80", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0519", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023073121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0520", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0521", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0522", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 85", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0523", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 85", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080109/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0524", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0525", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080115/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0526", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0527", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 95", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080121/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0528", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0529", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080203/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0530", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 95", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0531", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080209/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0532", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 95", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0533", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080215/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0534", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0535", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080221/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0536", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 80", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0537", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080303/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0538", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 70", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0539", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080309/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0540", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0541", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 75", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0542", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 60", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0543", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0544", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0545", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0546", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0547", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0548", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0549", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0550", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0551", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080421/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0552", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0553", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 60", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080503/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0554", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0555", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080509/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0556", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0557", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080515/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0558", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0559", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080521/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0560", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0561", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080603/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0562", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0563", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080609/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0564", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0565", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080615/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0566", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0567", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080621/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0568", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0569", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080703/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0570", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0571", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080709/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0572", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0573", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080715/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0574", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0575", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080721/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0576", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0577", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080803/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0578", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0579", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080809/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0580", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0581", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080815/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0582", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0583", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080821/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0584", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0585", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080903/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0586", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0587", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080909/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0588", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0589", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080915/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0590", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0591", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023080921/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0592", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0593", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0594", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0595", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0596", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0597", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0598", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0599", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202306/jpg/region/2023081118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0600", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0601", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0602", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0603", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0604", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0605", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0606", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0607", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0608", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0609", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0610", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0611", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0612", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0613", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0614", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 70", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0615", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0616", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0617", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0618", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 85", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0619", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0620", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0621", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0622", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 100", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0623", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0624", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0625", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0626", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0627", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0628", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 75", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0629", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 80", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0630", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 85", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0631", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023082918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0632", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 105", + "(C) 100", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0633", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0634", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 110", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0635", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 105", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0636", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0637", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 95", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0638", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 105", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0639", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 95", + "(C) 90", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0640", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0641", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0642", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0643", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 60", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0644", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0645", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0646", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0647", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0648", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0649", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0650", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202309/jpg/region/2023090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0651", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0652", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0653", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0654", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0655", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0656", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0657", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0658", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0659", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0660", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0661", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0662", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0663", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0664", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0665", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 65", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023100918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0666", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0667", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 75", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0668", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0669", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0670", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0671", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 115", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0672", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 115", + "(B) 110", + "(C) 105", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0673", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 115", + "(B) 110", + "(C) 105", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0674", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 115", + "(B) 110", + "(C) 105", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0675", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 115", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0676", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 115", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0677", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 95", + "(C) 100", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0678", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 105", + "(C) 100", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0679", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 85", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0680", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0681", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 90", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0682", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 85", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0683", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0684", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0685", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0686", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0687", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0688", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0689", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2023/202315/jpg/region/2023101518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0690", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0691", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0692", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0693", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024071918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0694", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0695", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0696", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0697", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0698", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0699", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0700", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0701", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0702", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0703", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0704", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0705", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0706", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 75", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0707", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0708", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0709", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072315/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0710", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 90", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0711", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 75", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072321/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0712", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0713", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 90", + "(C) 80", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0714", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 80", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0715", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 75", + "(B) 65", + "(C) 70", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0716", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 70", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0717", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0718", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 65", + "(C) 60", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0719", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0720", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 45", + "(C) 50", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0721", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 55", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0722", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0723", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0724", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0725", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0726", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0727", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0728", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0729", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0730", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0731", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0732", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0733", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0734", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202403/jpg/region/2024072818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0735", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0736", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 0", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024083118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0737", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0738", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0739", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0740", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0741", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0742", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0743", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0744", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0745", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0746", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0747", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0748", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 55", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0749", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 70", + "(C) 75", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0750", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0751", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 85", + "(C) 90", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0752", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 95", + "(B) 100", + "(C) 105", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0753", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 100", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0754", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 105", + "(B) 110", + "(C) 95", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0755", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 95", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0756", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 105", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0757", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 105", + "(C) 110", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0758", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 110", + "(B) 105", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0759", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 100", + "(B) 95", + "(C) 85", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0760", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 80", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0761", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 75", + "(C) 80", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0762", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0763", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0764", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0765", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0766", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0767", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 0", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0768", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0769", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0770", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0771", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202411/jpg/region/2024090912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0772", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024090918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0773", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0774", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 0", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0775", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0776", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0777", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0778", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0779", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0780", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0781", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091200/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0782", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091206/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0783", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091212/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0784", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091218/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0785", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091300/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0786", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091306/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0787", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091312/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0788", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091318/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0789", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0790", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 50", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091403/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0791", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 50", + "(C) 55", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0792", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091409/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0793", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 60", + "(C) 50", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0794", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 60", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091415/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0795", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 65", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0796", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0797", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 80", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0798", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 75", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0799", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 65", + "(C) 70", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0800", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 55", + "(C) 70", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0801", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 55", + "(C) 65", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0802", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 45", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0803", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0804", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0805", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0806", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0807", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 0", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0808", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0809", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 40", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202413/jpg/region/2024091806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0810", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102400/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0811", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 0", + "(B) 45", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102406/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0812", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 0", + "(C) 45", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102412/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0813", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 45", + "(C) 40", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102418/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0814", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102500/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0815", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102506/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0816", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102512/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0817", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102518/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0818", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 45", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102600/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0819", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 35", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102606/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0820", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 40", + "(C) 35", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102612/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0821", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 35", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102618/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0822", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 40", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102700/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0823", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102706/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0824", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 45", + "(C) 40", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102712/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0825", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 40", + "(C) 50", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102718/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0826", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 50", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102800/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0827", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 60", + "(B) 55", + "(C) 50", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102806/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0828", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 50", + "(B) 65", + "(C) 60", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102812/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0829", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 65", + "(B) 70", + "(C) 55", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102818/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0830", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 65", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102900/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0831", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 70", + "(C) 85", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102906/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0832", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 75", + "(C) 90", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102912/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0833", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 95", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024102918/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0834", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 100", + "(C) 95", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103000/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0835", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 90", + "(C) 100", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103006/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0836", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 85", + "(B) 80", + "(C) 95", + "(D) 90", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103012/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0837", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 95", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103018/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0838", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 85", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103021/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0839", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 80", + "(B) 90", + "(C) 75", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0840", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 80", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103103/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0841", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 70", + "(B) 80", + "(C) 65", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0842", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 55", + "(B) 60", + "(C) 45", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0843", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 35", + "(B) 50", + "(C) 40", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024103118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0844", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 35", + "(C) 50", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110100/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0845", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 45", + "(C) 50", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110106/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0846", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 0", + "(D) 35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110112/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0847", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 40", + "(B) 35", + "(C) 45", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110118/1.jpg" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Wind Estimation/0848", + "Text": "The provided image represents a typhoon. What is its wind (kt)?", + "Answer Choices": [ + "(A) 45", + "(B) 40", + "(C) 35", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "Typhoon", + "L3-task": "Reasoning", + "L4-task": "Wind Estimation", + "Dataset": "DigitalTyphoon", + "Images": [ + "raw/Atmosphere/DigitalTyphoon/2024/202421/jpg/region/2024110200/1.jpg" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/long_term/Perception/ENSO_feature_analysis.json b/jsons/Atmosphere/long_term/Perception/ENSO_feature_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..f7988f97a371f9d30d7d73bd9c26bffd93363dba --- /dev/null +++ b/jsons/Atmosphere/long_term/Perception/ENSO_feature_analysis.json @@ -0,0 +1,3872 @@ +[ + { + "Question_id": "long_term-ENSO_feature-000", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. What ENSO transition occurred during 2010?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Transition from La Niña to El Niño", + "B. Transition from El Niño to La Niña", + "C. No ENSO transition occurred", + "D. Continued La Niña throughout the year", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-001", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which ENSO phase was active at the beginning of 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. La Niña", + "B. ENSO-neutral", + "C. Weak El Niño", + "D. Moderate-to-strong El Niño", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-002", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. By what month in 2010 did El Niño conditions officially end, returning to ENSO-neutral?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. April", + "C. May", + "D. July", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-003", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which ENSO phase influenced the heavy rainfall and flooding in Australia during late 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. La Niña", + "D. Indian Ocean Dipole", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-004", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. How did La Niña conditions affect global ocean temperatures during September–November 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. They were the warmest on record", + "B. They were close to average", + "C. They were the tenth warmest on record", + "D. They were the coolest on record", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-005", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which of the following precipitation patterns in 2010 is most directly associated with La Niña conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Drought in northeastern Brazil", + "B. Heavy flooding in Pakistan", + "C. Wettest spring on record in Australia", + "D. Driest winter in Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-006", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. What ENSO phase was predominantly present during most of 2011?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. None of the above", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-007", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. Which of the following regions experienced severe drought conditions attributed to La Niña in 2011?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western Europe", + "B. Horn of Africa", + "C. Southeast Asia", + "D. Eastern Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-008", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. Which ENSO condition contributed to Australia experiencing its third wettest year on record in 2011?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. Arctic Oscillation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-009", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. How did global temperatures in 2011 compare to previous La Niña years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was cooler than all previous La Niña years", + "B. It was average for a La Niña year", + "C. It was the warmest La Niña year on record", + "D. It was among the coldest years since 1950", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-010", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. Which ENSO state is typically associated with cooler-than-normal waters in the eastern and central equatorial Pacific Ocean?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. La Niña", + "D. Positive Arctic Oscillation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-011", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. What was the ENSO condition during the middle of 2011, between two La Niña phases?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. Arctic Oscillation", + "D. Negative AO", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-012", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. What ENSO phase was present during the first quarter (January–March) of 2012?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. Positive Indian Ocean Dipole", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-013", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. How did the ENSO state evolve throughout 2012 after the first quarter?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It remained in La Niña", + "B. It transitioned to El Niño", + "C. It remained in El Niño", + "D. It transitioned to ENSO-neutral", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-014", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. Which of the following statements about La Niña years is true based on 2012 data?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2012 was the coldest La Niña year on record", + "B. 2012 was the warmest La Niña year on record", + "C. 2012 was the third warmest La Niña year on record", + "D. 2012 was a typical La Niña year with below-average temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-015", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. How did La Niña conditions affect precipitation in Australia during early 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Drier-than-average conditions across the continent", + "B. Heavy rainfall, especially in the east", + "C. Record low precipitation across northern Australia", + "D. No significant impact on precipitation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-016", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. What ENSO condition contributed to above-average global ocean temperatures in 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. A strengthening La Niña", + "B. A strong El Niño event", + "C. Transition to ENSO-neutral conditions after La Niña", + "D. A prolonged El Niño Modoki phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-017", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which ENSO state was present throughout 2013, as described in the NOAA climate report?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. Transitioning from La Niña to El Niño", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-018", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. What effect did the ENSO-neutral conditions have on global ocean temperatures in 2013?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caused record high ocean temperatures", + "B. Resulted in below-average SSTs", + "C. Contributed to the 8th warmest ocean temperatures on record", + "D. Had no impact on ocean temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-019", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Given the ENSO-neutral conditions in 2013, which of the following is a typical feature for such a year based on the report?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong warming in the eastern tropical Pacific", + "B. Record cold anomalies in the central Pacific", + "C. Lack of strong ocean temperature anomalies in the equatorial Pacific", + "D. Elevated precipitation in the eastern Pacific", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-020", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which of the following best describes the relationship between ENSO-neutral conditions and precipitation patterns in 2013?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. ENSO-neutral years often bring increased rainfall globally", + "B. ENSO-neutral conditions can still coincide with extreme regional droughts and floods", + "C. ENSO-neutral suppresses all precipitation extremes", + "D. ENSO-neutral results in uniform global precipitation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-021", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. How did the ENSO-neutral conditions in 2013 compare to typical El Niño years in terms of global ocean surface temperature anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Much warmer than typical El Niño years", + "B. Slightly cooler than record El Niño years", + "C. Identical to La Niña years", + "D. Significantly cooler than any ENSO phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-022", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. What was the state of ENSO conditions during 2014 according to NOAA's CPC Oceanic Niño Index?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong El Niño", + "B. Weak El Niño", + "C. ENSO-neutral", + "D. Strong La Niña", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-023", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Despite the absence of El Niño conditions, what significant climate milestone occurred in 2014?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. The driest year ever recorded", + "B. The coldest global temperature since 1970", + "C. The warmest year globally on record", + "D. The highest global snowfall on record", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-024", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which of the following statements best describes the typical influence of El Niño on global temperatures?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It typically leads to a global cooling trend", + "B. It has no significant impact on global temperatures", + "C. It typically increases global temperatures", + "D. It causes more snowfall in tropical regions", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-025", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. How was the warmth of global oceans in 2014 unique compared to previous years with strong El Niño events?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Global oceans were cooler than average", + "B. Warmth was confined to the Southern Hemisphere only", + "C. Record ocean warmth occurred despite the lack of El Niño", + "D. Ocean temperatures did not change significantly", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-026", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which of the following ocean regions showed record warmth in 2014, typically also associated with El Niño events?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western equatorial Pacific", + "B. Southern Ocean near Antarctica", + "C. Central Arctic Ocean", + "D. North Sea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-027", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. What was the ENSO phase during 2015 that strongly influenced global temperatures and precipitation patterns?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. La Niña", + "B. Neutral", + "C. El Niño", + "D. Arctic Oscillation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-028", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which region experienced unusually high sea surface temperatures in 2015 due to the strong El Niño?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Eastern and central equatorial Pacific", + "B. North Atlantic near Greenland", + "C. Southern Ocean near Antarctica", + "D. Western Mediterranean Sea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-029", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which of the following precipitation patterns is typically associated with El Niño and was observed in 2015?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Above-average precipitation in the Amazon", + "B. Below-average rainfall in the Caribbean and Central America", + "C. Increased snowfall in the Sierra Nevada", + "D. Excessive monsoon rainfall in India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-030", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. How did the strong El Niño event in 2015 affect the Indian monsoon season?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It caused record-high rainfall across India", + "B. It delayed the monsoon onset indefinitely", + "C. It contributed to below-average rainfall during the season", + "D. It had no noticeable impact on the monsoon", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-031", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which of the following statements about the 2015 El Niño is correct based on climate data?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was weaker than the 1997–98 El Niño", + "B. It caused a cooling of global ocean temperatures", + "C. It contributed to record-breaking global land and ocean temperatures", + "D. It had no significant impact on global climate anomalies", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-032", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which region experienced drought conditions in 2015 that are characteristic of El Niño years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Eastern United States", + "B. Western Europe", + "C. South Africa", + "D. Southeast Brazil", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-033", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Which ENSO phase was dominant during the early part of 2016, contributing significantly to record global warmth?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong El Niño", + "B. Strong La Niña", + "C. Neutral ENSO conditions", + "D. Weak La Niña", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-034", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. What ENSO transition occurred during 2016, as indicated by NOAA's annual climate report?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Weak La Niña to strong El Niño", + "B. Strong El Niño to weak La Niña", + "C. Neutral to strong La Niña", + "D. La Niña to neutral conditions", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-035", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. How did the strong El Niño early in 2016 influence global ocean temperatures?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It caused them to drop sharply", + "B. It led to record cold anomalies in all ocean basins", + "C. It contributed to record or near-record high ocean temperatures", + "D. It had no noticeable effect on ocean temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-036", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Despite the transition to weak La Niña conditions later in 2016, what was notable about ocean temperatures?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. They returned to 20th century average levels", + "B. They dropped below average by December", + "C. They remained well above average", + "D. They fluctuated unpredictably month to month", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-037", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Which region experienced record warmth in ocean temperatures due to the strong El Niño in early 2016?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Southern Atlantic Ocean", + "B. Northern Pacific near Alaska and the Bering Sea", + "C. Eastern Mediterranean Sea", + "D. Arctic Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-038", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. What ENSO phase was present during 2017 according to the NOAA report?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong El Niño", + "B. Moderate El Niño", + "C. No El Niño", + "D. La Niña", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-039", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which statement best characterizes the 2017 global temperature in relation to ENSO?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017 was cooler due to La Niña conditions", + "B. 2017 was the warmest year ever due to El Niño", + "C. 2017 was unusually warm despite no El Niño", + "D. 2017 had normal temperatures because no ENSO event occurred", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-040", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. How did the absence of El Niño in 2017 affect the global temperature anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It caused the anomaly to be below average", + "B. It prevented any significant warming", + "C. It still resulted in the third warmest year on record", + "D. It led to global cooling", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-041", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which of the following is true about the March 2017 global temperature anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was the highest ever due to El Niño", + "B. It was over 1.0°C above average without El Niño", + "C. It was below average due to La Niña", + "D. It was the coldest March on record", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-042", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Compared to 2015 and 2016, both influenced by strong El Niño, how did 2017 rank in terms of warmth?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was the warmest year", + "B. It was cooler than both 2015 and 2016", + "C. It was warmer than 2016 but cooler than 2015", + "D. It was the same as 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-043", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. What ENSO phase was present at the beginning of 2018?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. El Niño Modoki", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-044", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. When did the ENSO phase transition from La Niña to ENSO-neutral in 2018?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. July", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-045", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which of the following best describes the ENSO state during the majority of 2018?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong El Niño", + "B. Weak El Niño", + "C. ENSO-neutral", + "D. Strong La Niña", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-046", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which ENSO phase is typically associated with cooler global temperatures, and was present at the start of 2018?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. Indian Ocean Dipole", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-047", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Given that 2018 began with La Niña conditions, what would you expect in the global precipitation anomaly dot plot for early 2018?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Wetter-than-average conditions in the central Pacific", + "B. Drier-than-average conditions in the western Pacific", + "C. Wetter-than-average conditions in Southeast Asia and northern Australia", + "D. Wetter-than-average conditions in South America’s west coast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-048", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. If global temperature anomalies were slightly lower in 2018 compared to 2015–2017, which ENSO-related factor might have contributed?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Presence of El Niño in early 2018", + "B. Absence of ENSO activity in 2015", + "C. Transition from La Niña to ENSO-neutral during 2018", + "D. Strong El Niño during mid-2018", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-049", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. What ENSO phase was present during the first half of 2019?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong La Niña", + "B. Weak-to-moderate El Niño", + "C. ENSO-neutral throughout the year", + "D. Strong El Niño", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-050", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which ENSO condition was observed by July 2019?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong La Niña", + "B. Moderate El Niño", + "C. ENSO-neutral", + "D. Weak La Niña", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-051", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. How might the weak-to-moderate El Niño during early 2019 have contributed to global climate conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Suppressed global temperatures", + "B. Enhanced global warmth", + "C. Increased Arctic sea ice extent", + "D. Strengthened monsoon circulation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-052", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Given the ENSO transition in mid-2019, which of the following is most likely true about precipitation patterns in the second half of 2019?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Continued widespread drought globally", + "B. Return to precipitation patterns typical of ENSO-neutral conditions", + "C. Intensified La Niña-related rainfall in South America", + "D. Suppressed Indian monsoon rainfall", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-053", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which region's record dryness in 2019 is more likely attributed to a strong positive Indian Ocean Dipole than ENSO?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. South America", + "B. Europe", + "C. Australia", + "D. North America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-054", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which of the following best describes typical global temperature anomalies during a weak-to-moderate El Niño year, such as early 2019?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Cooler-than-average global temperatures", + "B. Near-average global temperatures", + "C. Warmer-than-average global temperatures", + "D. Highly variable temperatures with no consistent trend", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-055", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which ENSO phase was present during the latter part of 2020?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. El Niño Modoki", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-056", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. How did the transition to La Niña conditions in August 2020 likely influence global temperatures in the latter part of the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caused a sudden increase in global temperatures", + "B. Had no impact on global temperatures", + "C. Contributed to relatively lower temperature anomalies compared to earlier in the year", + "D. Caused record-breaking heat in December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-057", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. What ENSO condition was present at the beginning of 2020?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong La Niña", + "B. Weak El Niño", + "C. ENSO-neutral", + "D. Strong El Niño", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-058", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Despite the emergence of La Niña in 2020, how did the global annual temperature rank?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Hottest on record", + "B. Second warmest on record", + "C. Coldest since 1998", + "D. Near the 20th-century average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-059", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. What is a typical global temperature pattern associated with La Niña events?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Strong global warming", + "B. Cooling or suppression of temperature increases", + "C. Uniform warming across all regions", + "D. More warming in the Southern Hemisphere only", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-060", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which of the following precipitation anomalies in 2020 could be associated with La Niña conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Drought in northern Argentina and Paraguay", + "B. Flooding in the United Kingdom", + "C. Heavy rainfall in Spain", + "D. Dry February in New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-061", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which ENSO phase was present during the beginning of 2021?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. Neutral", + "C. La Niña", + "D. Indian Ocean Dipole", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-062", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Based on typical ENSO impacts, what general global temperature pattern would be expected during a La Niña year like 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Significantly warmer global temperatures", + "B. Slightly cooler global temperatures", + "C. No change in global temperatures", + "D. Extremely cold global temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-063", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Looking at the dot plot of global temperature anomalies for 2021, which region likely showed cooling effects consistent with La Niña impacts?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Central and eastern tropical Pacific Ocean", + "B. Northern Europe", + "C. Southern Africa", + "D. Western U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-064", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. How did La Niña conditions likely influence the precipitation pattern over northern South America in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caused extreme drought", + "B. Had no influence", + "C. Contributed to above-average precipitation", + "D. Led to reduced cyclone activity", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-065", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which of the following regions experienced significantly below-average precipitation in 2021, consistent with typical La Niña patterns?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western U.S.", + "B. Eastern Australia", + "C. Northern South America", + "D. Southeast Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-066", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. How did La Niña likely affect precipitation in parts of eastern Australia in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caused severe drought", + "B. Led to below-normal rainfall", + "C. Resulted in above-average rainfall", + "D. Had no notable impact", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-067", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. What ENSO phase was present throughout the year 2022, influencing global temperature and precipitation patterns?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. El Niño Modoki", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-068", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. How did the persistent ENSO phase in 2022 typically affect global temperatures?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It caused record-high global temperatures", + "B. It had no impact on global temperatures", + "C. It tended to keep global temperatures slightly cooler than El Niño years", + "D. It caused rapid cooling globally", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-069", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which region experienced cooler-than-average sea surface temperatures in 2022 consistent with the La Niña phase?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. North Atlantic Ocean", + "B. Indian Ocean", + "C. Central and eastern tropical Pacific Ocean", + "D. Southern Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-070", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Despite La Niña conditions in 2022, how did the global temperature rank historically?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was the warmest year on record", + "B. It was cooler than the 20th century average", + "C. It was the sixth warmest year on record", + "D. It was not in the top ten warmest years", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-071", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. How did La Niña conditions affect precipitation in eastern Australia during 2022?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caused drought throughout the year", + "B. Led to extreme rainfall and flooding", + "C. Resulted in average precipitation", + "D. Caused unusually dry winter", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-072", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which of the following is a typical climate impact of La Niña, as seen in 2022’s global precipitation patterns?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increased rainfall in southern Europe", + "B. Above-average precipitation in the central U.S. and eastern Australia", + "C. Drought in eastern Australia", + "D. Enhanced monsoon in Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-073", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. What ENSO phase did the Earth transition into by June 2023?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. La Niña", + "B. ENSO-neutral", + "C. El Niño", + "D. Negative IOD", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-074", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which ENSO phase is typically associated with cooler global temperatures?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. La Niña", + "D. Positive IOD", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-075", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. How did the shift to El Niño in 2023 affect global temperature records?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It caused a cooling trend globally", + "B. It led to record-low ocean temperatures", + "C. It contributed to record-high global temperatures", + "D. It had no noticeable impact on global temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-076", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which period in 2023 saw each month rank as the warmest on record due to El Niño influence?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. June–December", + "D. September–November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-077", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. What characterizes global temperature patterns during El Niño years compared to La Niña years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Cooler temperatures globally", + "B. Little to no change in temperatures", + "C. Warmer temperatures globally", + "D. Increased volcanic activity", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-078", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. What was the ENSO condition during the previous two years before 2023?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. La Niña", + "D. Positive PDO", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-079", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which oceanic condition in 2023 was consistent with the development of El Niño?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Persistent cooling of central Pacific", + "B. Record-warm ocean temperatures globally", + "C. Neutral sea surface temperature anomalies", + "D. Cooling of the Indian Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-080", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which ENSO phase was in effect at the beginning of 2024?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. La Niña", + "C. ENSO-neutral", + "D. None of the above", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-081", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. When did the transition from El Niño to ENSO-neutral conditions occur in 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. May", + "C. August", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-082", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which ENSO phase emerged at the end of 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. ENSO-neutral", + "C. La Niña", + "D. None of the above", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-083", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. How did global temperatures behave during the ENSO-neutral period in 2024 (May–November)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Returned to average", + "B. Reached record lows", + "C. Continued to break monthly records through August", + "D. Stayed consistently below average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-084", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which precipitation pattern in South America during 2024 is most consistent with a transition from El Niño to La Niña?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increased rainfall in northern Brazil", + "B. Record dryness across large parts of Brazil, Bolivia, and Peru", + "C. Wet conditions in southern Chile", + "D. Above-average snowfall across the Andes", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-ENSO_feature-085", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. How did global sea surface temperatures respond during the ENSO transitions of 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "ENSO feature analysis", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. They remained average throughout the year", + "B. They declined rapidly during La Niña", + "C. They set monthly records from April 2023 through June 2024", + "D. They fluctuated with no clear pattern", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/long_term/Perception/Long-term_precipitation_trend.json b/jsons/Atmosphere/long_term/Perception/Long-term_precipitation_trend.json new file mode 100644 index 0000000000000000000000000000000000000000..1e3612d7b636f36a2b75ed8580ce1fc773adbf4e --- /dev/null +++ b/jsons/Atmosphere/long_term/Perception/Long-term_precipitation_trend.json @@ -0,0 +1,1802 @@ +[ + { + "Question_id": "long_term-precipitation_trend-000", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year recorded the highest global precipitation anomaly since 1900?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2011", + "C. 2012", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-001", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which two consecutive years were among the wettest globally?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010 and 2011", + "B. 2012 and 2013", + "C. 2015 and 2016", + "D. 2018 and 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-002", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year showed a shift from near-record wetness to average global precipitation levels?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2013", + "D. 2014", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-003", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked Australia's driest conditions and contributed to major wildfires?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2018", + "C. 2019", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-004", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year experienced near-average global precipitation following several wetter years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-005", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. In which year did global precipitation trend slightly below the long-term average following previous wet years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-006", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw a recovery in wetness in Europe despite ongoing drought in other regions like South Africa?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2017", + "C. 2018", + "D. 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-007", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the lowest precipitation in Australia since records began?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2018", + "C. 2019", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-008", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked a consistent trend of extreme variability with precipitation both above and below average across major regions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2018", + "B. 2019", + "C. 2020", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-009", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked the wettest Indian monsoon since 1994?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2018", + "C. 2019", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-010", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year observed a decline in global precipitation compared to highs in the earlier part of the decade?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2012", + "B. 2015", + "C. 2014", + "D. 2013", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-011", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had consistent below-average precipitation anomalies across multiple continents including South America and Africa?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2021", + "B. 2022", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-012", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which two years saw multiple record-breaking rainfall events in different parts of the world such as Africa, Asia, and Oceania?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2022 and 2023", + "B. 2021 and 2022", + "C. 2020 and 2021", + "D. 2023 and 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-013", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw a reduction in global rainfall despite some record-breaking wet months in Europe and Asia?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2016", + "C. 2017", + "D. 2018", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-014", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had extreme wetness in eastern Australia and later average annual precipitation due to drying conditions later in the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2013", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-015", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year followed a severe drought in Australia and showed the most extreme transition to wet conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2019", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-016", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw consistently near-average global precipitation levels after a series of extremes?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2014", + "C. 2016", + "D. 2018", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-017", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked a notably wetter year in parts of Asia and Oceania while maintaining below-average precipitation overall?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2020", + "B. 2021", + "C. 2022", + "D. 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-018", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which two years were characterized by consistent drought patterns in Brazil, the western U.S., and Southern Africa?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016 and 2017", + "B. 2018 and 2019", + "C. 2020 and 2021", + "D. 2021 and 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-019", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years displayed the strongest signal of alternating wet and dry anomalies across continents?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2016", + "C. 2019", + "D. 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-020", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the highest global precipitation since records began?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2011", + "C. 2014", + "D. 2016", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-021", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was globally the second wettest on record following the wettest year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2015", + "D. 2016", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-022", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which two consecutive years had global precipitation near the 1961–1990 average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013 and 2014", + "B. 2012 and 2013", + "C. 2015 and 2016", + "D. 2020 and 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-023", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year recorded the driest global precipitation anomaly among 2010–2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2019", + "B. 2023", + "C. 2015", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-024", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked a return to extreme global wet anomalies after a three-year near-average period?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2017", + "C. 2019", + "D. 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-025", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the driest recorded condition across Australia?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2019", + "B. 2020", + "C. 2017", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-026", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which year did global precipitation anomalies begin trending downward after two consecutive wettest years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2012", + "B. 2013", + "C. 2014", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-027", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the most extreme wet and dry conditions co-occurring across continents, particularly influenced by El Niño?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-028", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had eight of its wettest rainfall months globally, leading to Australia logging its eighth-wettest year on record?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2017", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-029", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw a decreasing global precipitation anomaly following a statistically wet period caused by La Niña?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2011", + "C. 2012", + "D. 2014", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-030", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. After which year did the global precipitation anomaly stay consistently near or below average for several years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2012", + "C. 2014", + "D. 2011", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-031", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years had the most consistent precipitation pattern near the long-term average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2014", + "C. 2016", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-032", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year followed the wettest year with the most regional variability despite a near-average global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2013", + "C. 2012", + "D. 2014", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-033", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. In which year did global precipitation rise after three years around the long-term average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2017", + "C. 2018", + "D. 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-034", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the widest inter-annual deviation from previous years in terms of anomaly after a relatively consistent trend?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2018", + "C. 2019", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-035", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year is most likely to display a sharp increase in precipitation anomaly relative to the long-term declining trend observed earlier?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2021", + "B. 2023", + "C. 2022", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-036", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the highest recorded global land precipitation anomaly since 1900?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2011", + "C. 2014", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-037", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which consecutive years were ranked first and second for global precipitation anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010 and 2011", + "B. 2015 and 2016", + "C. 2013 and 2014", + "D. 2011 and 2012", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-038", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. In which year was there a noticeable shift in global precipitation anomalies from wet to near average levels?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2012", + "C. 2013", + "D. 2011", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-039", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What was the general trend in global precipitation anomalies from 2010 to 2016?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Decreasing trend", + "B. Increasing trend", + "C. Constantly increasing", + "D. No discernible trend", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-040", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked a return to near-average global precipitation after consecutive above-average years?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2012", + "C. 2014", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-041", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the greatest deficit in global precipitation relative to the 1961–1990 average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2014", + "D. 2013", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-042", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What trend is apparent in global precipitation anomalies from 2015 to 2017?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Fluctuating with overall deficit", + "B. Constantly increasing", + "C. Record-breaking rainfall each year", + "D. Dry conditions consistently decreasing", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-043", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was characterized by near-record extremes in both dry and wet conditions globally but was overall near-normal in anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2014", + "C. 2017", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-044", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years had below-average global precipitation anomalies due to widespread drought conditions in major regions like Brazil and Australia?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2023", + "B. 2019", + "C. 2015", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-045", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year stands out for having Australia's driest year on record based on global precipitation anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2019", + "C. 2020", + "D. 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-046", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw its global precipitation anomaly increase again after multiple years of generally below or near average values post-2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2022", + "B. 2023", + "C. 2024", + "D. 2016", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-047", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. How did global precipitation anomalies trend between 2020 and 2022?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Gradual increase", + "B. Gradual decline", + "C. High interannual variability", + "D. Constant above-average anomaly", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-048", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year recorded a notable rebound in global precipitation anomaly due to Australia’s eighth-wettest year on record and intense flooding elsewhere?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2021", + "B. 2022", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-precipitation_trend-049", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Based on the anomaly dot plot, which of the following years had the lowest overall global precipitation anomaly in the decade 2010–2020?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-annual-prcp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term precipitation trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2019", + "D. 2010", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/long_term/Perception/Long-term_temperature_trend.json b/jsons/Atmosphere/long_term/Perception/Long-term_temperature_trend.json new file mode 100644 index 0000000000000000000000000000000000000000..237245177c89bb902a0528a3f77739cee5713b98 --- /dev/null +++ b/jsons/Atmosphere/long_term/Perception/Long-term_temperature_trend.json @@ -0,0 +1,1838 @@ +[ + { + "Question_id": "long_term-temperature_trend-000", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked the first time a global record temperature was set without the influence of El Niño?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2013", + "D. 2016", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-001", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Between which two consecutive years did the largest year-to-year increase in global temperature on record occur?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013–2014", + "B. 2014–2015", + "C. 2015–2016", + "D. 2016–2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-002", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was the warmest ever recorded globally as of the end of 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2020", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-003", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What was the global temperature anomaly recorded in the year 2023?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. +0.98°C", + "B. +1.18°C", + "C. +0.86°C", + "D. +1.29°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-004", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which decade was the warmest on record according to the analysis?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 1991–2000", + "B. 2001–2010", + "C. 2011–2020", + "D. 2014–2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-005", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was the warmest La Niña year on record at the time it occurred?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010", + "B. 2011", + "C. 2012", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-006", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had global ocean surface temperatures breaking annual records for the first time since 2014?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-007", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years did NOT experience a new record in global average temperature?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2017", + "D. 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-008", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What is the approximate rate of global warming since 1981 according to the data summary?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 0.06°C/decade", + "B. 0.12°C/decade", + "C. 0.18°C/decade", + "D. 0.26°C/decade", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-009", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked the 45th consecutive year of above-average global temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2020", + "B. 2021", + "C. 2022", + "D. 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-010", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year experienced the warmest September anomaly on record of +1.44°C?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2017", + "C. 2023", + "D. 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-011", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year registered the third consecutive year of record-breaking global temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-012", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which year did the contiguous U.S. experience its warmest year on record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2012", + "B. 2015", + "C. 2020", + "D. 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-013", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Global temperature anomalies were above the 20th-century average for how many consecutive years by 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 36", + "B. 40", + "C. 46", + "D. 48", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-014", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was the warmest globally despite having neutral ENSO conditions for most of the year?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2012", + "B. 2013", + "C. 2014", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-015", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which year did all continents except Antarctica set or nearly set temperature records?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2020", + "B. 2022", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-016", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year became the second warmest year globally, just behind the record set in 2016, based on NOAA data?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2019", + "B. 2020", + "C. 2021", + "D. 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-017", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. How many of the ten warmest years globally occurred since 2015 according to the data?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 7", + "B. 8", + "C. 9", + "D. 10", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-018", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw a transition from El Niño to La Niña and still reached a new global temperature record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2021", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-019", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years ranks as the third warmest globally as of 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2020", + "C. 2017", + "D. 2019", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-020", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year had the highest global temperature anomaly on record according to the data?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2020", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-021", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years experienced the largest year-over-year increase in global temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010 to 2011", + "B. 2014 to 2015", + "C. 2019 to 2020", + "D. 2022 to 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-022", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following periods had three consecutive years of record-high temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014–2016", + "B. 2016–2018", + "C. 2017–2019", + "D. 2021–2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-023", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What pattern is observed in the global temperature anomalies from 2014 through 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. No clear trend", + "B. Gradual cooling trend", + "C. Overall warming trend with record highs", + "D. Annual fluctuations without consistent direction", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-024", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was the warmest globally without the influence of an El Niño?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2011", + "C. 2013", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-025", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which decade, according to the data, was the warmest on record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 1990–1999", + "B. 2000–2009", + "C. 2010–2019", + "D. 2011–2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-026", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which period did the most rapid acceleration in warming occur based on decadal trends?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 1880–1920", + "B. 1950–1970", + "C. 1982–2024", + "D. 2000–2010", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-027", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Among La Niña years, which year recorded the warmest global temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2021", + "D. 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-028", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year broke the previous warmest year record set in 2016?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2018", + "B. 2019", + "C. 2023", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-029", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. How many of the top 10 warmest years occurred between 2014 and 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 6", + "B. 8", + "C. 9", + "D. 10", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-030", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of these years had the least impact from El Niño or La Niña (ENSO-neutral), yet recorded a record-high anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-031", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years followed a strong El Niño year and still remained among the top 3 warmest globally?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2017", + "B. 2013", + "C. 2012", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-032", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What temperature anomaly threshold was first crossed globally in 2015?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 0.60°C", + "B. 0.70°C", + "C. 0.90°C", + "D. 1.10°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-033", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which of the following years did the global temperature anomaly increase by more than 0.1°C compared to the previous record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2015", + "C. 2023", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-034", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of these years marked the 45th consecutive year of above-average global temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2018", + "C. 2020", + "D. 2021", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-035", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following years marked the first in a three-year streak of record-breaking global temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-036", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What was the warmest year globally according to NOAA's records as of 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2016", + "B. 2023", + "C. 2020", + "D. 2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-037", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year experienced the largest year-to-year temperature increase compared to the previous year?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2017", + "D. 2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-038", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Between which two years did global temperature anomalies tie or remain almost the same?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2010 and 2011", + "B. 2019 and 2020", + "C. 2012 and 2013", + "D. 2015 and 2016", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-039", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year was the warmest globally in the absence of an El Niño event?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2013", + "B. 2014", + "C. 2017", + "D. 2018", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-040", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. According to the dot plot, which of the following years had the lowest global temperature anomaly since 2010?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2013", + "D. 2014", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-041", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw the largest gap between land and ocean temperature anomalies?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015", + "B. 2016", + "C. 2017", + "D. 2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-042", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Between 2014 and 2024, what pattern is observed in the sequence of annual global temperatures?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Fluctuating without a trend", + "B. Constant from year to year", + "C. Consistent warming with most years setting new records", + "D. Alternating warming and cooling cycles", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-043", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year marked the beginning of a five-year stretch where all individual years were among the five warmest on record at the time?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014", + "B. 2015", + "C. 2016", + "D. 2017", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-044", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Based on the trend seen in the dot plot, which decade had the highest rate of global temperature increase?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 1980–1990", + "B. 1990–2000", + "C. 2000–2010", + "D. 2010–2020", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-045", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which of the following pairs of consecutive years both broke the previous global temperature record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2014–2015", + "B. 2011–2012", + "C. 2018–2019", + "D. 2022–2023", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-046", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which year saw the start of the warmest 10-year period on record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2009", + "B. 2010", + "C. 2014", + "D. 2015", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-047", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. During which La Niña year was the global temperature anomaly the highest?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2011", + "B. 2012", + "C. 2021", + "D. 2022", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-048", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. Which consecutive years showed the highest two-year average global temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 2015–2016", + "B. 2016–2017", + "C. 2019–2020", + "D. 2023–2024", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-049", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. How many years since 2010 were recorded as the warmest year globally at the time they occurred?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 3", + "B. 4", + "C. 5", + "D. 6", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "long_term-temperature_trend-050", + "Text": "You are given visualization for annual global climate anomaly since 2010 to 2024. What trend is evident in the global temperature anomaly data from 2010 to 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2013.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2014.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2015.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2016.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2017.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2018.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2019.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2020.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2021.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2022.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2023.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-annual-mntp-2024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "long term", + "L3-task": "Perception", + "L4-task": "Long-term temperature trend", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Random fluctuations year to year", + "B. Cooling trend since 2016", + "C. Gradual increase with notable peaks", + "D. No clear trend visible", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Cyclone_movement_identification.json b/jsons/Atmosphere/medium_term/Perception/Cyclone_movement_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..0d23ea3feb41f22be83e45fa7e93915f671e8280 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Cyclone_movement_identification.json @@ -0,0 +1,6549 @@ +[ + { + "Question_id": "medium_term-Cyclone_movement_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast united states", + "Answer Choices": [ + "(A) Northwest United States", + "(B) Southeast United States", + "(C) Midwest United States", + "(D) Northeast United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Tunisia", + "Answer Choices": [ + "(A) Algeria", + "(B) Morocco", + "(C) Libya", + "(D) Tunisia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Southeast Asia", + "(B) Eastern Asia", + "(C) Central Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest usa", + "Answer Choices": [ + "(A) Northeast USA", + "(B) Northwest USA", + "(C) Southeast USA", + "(D) Central USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) New Zealand", + "(B) Australia", + "(C) Fiji", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "France", + "Answer Choices": [ + "(A) United Kingdom", + "(B) Germany", + "(C) Italy", + "(D) France", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Western Europe", + "(C) Southern Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) New Zealand", + "(C) Fiji", + "(D) Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern united states", + "Answer Choices": [ + "(A) Western United States", + "(B) Eastern United States", + "(C) Central Canada", + "(D) Northern Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) South Korea", + "(B) Japan", + "(C) China", + "(D) Taiwan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Morocco", + "(B) South Africa", + "(C) Nigeria", + "(D) Kenya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern canada", + "Answer Choices": [ + "(A) Eastern Canada", + "(B) Midwestern United States", + "(C) Pacific Northwest", + "(D) Southeastern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) South Asia", + "(B) Eastern Asia", + "(C) Southeast Asia", + "(D) Central Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "England", + "Answer Choices": [ + "(A) Netherlands", + "(B) France", + "(C) England", + "(D) Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Southern Europe", + "(C) Eastern Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northern china", + "Answer Choices": [ + "(A) Northern China", + "(B) Western Japan", + "(C) Eastern Russia", + "(D) Southern India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Tunisia", + "Answer Choices": [ + "(A) Morocco", + "(B) Tunisia", + "(C) Algeria", + "(D) Libya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast usa", + "Answer Choices": [ + "(A) Northeast USA", + "(B) Midwest USA", + "(C) Pacific Northwest USA", + "(D) Southeast USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) South Asia", + "(B) Central Asia", + "(C) Eastern Asia", + "(D) Southeast Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast usa", + "Answer Choices": [ + "(A) Southeast USA", + "(B) Northeast USA", + "(C) Pacific Northwest USA", + "(D) Midwest USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western usa", + "Answer Choices": [ + "(A) Northern Africa", + "(B) Western USA", + "(C) Southern UK", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) New Zealand", + "(D) Fiji", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Botswana", + "(B) Zimbabwe", + "(C) Namibia", + "(D) South Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern usa", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) New Zealand", + "(B) Papua New Guinea", + "(C) Australia", + "(D) Fiji", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northern china", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern India", + "(C) Southeast Asia", + "(D) Northern China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Egypt", + "Answer Choices": [ + "(A) Libya", + "(B) Chad", + "(C) Egypt", + "(D) Sudan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Eastern Europe", + "(C) Western Europe", + "(D) Southern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northern pacific", + "Answer Choices": [ + "(A) Southeast Asia", + "(B) Middle East", + "(C) Central Asia", + "(D) Northern Pacific", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) South Asia", + "(B) Southeast Asia", + "(C) Central Asia", + "(D) Eastern Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) South Africa", + "(B) Botswana", + "(C) Namibia", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Germany", + "Answer Choices": [ + "(A) France", + "(B) Czech Republic", + "(C) Germany", + "(D) Poland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Australia", + "(B) New zealand", + "(C) Papua New Guinea", + "(D) Fiji", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Central usa", + "Answer Choices": [ + "(A) Southeastern USA", + "(B) Pacific Northwest", + "(C) Northeastern USA", + "(D) Central USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northern china", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern India", + "(C) Central Japan", + "(D) Northern China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Central Asia", + "(B) Southeast Asia", + "(C) Eastern Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) South Africa", + "(B) Botswana", + "(C) Namibia", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southern australia", + "Answer Choices": [ + "(A) New Zealand", + "(B) Southern Australia", + "(C) Northern Australia", + "(D) Eastern Indonesia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western usa", + "Answer Choices": [ + "(A) Central Canada", + "(B) Western USA", + "(C) Eastern USA", + "(D) Southeastern Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Western Europe", + "(C) Southern Europe", + "(D) Northern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Central Asia", + "(B) Southeast Asia", + "(C) South Asia", + "(D) Eastern Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northern pacific", + "Answer Choices": [ + "(A) Northern Pacific", + "(B) Southeastern Canada", + "(C) Midwest United States", + "(D) Southern California", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest usa", + "Answer Choices": [ + "(A) Central USA", + "(B) Southeast USA", + "(C) Northwest USA", + "(D) Northeast USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Botswana", + "(B) South Africa", + "(C) Zimbabwe", + "(D) Namibia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "France", + "Answer Choices": [ + "(A) Germany", + "(B) United Kingdom", + "(C) France", + "(D) Italy", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) Vietnam", + "(B) Thailand", + "(C) Japan", + "(D) Philippines", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Mexico", + "Answer Choices": [ + "(A) Mexico", + "(B) Louisiana", + "(C) Texas", + "(D) Florida", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Fiji", + "Answer Choices": [ + "(A) Fiji", + "(B) Solomon Islands", + "(C) Vanuatu", + "(D) Tonga", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Philipphines", + "Answer Choices": [ + "(A) Thailand", + "(B) Philipphines", + "(C) Malaysia", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Mozambique", + "(B) Tanzania", + "(C) Madagascar", + "(D) Kenya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Caribbean", + "Answer Choices": [ + "(A) Texas", + "(B) Louisiana", + "(C) Caribbean", + "(D) Florida", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) Philippines", + "(B) Vietnam", + "(C) Japan", + "(D) Thailand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern usa", + "Answer Choices": [ + "(A) Northern Mexico", + "(B) Central Canada", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Fiji", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Tonga", + "(C) Fiji", + "(D) Samoa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Mozambique", + "(B) Kenya", + "(C) Tanzania", + "(D) Madagascar", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Central mediterranean", + "Answer Choices": [ + "(A) Eastern Mediterranean", + "(B) Central Mediterranean", + "(C) Western Europe", + "(D) Northern Balkans", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Madagascar", + "(B) Mozambique", + "(C) Tanzania", + "(D) Kenya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Fiji", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Fiji", + "(C) Tonga", + "(D) Solomon Islands", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Central america", + "Answer Choices": [ + "(A) Central America", + "(B) Mexico", + "(C) Caribbean Islands", + "(D) Southeastern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) Thailand", + "(B) Vietnam", + "(C) Bangladesh", + "(D) India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_018.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Madagascar", + "(B) Tanzania", + "(C) Mozambique", + "(D) Kenya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Kenya", + "(B) Tanzania", + "(C) Madagascar", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Solomon islands", + "Answer Choices": [ + "(A) Vanuatu", + "(B) Fiji", + "(C) Solomon Islands", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) Philippines", + "(B) Japan", + "(C) Vietnam", + "(D) Thailand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern usa", + "Answer Choices": [ + "(A) Western USA", + "(B) Eastern Mexico", + "(C) Eastern USA", + "(D) Central Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastern usa", + "Answer Choices": [ + "(A) Northern Mexico", + "(B) Central Canada", + "(C) Western USA", + "(D) Eastern USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Australia", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Ionian sea", + "Answer Choices": [ + "(A) Tyrrhenian Sea", + "(B) Aegean Sea", + "(C) Adriatic Sea", + "(D) Ionian Sea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Myanmar", + "Answer Choices": [ + "(A) Bangladesh", + "(B) Myanmar", + "(C) Thailand", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Fiji", + "(B) Australia", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Western mediterranean", + "Answer Choices": [ + "(A) Baltic Sea", + "(B) Western Mediterranean", + "(C) Eastern Mediterranean", + "(D) North Sea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Madagascar", + "Answer Choices": [ + "(A) Madagascar", + "(B) Tanzania", + "(C) Kenya", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Caribbean", + "Answer Choices": [ + "(A) Gulf Coast", + "(B) Yucatan Peninsula", + "(C) Florida", + "(D) Caribbean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) Philippines", + "(B) Japan", + "(C) Vietnam", + "(D) South Korea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Philippines", + "Answer Choices": [ + "(A) Philippines", + "(B) Malaysia", + "(C) Vietnam", + "(D) Thailand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Central mediterranean", + "Answer Choices": [ + "(A) Western Balkans", + "(B) Central Mediterranean", + "(C) Northern Italy", + "(D) Eastern Mediterranean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_018.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Fiji", + "Answer Choices": [ + "(A) Fiji", + "(B) Tonga", + "(C) Solomon Islands", + "(D) Vanuatu", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_016.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southern usa", + "Answer Choices": [ + "(A) Southern USA", + "(B) Central America", + "(C) Eastern Mexico", + "(D) Northern USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/33_24h/msl_016.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Dominica", + "Answer Choices": [ + "(A) Colombia", + "(B) Dominica", + "(C) Venezuela", + "(D) Brazil", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Greece", + "Answer Choices": [ + "(A) Italy", + "(B) Bulgaria", + "(C) Turkey", + "(D) Greece", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Zimbabwe", + "Answer Choices": [ + "(A) Zimbabwe", + "(B) Zambia", + "(C) Botswana", + "(D) Mozambique", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Fiji", + "Answer Choices": [ + "(A) Samoa", + "(B) Tonga", + "(C) Fiji", + "(D) Vanuatu", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) Thailand", + "(B) Myanmar", + "(C) Bangladesh", + "(D) India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Ionian sea", + "Answer Choices": [ + "(A) Aegean Sea", + "(B) Adriatic Sea", + "(C) Ionian Sea", + "(D) Tyrrhenian Sea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Philippines", + "Answer Choices": [ + "(A) Malaysia", + "(B) Vietnam", + "(C) Thailand", + "(D) Philippines", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Zimbabwe", + "Answer Choices": [ + "(A) Mozambique", + "(B) Botswana", + "(C) Malawi", + "(D) Zimbabwe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southeastern usa", + "Answer Choices": [ + "(A) Midwestern USA", + "(B) Southwestern USA", + "(C) Southeastern USA", + "(D) Northeastern USA", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/42_6h/msl_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Central mediterranean", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Northern Balkans", + "(C) Western Mediterranean", + "(D) Central Mediterranean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Puerto rico", + "Answer Choices": [ + "(A) Florida", + "(B) Puerto Rico", + "(C) Louisiana", + "(D) Texas", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "East australia", + "Answer Choices": [ + "(A) New Zealand", + "(B) East Australia", + "(C) Papua New Guinea", + "(D) Fiji", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Northeast", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Eastward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northward", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Southwestward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southeast", + "(B) Northeast", + "(C) Northwest", + "(D) Southwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Westward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Eastward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Southward", + "(C) Northward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Southward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Northward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Northeast", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southwest", + "(B) Northeast", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Eastward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Southward", + "(C) Eastward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Northward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Eastward", + "(B) Westward", + "(C) Southward", + "(D) Northward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Westward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Eastward", + "(C) Southward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Southward", + "(C) Eastward", + "(D) Westward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northward", + "Answer Choices": [ + "(A) Southward", + "(B) Northward", + "(C) Westward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Southward", + "(B) Westward", + "(C) Northward", + "(D) Eastward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Northward", + "(B) Westward", + "(C) Eastward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Eastward", + "Answer Choices": [ + "(A) Westward", + "(B) Northward", + "(C) Eastward", + "(D) Southward", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southeast", + "(B) Northeast", + "(C) Southwest", + "(D) Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest", + "Answer Choices": [ + "(A) Northwest", + "(B) Southeast", + "(C) Southwest", + "(D) Northeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southeast", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Southeast", + "(D) Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) west", + "(B) east", + "(C) south", + "(D) north", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest", + "Answer Choices": [ + "(A) Northwest", + "(B) Northeast", + "(C) Southeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Southeast", + "(B) Northwest", + "(C) Northeast", + "(D) Southwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southeast", + "Answer Choices": [ + "(A) Southwest", + "(B) Southeast", + "(C) Northeast", + "(D) East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southwest", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) Northwest", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) East", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) West", + "(D) East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) West", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northwest", + "Answer Choices": [ + "(A) Northeast", + "(B) Southeast", + "(C) Northwest", + "(D) Southwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) South", + "(B) North", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West then south", + "Answer Choices": [ + "(A) Northwest then west", + "(B) West then south", + "(C) East then north", + "(D) South then east", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West then north", + "Answer Choices": [ + "(A) West then North", + "(B) West then South", + "(C) East then North", + "(D) South then East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West then north", + "Answer Choices": [ + "(A) South then West", + "(B) East then North", + "(C) West then North", + "(D) North then West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) North", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/21_6h/msl_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) North", + "(B) East", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Northeast", + "Answer Choices": [ + "(A) Northwest", + "(B) Southwest", + "(C) Southeast", + "(D) Northeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/24_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) North", + "(B) South", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) West", + "(B) South", + "(C) North", + "(D) East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West then east", + "Answer Choices": [ + "(A) South then north", + "(B) West then east", + "(C) East then west", + "(D) North then south", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) South", + "(D) East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/29_24h/msl_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) North", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/30_6h/msl_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "East", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South", + "Answer Choices": [ + "(A) North", + "(B) South", + "(C) East", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_016.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) South", + "(B) East", + "(C) North", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "East", + "Answer Choices": [ + "(A) South", + "(B) West", + "(C) East", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/35_24h/msl_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/36_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "Southeast", + "Answer Choices": [ + "(A) Northeast", + "(B) Southwest", + "(C) East", + "(D) Southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/37_6h/msl_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) West", + "(B) South", + "(C) North", + "(D) East", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/38_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) East", + "(B) West", + "(C) South", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/39_24h/msl_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) South", + "(D) West", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/40_24h/msl_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "West", + "Answer Choices": [ + "(A) South", + "(B) West", + "(C) East", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/41_24h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) East", + "(B) South", + "(C) West", + "(D) North", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/43_24h/msl_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "North", + "Answer Choices": [ + "(A) East", + "(B) North", + "(C) West", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Cyclone_movement_identification-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. In which direction is the cyclone moving?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/44_24h/msl_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone movement identification", + "Dataset": "ERA5", + "Answer": "South", + "Answer Choices": [ + "(A) North", + "(B) West", + "(C) East", + "(D) South", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Cyclone_phase_identification.json b/jsons/Atmosphere/medium_term/Perception/Cyclone_phase_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..05c593199cd69cea9afa35961d0e9cecb4ee3ca2 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Cyclone_phase_identification.json @@ -0,0 +1,5645 @@ +[ + { + "Question_id": "Cyclone phase identification/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Occlusion Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Occlusion Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Dissipating Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/v10_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Formation Phase", + "(C) Peak Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Occlusion Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/v10_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Intensification Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Formation Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/v10_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Intensification Phase", + "(C) Dissipation Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Formation Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/v10_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 12?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Dissipation Phase", + "(C) Formation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 12?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Intensification Phase", + "(C) Formation Phase", + "(D) Dissipating Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 12?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Formation Phase", + "(C) Peak Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Intensification Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Occlusion Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Occlusion Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Formation Phase", + "(C) Dissipation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Peak Phase", + "(C) Intensification Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Intensification Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/v10_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Occlusion Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Intensification Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Mature Phase", + "(C) Formation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Early Phase", + "(C) Intensification Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Formation Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/v10_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Intensification Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/v10_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Intensification Phase", + "(C) Formation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Intensification Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/v10_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Occlusion Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Intensification Phase", + "(C) Dissipation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/v10_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Dissipation Phase", + "(C) Formation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Occlusion Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/v10_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Occlusion Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 18?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Formation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 18?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Mature Phase", + "(C) Intensification Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 18?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/v10_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Formation Phase", + "(C) Decay Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/v10_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Peak Phase", + "(C) Intensification Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Peak Phase", + "(C) Weakening Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Peak Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Mature Phase", + "(C) Intensification Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Intensification Phase", + "(C) Formation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/19_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Peak Phase", + "(C) Formation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Occlusion Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Intensification Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/20_24h/v10_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Occlusion Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Peak Phase", + "(C) Intensification Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Intensification Phase", + "(C) Dissipation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/22_6h/v10_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Formation Phase", + "(C) Intensification Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Intensification Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/23_24h/v10_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_016.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Peak Phase", + "(C) Dissipation Phase", + "(D) Development Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/70", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_016.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Intensification Phase", + "(C) Formation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/71", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/32_24h/v10_016.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Peak Phase", + "(C) Dissipation Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/72", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/73", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Decay Phase", + "(C) Peak Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/74", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/25_6h/v10_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Formation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/75", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/76", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Intensification Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/77", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/26_24h/v10_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Mature Phase", + "(C) Dissipating Phase", + "(D) Developing Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/78", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Occlusion Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/79", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Intensification Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/80", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/27_24h/v10_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Occlusion Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/81", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/82", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Peak Phase", + "(C) Mature Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/83", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/28_6h/v10_018.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Decay Phase", + "(C) Intensification Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/84", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Intensification Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/85", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/86", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/u10_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/31_24h/v10_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Occlusion Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/87", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Formation Phase", + "(C) Decay Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/88", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Formation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Intensification Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Cyclone phase identification/89", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What phase is the cyclone in on frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/u10_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/34_6h/v10_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Cyclone phase identification", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Intensification Phase", + "(C) Decay Phase", + "(D) Formation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Event_intensity_identification.json b/jsons/Atmosphere/medium_term/Perception/Event_intensity_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..a5bf7ec02b4497eb9fc5510b30458bbc00064f71 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Event_intensity_identification.json @@ -0,0 +1,27819 @@ +[ + { + "Question_id": "medium_term-Event_intensity_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Kinshasa?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 35~40 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-30~-25 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) -30~-25 °C", + "(C) -35~-30 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Toronto?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-30~-25 °C", + "Answer Choices": [ + "(A) -30~-25 °C", + "(B) -20~-15 °C", + "(C) -35~-30 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Wellington?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-20~-15 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -30~-25 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 11~15 °C", + "(D) 6~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Madrid?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Moscow?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Madrid?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 6~10 °C", + "(B) 11~15 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-20~-15 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -20~-15 °C", + "(C) -5~0 °C", + "(D) -30~-25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Ulaanbaatar?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -15~-10 °C", + "(C) -25~-20 °C", + "(D) -35~-30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -15~-10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Ulaanbaatar?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -25~-20 °C", + "(C) -15~-10 °C", + "(D) -35~-30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Beijing?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -15~-10 °C", + "(C) -20~-15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Nairobi?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 30~35 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Moscow?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -35~-30 °C", + "(C) -15~-10 °C", + "(D) -25~-20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 6~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 0~5 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at New York?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Wellington?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Cairo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "45~50 °C", + "Answer Choices": [ + "(A) 40~45 °C", + "(B) 35~40 °C", + "(C) 45~50 °C", + "(D) 50~55 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-20~-15 °C", + "Answer Choices": [ + "(A) -30~-25 °C", + "(B) -20~-15 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Ulaanbaatar?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -35~-30 °C", + "(B) -15~-10 °C", + "(C) -45~-40 °C", + "(D) -25~-20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 17~22 °C", + "(B) 5~10 °C", + "(C) 12~17 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 6~10 °C", + "(B) -5~0 °C", + "(C) 11~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Madrid?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at London?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Kinshasa?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 35~40 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Wellington?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -2~3 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Beijing?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -20~-15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -40~-35 °C", + "(B) -35~-30 °C", + "(C) -15~-10 °C", + "(D) -25~-20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Moscow?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) 0~5 °C", + "(C) -20~-15 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Wellington?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -25~-20 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) -20~-15 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Madrid?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 25~30 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Cairo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Kinshasa?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Madrid?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 30~35 °C", + "(C) 20~25 °C", + "(D) 35~40 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Nairobi?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Cairo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Beijing?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 950~990 hPa", + "(B) 1000~1100 hPa", + "(C) 870~950 hPa", + "(D) 1100~1150 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at London?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 700~800 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Tokyo?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Kinshasa?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Cairo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mumbai?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 850~950 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at London?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 700~800 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Athens?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Moscow?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 20~25 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Beijing?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Athens?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Nairobi?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Beijing?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Kinshasa?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 20~25 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Tokyo?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~950 hPa", + "(B) 1000~1100 hPa", + "(C) 1150~1200 hPa", + "(D) 1100~1150 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at New York?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 20~25 mm", + "(C) 0~5 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Cairo?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Tokyo?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 2~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Kinshasa?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Kinshasa?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 85~90 %", + "(C) 70~75 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Kinshasa?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Nairobi?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 mm", + "Answer Choices": [ + "(A) 25~30 mm", + "(B) 35~40 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mexico City?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 70~75 %", + "(C) 85~90 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mexico City?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 10~15 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 20~25 %", + "(C) 30~35 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mumbai?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) -5~0 m³/m³", + "(C) 0~5 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Madrid?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 30~35 m³/m³", + "(B) 10~15 m³/m³", + "(C) 20~25 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 95~100 %", + "(B) 70~75 %", + "(C) 80~85 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Auckland?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 20~25 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 85~90 %", + "(C) 70~75 %", + "(D) 95~100 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Wellington?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 0~5 m³/m³", + "(C) 10~15 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 20~25 mm", + "(C) 30~35 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 30~35 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Wellington?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 15~20 m³/m³", + "(C) 5~10 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 40~45 %", + "(C) 20~25 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Mumbai?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Tokyo?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) 15~20 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Nairobi?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 15~20 m³/m³", + "(C) 10~15 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Moscow?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 100~105 %", + "(C) 85~90 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "90~95 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 80~85 %", + "(C) 60~65 %", + "(D) 90~95 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Ulaanbaatar?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_037.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 30~35 m³/m³", + "(B) 0~5 m³/m³", + "(C) 10~15 m³/m³", + "(D) 20~25 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_037.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 30~35 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_030.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 80~85 %", + "(B) 90~95 %", + "(C) 100~105 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Wellington?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Wellington?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_030.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 10~15 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_030.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at New York?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 10~15 m³/m³", + "(C) 0~5 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at London?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) 15~20 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-229", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-230", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-231", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Tokyo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 10~15 %", + "(C) 20~25 %", + "(D) 0~5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-232", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Tokyo?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-233", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Tokyo?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 5~10 m³/m³", + "(C) 15~20 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-234", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-235", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-236", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 10~15 %", + "(C) 0~5 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-237", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Auckland?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-238", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-239", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mexico City?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 80~85 %", + "(B) 60~65 %", + "(C) 95~100 %", + "(D) 70~75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-240", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-241", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-242", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 95~100 %", + "(C) 70~75 %", + "(D) 85~90 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-243", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Wellington?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-244", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-245", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Madrid?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 10~15 %", + "(C) 40~45 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-246", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Madrid?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-247", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-248", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mexico City?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 10~15 m³/m³", + "(C) 15~20 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-249", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-250", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Athens?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 20~25 %", + "(C) 30~35 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-251", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Madrid?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-252", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-253", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Moscow?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 30~35 %", + "(C) 20~25 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-254", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Athens?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 20~25 m³/m³", + "(C) 0~5 m³/m³", + "(D) 30~35 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-255", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Athens?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-256", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-257", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Ulaanbaatar?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 16~20 %", + "(B) 11~15 %", + "(C) 0~5 %", + "(D) 6~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-258", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Mumbai?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-259", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mumbai?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 15~20 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-260", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-261", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-262", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Nairobi?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "60~65 %", + "Answer Choices": [ + "(A) 50~55 %", + "(B) 60~65 %", + "(C) 40~45 %", + "(D) 70~75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-263", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-264", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "85~90 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 95~100 %", + "(C) 70~75 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-265", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Wellington?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 20~25 m³/m³", + "(C) 0~5 m³/m³", + "(D) 30~35 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-266", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-267", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-268", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Toronto?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 85~90 %", + "(C) 100~105 %", + "(D) 70~75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-269", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-270", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Tokyo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 80~85 %", + "(C) 60~65 %", + "(D) 95~100 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-271", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Mumbai?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-272", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Ulaanbaatar?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 15~20 m³/m³", + "(C) 5~10 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-273", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-274", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-275", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Athens?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 5~10 %", + "(C) 30~35 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-276", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Moscow?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-277", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -2~3 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-278", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-279", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Beijing?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 95~100 %", + "(B) 70~75 %", + "(C) 80~85 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-280", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Beijing?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_037.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-281", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-282", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Cairo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_037.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-283", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Nairobi?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "70~75 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 50~55 %", + "(C) 60~65 %", + "(D) 80~85 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-284", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Kinshasa?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 10~15 m³/m³", + "(C) 15~20 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-285", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 30~35 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-286", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at São Paulo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-287", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at São Paulo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 70~75 %", + "(C) 60~65 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-288", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Lima?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-289", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at São Paulo?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_018.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) 15~20 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-290", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Lima?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-291", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-292", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 20~25 %", + "(C) 0~5 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-293", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Sydney?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 15~20 m³/m³", + "(C) 5~10 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-294", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-295", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Madrid?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "75~80 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 55~60 %", + "(C) 65~70 %", + "(D) 75~80 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-296", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at London?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 15~20 m³/m³", + "(C) 10~15 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-297", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-298", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "55~60 %", + "Answer Choices": [ + "(A) 55~60 %", + "(B) 30~35 %", + "(C) 65~70 %", + "(D) 40~45 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-299", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mumbai?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) -10~-5 m³/m³", + "(C) -5~0 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-300", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-301", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 20~25 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-302", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at New York?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "75~80 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 75~80 %", + "(C) 60~65 %", + "(D) 45~50 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-303", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Mexico City?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 15~20 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-304", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -2~3 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-305", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at São Paulo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 10~15 %", + "(C) 40~45 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-306", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Lima?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-307", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-308", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Auckland?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 55~60 %", + "(C) 85~90 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-309", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Auckland?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 15~20 m³/m³", + "(C) 10~15 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-310", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-311", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-312", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Ulaanbaatar?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "70~75 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 50~55 %", + "(C) 70~75 %", + "(D) 80~85 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-313", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of sst at Mumbai?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-314", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Beijing?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 15~20 m³/m³", + "(C) 0~5 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-315", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-316", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Kinshasa?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 %", + "Answer Choices": [ + "(A) 50~55 %", + "(B) 20~25 %", + "(C) 40~45 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-317", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of swvl1 at Cairo?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 15~20 m³/m³", + "(C) 0~5 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-318", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 35~40 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-319", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Toronto?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-285~-280 W/m²", + "Answer Choices": [ + "(A) -290~-285 W/m²", + "(B) -285~-280 W/m²", + "(C) -300~-295 W/m²", + "(D) -270~-265 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-320", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-321", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-322", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-323", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Wellington?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -290~-285 W/m²", + "(B) -230~-225 W/m²", + "(C) -270~-265 W/m²", + "(D) -250~-245 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-324", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-325", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Moscow?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-326", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-327", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Moscow?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -270~-265 W/m²", + "(B) -250~-245 W/m²", + "(C) -285~-280 W/m²", + "(D) -300~-295 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-328", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at New York?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-329", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-330", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-331", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Ulaanbaatar?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-332", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 20~25 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-333", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Beijing?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-285~-280 W/m²", + "Answer Choices": [ + "(A) -300~-295 W/m²", + "(B) -285~-280 W/m²", + "(C) -270~-265 W/m²", + "(D) -290~-285 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-334", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Cairo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 35~40 °C", + "(B) 45~50 °C", + "(C) 40~45 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-335", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-336", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Nairobi?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-265~-260 W/m²", + "Answer Choices": [ + "(A) -270~-265 W/m²", + "(B) -280~-275 W/m²", + "(C) -250~-245 W/m²", + "(D) -265~-260 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-337", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 30~35 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-338", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Nairobi?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-339", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Kinshasa?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-260~-255 W/m²", + "Answer Choices": [ + "(A) -300~-295 W/m²", + "(B) -260~-255 W/m²", + "(C) -240~-235 W/m²", + "(D) -275~-270 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-340", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-341", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-342", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-343", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Sydney?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-280~-275 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -300~-295 W/m²", + "(C) -240~-235 W/m²", + "(D) -280~-275 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-344", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 25~30 °C", + "(D) 35~40 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-345", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-346", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-347", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-348", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mexico City?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-255~-250 W/m²", + "Answer Choices": [ + "(A) -240~-235 W/m²", + "(B) -275~-270 W/m²", + "(C) -200~-195 W/m²", + "(D) -255~-250 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-349", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-350", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 30~35 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-351", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-352", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mumbai?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-275~-270 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -275~-270 W/m²", + "(C) -245~-240 W/m²", + "(D) -290~-285 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-353", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-354", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Toronto?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-355", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-356", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at New York?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-175~-170 W/m²", + "Answer Choices": [ + "(A) -145~-140 W/m²", + "(B) -190~-185 W/m²", + "(C) -160~-155 W/m²", + "(D) -175~-170 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-357", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-358", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 30~35 °C", + "(C) 25~30 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-359", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-360", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mumbai?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-320~-315 W/m²", + "Answer Choices": [ + "(A) -280~-275 W/m²", + "(B) -300~-295 W/m²", + "(C) -320~-315 W/m²", + "(D) -350~-345 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-361", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Madrid?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-325~-320 W/m²", + "Answer Choices": [ + "(A) -325~-320 W/m²", + "(B) -295~-290 W/m²", + "(C) -310~-305 W/m²", + "(D) -340~-335 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-362", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-363", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-364", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-365", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Wellington?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-255~-250 W/m²", + "Answer Choices": [ + "(A) -225~-220 W/m²", + "(B) -270~-265 W/m²", + "(C) -240~-235 W/m²", + "(D) -255~-250 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-366", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Cairo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 45~50 °C", + "(B) 35~40 °C", + "(C) 30~35 °C", + "(D) 40~45 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-367", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Cairo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-368", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Nairobi?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-240~-235 W/m²", + "Answer Choices": [ + "(A) -200~-195 W/m²", + "(B) -220~-215 W/m²", + "(C) -240~-235 W/m²", + "(D) -260~-255 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-369", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-370", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at London?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-371", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-372", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Athens?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-315~-310 W/m²", + "Answer Choices": [ + "(A) -290~-285 W/m²", + "(B) -300~-295 W/m²", + "(C) -330~-325 W/m²", + "(D) -315~-310 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-373", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-374", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-375", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-376", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Lima?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-377", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at São Paulo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-378", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Lima?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-280~-275 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -245~-240 W/m²", + "(C) -300~-295 W/m²", + "(D) -280~-275 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-379", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-380", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_030.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 30~35 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-381", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_030.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-382", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Ulaanbaatar?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-220~-215 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -220~-215 W/m²", + "(C) -200~-195 W/m²", + "(D) -190~-185 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-383", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 30~35 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-384", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-385", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Cairo?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-265~-260 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -280~-275 W/m²", + "(C) -270~-265 W/m²", + "(D) -265~-260 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-386", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-387", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-388", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-389", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Auckland?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -270~-265 W/m²", + "(B) -230~-225 W/m²", + "(C) -250~-245 W/m²", + "(D) -290~-285 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-390", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Nairobi?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-391", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Cairo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 35~40 °C", + "(B) 45~50 °C", + "(C) 40~45 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-392", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Nairobi?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-260~-255 W/m²", + "Answer Choices": [ + "(A) -290~-285 W/m²", + "(B) -275~-270 W/m²", + "(C) -240~-235 W/m²", + "(D) -260~-255 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-393", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 35~40 °C", + "(B) 30~35 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-394", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at London?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-170~-165 W/m²", + "Answer Choices": [ + "(A) -200~-195 W/m²", + "(B) -185~-180 W/m²", + "(C) -150~-145 W/m²", + "(D) -170~-165 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-395", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-396", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-397", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-398", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mumbai?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -270~-265 W/m²", + "(B) -230~-225 W/m²", + "(C) -250~-245 W/m²", + "(D) -290~-285 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-399", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at New York?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-400", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-401", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-402", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Toronto?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 0~5 °C", + "(C) 30~35 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-403", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-404", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Toronto?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-280~-275 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -265~-260 W/m²", + "(C) -300~-295 W/m²", + "(D) -280~-275 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-405", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-406", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-407", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-408", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Sydney?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -230~-225 W/m²", + "(B) -250~-245 W/m²", + "(C) -290~-285 W/m²", + "(D) -270~-265 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-409", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 30~35 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-410", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 18~22 °C", + "(C) 31~35 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-411", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 20~25 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-412", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Tokyo?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-285~-280 W/m²", + "Answer Choices": [ + "(A) -285~-280 W/m²", + "(B) -300~-295 W/m²", + "(C) -270~-265 W/m²", + "(D) -250~-245 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-413", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-414", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Beijing?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 25~30 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-415", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-416", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Ulaanbaatar?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-185~-180 W/m²", + "Answer Choices": [ + "(A) -185~-180 W/m²", + "(B) -175~-170 W/m²", + "(C) -200~-195 W/m²", + "(D) -160~-155 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-417", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-418", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-419", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Cairo?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-325~-320 W/m²", + "Answer Choices": [ + "(A) -325~-320 W/m²", + "(B) -340~-335 W/m²", + "(C) -295~-290 W/m²", + "(D) -310~-305 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-420", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Lima?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-421", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Lima?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-422", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Lima?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-423", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Lima?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-205~-200 W/m²", + "Answer Choices": [ + "(A) -180~-175 W/m²", + "(B) -230~-225 W/m²", + "(C) -205~-200 W/m²", + "(D) -160~-155 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-424", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-425", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-426", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-427", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Wellington?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-190~-185 W/m²", + "Answer Choices": [ + "(A) -210~-205 W/m²", + "(B) -140~-135 W/m²", + "(C) -170~-165 W/m²", + "(D) -190~-185 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-428", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Madrid?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 40~45 °C", + "(C) 45~50 °C", + "(D) 35~40 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-429", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Moscow?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-430", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Madrid?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-315~-310 W/m²", + "Answer Choices": [ + "(A) -315~-310 W/m²", + "(B) -250~-245 W/m²", + "(C) -290~-285 W/m²", + "(D) -360~-355 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-431", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-432", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Athens?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 35~40 °C", + "(B) 30~35 °C", + "(C) 40~45 °C", + "(D) 45~50 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-433", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-434", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Athens?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-305~-300 W/m²", + "Answer Choices": [ + "(A) -275~-270 W/m²", + "(B) -290~-285 W/m²", + "(C) -320~-315 W/m²", + "(D) -305~-300 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-435", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-436", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 2~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-437", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Toronto?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-170~-165 W/m²", + "Answer Choices": [ + "(A) -170~-165 W/m²", + "(B) -130~-125 W/m²", + "(C) -150~-145 W/m²", + "(D) -190~-185 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-438", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-439", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mumbai?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-440", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-441", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Beijing?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-230~-225 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -230~-225 W/m²", + "(C) -195~-190 W/m²", + "(D) -210~-205 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-442", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Moscow?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-443", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Athens?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-444", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Moscow?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-445", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Madrid?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-280~-275 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -280~-275 W/m²", + "(C) -300~-295 W/m²", + "(D) -240~-235 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-446", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 30~35 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-447", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-448", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-449", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Sydney?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-450", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-451", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Auckland?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-285~-280 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -285~-280 W/m²", + "(C) -270~-265 W/m²", + "(D) -300~-295 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-452", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-453", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-454", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-455", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Tokyo?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-200~-195 W/m²", + "Answer Choices": [ + "(A) -220~-215 W/m²", + "(B) -180~-175 W/m²", + "(C) -200~-195 W/m²", + "(D) -160~-155 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-456", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-457", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-458", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-459", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Sydney?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-245~-240 W/m²", + "Answer Choices": [ + "(A) -265~-260 W/m²", + "(B) -230~-225 W/m²", + "(C) -215~-210 W/m²", + "(D) -245~-240 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-460", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-461", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at London?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-240~-235 W/m²", + "Answer Choices": [ + "(A) -240~-235 W/m²", + "(B) -260~-255 W/m²", + "(C) -220~-215 W/m²", + "(D) -200~-195 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-462", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-463", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Kinshasa?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 35~40 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-464", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-465", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Nairobi?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-260~-255 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -240~-235 W/m²", + "(C) -300~-295 W/m²", + "(D) -275~-270 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-466", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-467", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Mexico City?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-468", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-469", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Toronto?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-275~-270 W/m²", + "Answer Choices": [ + "(A) -260~-255 W/m²", + "(B) -275~-270 W/m²", + "(C) -300~-295 W/m²", + "(D) -285~-280 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-470", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-471", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Auckland?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-472", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-473", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Wellington?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-270~-265 W/m²", + "Answer Choices": [ + "(A) -250~-245 W/m²", + "(B) -290~-285 W/m²", + "(C) -270~-265 W/m²", + "(D) -275~-270 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-474", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-475", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-476", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-477", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mumbai?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-310~-305 W/m²", + "Answer Choices": [ + "(A) -335~-330 W/m²", + "(B) -290~-285 W/m²", + "(C) -270~-265 W/m²", + "(D) -310~-305 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-478", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at New York?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-479", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-480", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Toronto?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-145~-140 W/m²", + "Answer Choices": [ + "(A) -115~-110 W/m²", + "(B) -145~-140 W/m²", + "(C) -130~-125 W/m²", + "(D) -160~-155 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-481", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Cairo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 40~45 °C", + "(B) 30~35 °C", + "(C) 45~50 °C", + "(D) 35~40 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-482", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Nairobi?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-255~-250 W/m²", + "Answer Choices": [ + "(A) -275~-270 W/m²", + "(B) -230~-225 W/m²", + "(C) -255~-250 W/m²", + "(D) -200~-195 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-483", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 20~25 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-484", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Madrid?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "40~45 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 40~45 °C", + "(C) 45~50 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-485", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-486", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Madrid?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-295~-290 W/m²", + "Answer Choices": [ + "(A) -295~-290 W/m²", + "(B) -310~-305 W/m²", + "(C) -280~-275 W/m²", + "(D) -265~-260 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-487", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 30~35 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-488", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Tokyo?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-489", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-490", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Mumbai?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-275~-270 W/m²", + "Answer Choices": [ + "(A) -240~-235 W/m²", + "(B) -260~-255 W/m²", + "(C) -290~-285 W/m²", + "(D) -275~-270 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-491", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at London?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_036.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-492", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_036.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-493", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Athens?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_036.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-300~-295 W/m²", + "Answer Choices": [ + "(A) -300~-295 W/m²", + "(B) -320~-315 W/m²", + "(C) -260~-255 W/m²", + "(D) -280~-275 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-494", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Lima?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-495", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at São Paulo?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-220~-215 W/m²", + "Answer Choices": [ + "(A) -180~-175 W/m²", + "(B) -220~-215 W/m²", + "(C) -240~-235 W/m²", + "(D) -200~-195 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-496", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 35~40 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-497", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 20~25 mm", + "(C) 0~5 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-498", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-499", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of skt at Wellington?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-500", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-501", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of mtnlwrf at Sydney?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-190~-185 W/m²", + "Answer Choices": [ + "(A) -190~-185 W/m²", + "(B) -210~-205 W/m²", + "(C) -170~-165 W/m²", + "(D) -200~-195 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-502", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-503", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Moscow?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 40~45 %", + "(C) 20~25 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-504", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -25~-20 °C", + "(B) -15~-10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-505", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-506", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Wellington?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-507", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 70~75 %", + "(C) 85~90 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-508", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-509", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-510", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-511", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-512", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Kinshasa?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "80~85 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 80~85 %", + "(C) 90~95 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-513", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-514", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-515", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Ulaanbaatar?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 11~15 %", + "(C) 16~20 %", + "(D) 6~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-516", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at London?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 30~35 %", + "(C) 20~25 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-517", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 20~25 mm", + "(C) 10~15 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-518", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-519", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-520", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-521", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Sydney?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "45~50 %", + "Answer Choices": [ + "(A) 45~50 %", + "(B) 55~60 %", + "(C) 35~40 %", + "(D) 25~30 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-522", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-523", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-524", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mexico City?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 30~35 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-525", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-526", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-20~-15 °C", + "Answer Choices": [ + "(A) -30~-25 °C", + "(B) -10~-5 °C", + "(C) -20~-15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-527", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "90~95 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 70~75 %", + "(C) 90~95 %", + "(D) 80~85 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-528", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-529", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-530", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Moscow?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-531", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Athens?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 60~65 %", + "(C) 100~105 %", + "(D) 70~75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-532", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-533", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at New York?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 6~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-534", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Toronto?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 85~90 %", + "(C) 60~65 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-535", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-536", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-30~-25 °C", + "Answer Choices": [ + "(A) -30~-25 °C", + "(B) -20~-15 °C", + "(C) -35~-30 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-537", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Ulaanbaatar?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 11~15 %", + "(B) 16~20 %", + "(C) 6~10 %", + "(D) 0~5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-538", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-539", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Kinshasa?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 70~75 %", + "(C) 80~85 %", + "(D) 95~100 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-540", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-541", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-542", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "35~40 %", + "Answer Choices": [ + "(A) 45~50 %", + "(B) 35~40 %", + "(C) 15~20 %", + "(D) 25~30 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-543", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-544", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Tokyo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-545", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 10~15 %", + "(C) 0~5 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-546", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Athens?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -2~3 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-547", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-548", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mexico City?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "60~65 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 45~50 %", + "(C) 30~35 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-549", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-550", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Toronto?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-551", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Madrid?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "35~40 %", + "Answer Choices": [ + "(A) 15~20 %", + "(B) 45~50 %", + "(C) 35~40 %", + "(D) 25~30 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-552", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-553", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-554", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Sydney?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 100~105 %", + "(B) 70~75 %", + "(C) 60~65 %", + "(D) 85~90 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-555", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-556", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-557", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Tokyo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 11~15 %", + "(B) 16~20 %", + "(C) 0~5 %", + "(D) 6~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-558", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 30~35 °C", + "(C) 35~40 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-559", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-560", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-561", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 85~90 %", + "(C) 70~75 %", + "(D) 95~100 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-562", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-563", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-564", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at New York?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 20~25 %", + "(C) 10~15 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-565", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-566", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Nairobi?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 26~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-567", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-568", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Beijing?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-569", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 20~25 %", + "(C) 0~5 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-570", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-571", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Athens?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-572", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Moscow?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 85~90 %", + "(C) 100~105 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-573", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Cairo?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-574", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Kinshasa?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "70~75 %", + "Answer Choices": [ + "(A) 80~85 %", + "(B) 70~75 %", + "(C) 50~55 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-575", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Moscow?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 55~60 %", + "(C) 85~90 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-576", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-577", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mexico City?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 6~10 °C", + "(B) −5~0 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-578", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-579", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Mumbai?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-580", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Ulaanbaatar?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 6~10 %", + "(C) 16~20 %", + "(D) 11~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-581", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-582", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Sydney?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-583", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Wellington?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "60~65 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 60~65 %", + "(C) 70~75 %", + "(D) 45~50 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-584", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Kinshasa?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-585", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Cairo?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 0~5 %", + "(C) 10~15 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-586", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Athens?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-587", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at London?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 85~90 %", + "(B) 100~105 %", + "(C) 70~75 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-588", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-589", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Ulaanbaatar?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-20~-15 °C", + "Answer Choices": [ + "(A) -30~-25 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-590", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mumbai?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 20~25 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-591", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Mexico City?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "45~50 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 55~60 %", + "(C) 45~50 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-592", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-593", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of t2m at Auckland?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-594", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tcc at Sydney?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "85~90 %", + "Answer Choices": [ + "(A) 95~100 %", + "(B) 85~90 %", + "(C) 70~75 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-595", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-596", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-597", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-598", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 6~10 mm", + "(C) 0~5 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-599", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1110~1150 hPa", + "(C) 950~990 hPa", + "(D) 880~940 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-600", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-601", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Beijing?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-602", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-603", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Toronto?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-604", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mumbai?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-605", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-606", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-607", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 30~35 mm", + "(C) 10~15 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-608", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 20~25 mm", + "(B) 30~35 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-609", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-610", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 20~25 mm", + "(D) 30~35 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-611", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-612", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-613", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-614", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-615", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-616", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Kinshasa?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-617", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-618", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Nairobi?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-619", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Nairobi?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-620", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1101~1150 hPa", + "(B) 950~999 hPa", + "(C) 900~949 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-621", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-622", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Tokyo?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-623", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-624", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-625", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mexico City?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-626", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-627", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-628", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-629", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Ulaanbaatar?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-630", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-631", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Sydney?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-632", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Wellington?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-633", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at London?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-634", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Nairobi?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-635", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Kinshasa?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 0~5 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-636", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at New York?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-637", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mumbai?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-638", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Beijing?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-639", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Tokyo?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-640", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Mumbai?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-641", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at London?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 700~800 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-642", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-643", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-644", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Auckland?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-645", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at New York?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-646", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 30~35 mm", + "(B) 20~25 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-647", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Lima?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 850~950 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-648", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Lima?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-649", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Moscow?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-650", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-651", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Nairobi?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-652", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Wellington?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-653", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 20~25 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-654", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mumbai?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-655", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Ulaanbaatar?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-656", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at London?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-657", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at London?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-658", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Beijing?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-659", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Tokyo?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-660", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Kinshasa?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-661", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Mexico City?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-662", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Madrid?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 2~5 mm", + "(C) 0~2 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-663", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Toronto?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 6~10 mm", + "(C) 0~5 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-664", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of msl at Auckland?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_intensity_identification-665", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of tp6h at Sydney?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Event_trend_analysis.json b/jsons/Atmosphere/medium_term/Perception/Event_trend_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..48f210b2afd8f9384c8d205ba386ddd2c5e72056 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Event_trend_analysis.json @@ -0,0 +1,26643 @@ +[ + { + "Question_id": "medium_term-Event_trend_analysis-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 4 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 5 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Cairo change from frame 1 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 4 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) −5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mexico City change from frame 5 to frame 7?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 6 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 0 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 2 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 7 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -25~-20 °C", + "(C) 0~5 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 9 to frame 15?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 7 to frame 10?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-25~-20 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -15~-10 °C", + "(C) -10~-5 °C", + "(D) -25~-20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 10 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -2~3 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Moscow change from frame 6 to frame 11?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Beijing change from frame 7 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 4 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Ulaanbaatar change from frame 1 to frame 12?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 5 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 7 to frame 8?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 2 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 7 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at London change from frame 0 to frame 10?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 7 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 8 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Ulaanbaatar change from frame 2 to frame 7?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mexico City change from frame 0 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -2~1 °C", + "(B) 6~10 °C", + "(C) 0~5 °C", + "(D) 11~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 6 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 3 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 8 to frame 9?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 0 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -2~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 13 to frame 18?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mexico City change from frame 7 to frame 24?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 2 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 7 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Kinshasa change from frame 7 to frame 8?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Moscow change from frame 7 to frame 9?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 1 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 2 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 5 to frame 7?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 1 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) −5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 1 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 0 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 11~15 °C", + "(B) -2~1 °C", + "(C) 0~5 °C", + "(D) 6~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 8 to frame 10?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 5 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Tokyo change from frame 0 to frame 4?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 3 to frame 10?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 1 to frame 4?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 2 to frame 9?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 5 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 0 to frame 1?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -2~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 5 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 1 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 6 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 11 to frame 14?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Tokyo change from frame 4 to frame 18?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 2 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 0 to frame 2?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Auckland change from frame 4 to frame 8?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 1 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -2~3 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at New York change from frame 3 to frame 12?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 0 to frame 5?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -2~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 2 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Kinshasa change from frame 2 to frame 3?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 1 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 1 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 30~35 mm", + "(D) 20~25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Auckland change from frame 2 to frame 3?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 1 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 10 to frame 14?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 7 to frame 14?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 16 to frame 17?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 29 to frame 30?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at New York change from frame 9 to frame 17?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_030.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) -25~-20 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 0 to frame 2?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 4 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 2 to frame 8?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 0 to frame 1?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 2 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 4 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 0 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 0 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mexico City change from frame 8 to frame 10?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 0 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -2~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 0 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -3~1 °C", + "(B) 6~10 °C", + "(C) 0~5 °C", + "(D) 11~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 0 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -3~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 4 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) −5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 2 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 0 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 0 to frame 5?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -3~1 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 6~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 2 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_014.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 0 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 1 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 20~25 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 1 to frame 3?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 6 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 3 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 5 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 0 to frame 3?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 3 to frame 9?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 1 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 1 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 0 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 16~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 4 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 2 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 0 to frame 1?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Nairobi change from frame 0 to frame 4?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Toronto change from frame 3 to frame 5?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 100~200 hPa", + "(C) −100~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 0 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 9 to frame 13?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Ulaanbaatar change from frame 3 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~50 hPa", + "(C) 50~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 12 to frame 16?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 11~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 0 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) -50~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 1 to frame 2?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 7 to frame 12?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -100~0 hPa", + "(C) 100~200 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 0 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Athens change from frame 0 to frame 1?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) −50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 1 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -20~-15 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Athens change from frame 1 to frame 3?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) 100~200 hPa", + "(D) −50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 2 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 1 to frame 9?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 100~200 hPa", + "(C) -100~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 8 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Toronto change from frame 0 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~0 hPa", + "(C) 0~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 3 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 0~5 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 2 to frame 10?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 9 to frame 13?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 mm", + "Answer Choices": [ + "(A) -20~-15 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 5 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 0 to frame 2?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 100~200 hPa", + "(C) -50~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 3 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 2 to frame 8?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 8 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 2 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 1 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 5 to frame 9?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -200~-100 hPa", + "(C) -100~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 2 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 5 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) 100~200 hPa", + "(D) -50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 5 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~2 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Tokyo change from frame 4 to frame 15?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) -200~-100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 0 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 2 to frame 6?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) 100~200 hPa", + "(D) -50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at London change from frame 4 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~0 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 2 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Auckland change from frame 8 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -200~-100 hPa", + "(C) 50~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 11 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 3 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 2 to frame 6?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 7 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at New York change from frame 0 to frame 4?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~50 hPa", + "(C) 50~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 0 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 25~30 mm", + "(B) 15~20 mm", + "(C) 1~2 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 4 to frame 8?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) −50~0 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 1 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Ulaanbaatar change from frame 12 to frame 18?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -100~0 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 0 to frame 16?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Nairobi change from frame 4 to frame 8?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 1 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 6~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Moscow change from frame 2 to frame 4?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 0 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) −50~0 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 5 to frame 19?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) –50~0 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 10 to frame 21?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 2 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Auckland change from frame 2 to frame 6?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~-50 hPa", + "(C) -50~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 2 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-30~-25 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -45~-40 mm", + "(D) -30~-25 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at New York change from frame 1 to frame 5?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) −100~0 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 5 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 3 to frame 6?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -200~-100 hPa", + "(C) 0~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 2 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Tokyo change from frame 6 to frame 12?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 3 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 0 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 7 to frame 8?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 1 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 0 to frame 8?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~150 hPa", + "(B) 0~100 hPa", + "(C) 150~200 hPa", + "(D) -50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 1 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at London change from frame 4 to frame 6?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -100~0 hPa", + "(C) 100~200 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 0 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Auckland change from frame 10 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 8 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 mm", + "Answer Choices": [ + "(A) -25~-20 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) -15~-10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 2 to frame 4?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 1 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at New York change from frame 5 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 16 to frame 20?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 6 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 7 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 4 to frame 13?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 1 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Nairobi change from frame 1 to frame 7?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) 100~200 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 3 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~2 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 0 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 1 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Kinshasa change from frame 3 to frame 5?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 2 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 5 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 2 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "95~100 %", + "Answer Choices": [ + "(A) 80~85 %", + "(B) 70~75 %", + "(C) 95~100 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 4 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 0 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 6~10 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Ulaanbaatar change from frame 7 to frame 13?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-90~-85 %", + "Answer Choices": [ + "(A) -90~-85 %", + "(B) -70~-65 %", + "(C) -95~-90 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Tokyo change from frame 5 to frame 13?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_015.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) -5~0 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 13 to frame 15?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -15~-10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 1 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Athens change from frame 0 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) 30~35 %", + "(C) 20~25 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Moscow change from frame 1 to frame 2?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 5~10 m³/m³", + "(C) -5~0 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 1 to frame 2?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 0 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 2 to frame 11?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-65~-60 %", + "Answer Choices": [ + "(A) -10~-5 %", + "(B) -40~-35 %", + "(C) -65~-60 %", + "(D) -75~-70 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Wellington change from frame 5 to frame 11?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Wellington change from frame 1 to frame 6?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 10 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 0 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at London change from frame 1 to frame 5?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) -5~0 m³/m³", + "(C) 5~10 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 3 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 5 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 2 to frame 3?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-30~-25 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) -45~-40 %", + "(C) -10~-5 %", + "(D) -20~-15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Wellington change from frame 0 to frame 1?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) −5~0 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 2 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 1 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 3 to frame 6?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 %", + "Answer Choices": [ + "(A) -5~0 %", + "(B) 0~5 %", + "(C) -10~-5 %", + "(D) -20~-15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Auckland change from frame 4 to frame 6?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 0~5 m³/m³", + "(C) 5~10 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 2 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 13 to frame 24?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Ulaanbaatar change from frame 3 to frame 25?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) 0~5 %", + "(C) 10~15 %", + "(D) 15~20 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Ulaanbaatar change from frame 2 to frame 15?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) -5~0 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 16 to frame 23?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 5 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Kinshasa change from frame 0 to frame 2?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) -10~-5 %", + "(B) 5~10 %", + "(C) 0~5 %", + "(D) -5~0 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 0 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Madrid change from frame 4 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "15~20 %", + "Answer Choices": [ + "(A) 35~40 %", + "(B) 15~20 %", + "(C) 5~10 %", + "(D) 25~30 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-229", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 1 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-230", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 11 to frame 13?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-231", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at London change from frame 10 to frame 15?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) -5~0 m³/m³", + "(C) -10~-5 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-232", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 9 to frame 20?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-233", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 16 to frame 21?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_037.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -20~-15 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-234", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 8 to frame 11?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_037.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "30~35 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 20~25 %", + "(C) 30~35 %", + "(D) 40~45 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-235", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Tokyo change from frame 23 to frame 27?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-236", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Ulaanbaatar change from frame 6 to frame 17?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_037.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) -5~0 m³/m³", + "(C) 0~5 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-237", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 3 to frame 17?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_037.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-238", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-239", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 15 to frame 24?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_030.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 60~65 %", + "(B) 80~85 %", + "(C) 100~105 %", + "(D) 45~50 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-240", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Sydney change from frame 6 to frame 28?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 0~5 m³/m³", + "(C) -5~0 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-241", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 16 to frame 30?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_030.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-242", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 4 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-243", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mexico City change from frame 2 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_014.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 0~5 %", + "(C) 30~35 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-244", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 3 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_014.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-245", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 17 to frame 23?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-246", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Madrid change from frame 15 to frame 20?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "25~30 %", + "Answer Choices": [ + "(A) 25~30 %", + "(B) 50~55 %", + "(C) 35~40 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-247", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Athens change from frame 6 to frame 10?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-248", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 5 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 mm", + "Answer Choices": [ + "(A) -15~-10 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-249", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Tokyo change from frame 2 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "75~80 %", + "Answer Choices": [ + "(A) 50~55 %", + "(B) 75~80 %", + "(C) 60~65 %", + "(D) 85~90 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-250", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Tokyo change from frame 1 to frame 11?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 10~15 m³/m³", + "(B) 5~10 m³/m³", + "(C) 15~20 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-251", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 1 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-252", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 0 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 11~15 mm", + "(B) 16~20 mm", + "(C) 6~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-253", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Auckland change from frame 0 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 10~15 %", + "(C) 5~10 %", + "(D) 15~20 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-254", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Auckland change from frame 3 to frame 7?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -5~0 m³/m³", + "(B) -10~-5 m³/m³", + "(C) 0~5 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-255", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 2 to frame 5?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-256", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-257", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at New York change from frame 5 to frame 6?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 10~15 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-258", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 1 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-259", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 7 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-260", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Auckland change from frame 2 to frame 3?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "35~40 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 20~25 %", + "(C) 35~40 %", + "(D) 45~50 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-261", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Auckland change from frame 1 to frame 2?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) -10~-5 m³/m³", + "(C) 5~10 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-262", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 5 to frame 13?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-263", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 8 to frame 22?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 2~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-264", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Madrid change from frame 9 to frame 24?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 0~5 %", + "(C) 15~20 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-265", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Moscow change from frame 4 to frame 9?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 10~15 m³/m³", + "(C) 5~10 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-266", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 2 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) -2~3 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-267", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 0 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-268", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mexico City change from frame 2 to frame 4?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-55~-50 %", + "Answer Choices": [ + "(A) -10~-5 %", + "(B) -30~-25 %", + "(C) -70~-65 %", + "(D) -55~-50 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-269", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Mexico City change from frame 4 to frame 5?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) 5~10 m³/m³", + "(C) 0~5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-270", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 3 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-271", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 3 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-272", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Athens change from frame 0 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-20~-15 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) 0~5 %", + "(C) -20~-15 %", + "(D) -10~-5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-273", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Madrid change from frame 4 to frame 5?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) -5~0 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-274", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at London change from frame 5 to frame 6?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-60~-55 %", + "Answer Choices": [ + "(A) -60~-55 %", + "(B) -40~-35 %", + "(C) -20~-15 %", + "(D) -70~-65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-275", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at London change from frame 3 to frame 12?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) -10~-5 m³/m³", + "(C) 0~5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-276", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 16 to frame 19?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -2~2 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-277", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 8 to frame 20?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-278", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Tokyo change from frame 15 to frame 21?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-95~-90 %", + "Answer Choices": [ + "(A) -70~-65 %", + "(B) -95~-90 %", + "(C) -85~-80 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-279", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Beijing change from frame 22 to frame 24?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) -10~-5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-280", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 4 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-281", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Cairo change from frame 0 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~-95 %", + "Answer Choices": [ + "(A) -80~-75 %", + "(B) -60~-55 %", + "(C) -30~-25 %", + "(D) -100~-95 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-282", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Cairo change from frame 4 to frame 9?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) -5~0 m³/m³", + "(C) 10~15 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-283", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 5 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-284", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 6 to frame 17?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-285", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Wellington change from frame 4 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-45~-40 %", + "Answer Choices": [ + "(A) -10~-5 %", + "(B) -45~-40 %", + "(C) -60~-55 %", + "(D) -30~-25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-286", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Wellington change from frame 0 to frame 10?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -2~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-287", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Wellington change from frame 2 to frame 12?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) -5~0 m³/m³", + "(D) 10~15 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-288", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 13 to frame 18?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-289", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Mexico City change from frame 13 to frame 17?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -10~-5 m³/m³", + "(B) -5~0 m³/m³", + "(C) 5~10 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-290", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 0 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 16~20 mm", + "(D) 11~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-291", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mumbai change from frame 2 to frame 4?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 0~5 %", + "(C) 20~25 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-292", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Tokyo change from frame 2 to frame 4?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) -5~0 m³/m³", + "(C) 10~15 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-293", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 9 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-294", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 1 to frame 2?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-295", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Moscow change from frame 0 to frame 2?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~-95 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) -80~-75 %", + "(C) -100~-95 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-296", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Moscow change from frame 4 to frame 5?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) -10~-5 m³/m³", + "(C) -5~0 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-297", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 0 to frame 18?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~2 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-298", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 21 to frame 36?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-80~-75 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) -90~-85 %", + "(C) -60~-55 %", + "(D) -80~-75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-299", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Beijing change from frame 17 to frame 18?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -5~0 m³/m³", + "(B) 0~5 m³/m³", + "(C) -10~-5 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-300", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 13 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -20~-15 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-301", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 23 to frame 35?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-302", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Cairo change from frame 5 to frame 33?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_037.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 30~35 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-303", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 20 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-304", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Lima change from frame 3 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-305", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Lima change from frame 5 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_018.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 %", + "Answer Choices": [ + "(A) 15~20 %", + "(B) 10~15 %", + "(C) 5~10 %", + "(D) 0~5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-306", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 2 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-307", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 2 to frame 3?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) 15~20 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-308", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Auckland change from frame 1 to frame 3?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) 5~10 m³/m³", + "(C) -10~-5 m³/m³", + "(D) -5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-309", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 0 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-310", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at London change from frame 0 to frame 9?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-55~-50 %", + "Answer Choices": [ + "(A) -55~-50 %", + "(B) -70~-65 %", + "(C) -10~-5 %", + "(D) -30~-25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-311", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 1 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-312", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 2 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-313", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Ulaanbaatar change from frame 15 to frame 22?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 5~10 %", + "(C) -20~-15 %", + "(D) -10~-5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-314", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Mumbai change from frame 9 to frame 13?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-315", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Tokyo change from frame 11 to frame 19?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) 0~5 m³/m³", + "(B) -5~0 m³/m³", + "(C) 5~10 m³/m³", + "(D) -10~-5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-316", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 3 to frame 23?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-317", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 6 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-318", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 0 to frame 4?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 20~25 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-319", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Mexico City change from frame 0 to frame 7?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -5~0 m³/m³", + "(B) -10~-5 m³/m³", + "(C) 5~10 m³/m³", + "(D) 0~5 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-320", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 2 to frame 9?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-321", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Lima change from frame 0 to frame 4?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "50~55 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 50~55 %", + "(C) 60~65 %", + "(D) 40~45 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-322", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 5 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-323", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 10 to frame 14?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) 0~5 %", + "(C) -10~-5 %", + "(D) -5~0 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-324", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Wellington change from frame 1 to frame 16?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-325", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Sydney change from frame 13 to frame 14?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 m³/m³", + "Answer Choices": [ + "(A) 5~10 m³/m³", + "(B) 0~5 m³/m³", + "(C) 10~15 m³/m³", + "(D) −5~0 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-326", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 9 to frame 18?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-327", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-328", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Moscow change from frame 1 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 %", + "Answer Choices": [ + "(A) -20~-15 %", + "(B) -10~-5 %", + "(C) 5~10 %", + "(D) 0~5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-329", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 2 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-330", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 13 to frame 15?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-331", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 3 to frame 10?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) -10~-5 %", + "(B) 0~5 %", + "(C) 5~10 %", + "(D) -5~0 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-332", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of sst at Mumbai change from frame 0 to frame 1?", + "Variable": "sst", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -2~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-333", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of swvl1 at Mumbai change from frame 5 to frame 14?", + "Variable": "swvl1", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 m³/m³", + "Answer Choices": [ + "(A) -5~0 m³/m³", + "(B) -10~-5 m³/m³", + "(C) 0~5 m³/m³", + "(D) 5~10 m³/m³", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-334", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 11 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-335", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 18 to frame 42?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) −5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-336", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 22 to frame 26?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-337", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at New York change from frame 16 to frame 26?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) -5~0 W/m²", + "(B) -25~-20 W/m²", + "(C) -15~-10 W/m²", + "(D) 0~5 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-338", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 3 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-339", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Auckland change from frame 4 to frame 30?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-340", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 5 to frame 31?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-341", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Wellington change from frame 20 to frame 33?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "30~35 W/m²", + "Answer Choices": [ + "(A) 20~25 W/m²", + "(B) 40~45 W/m²", + "(C) 30~35 W/m²", + "(D) 10~15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-342", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 15 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-343", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 1 to frame 35?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-344", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 33 to frame 37?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-345", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mexico City change from frame 9 to frame 15?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-346", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 17 to frame 25?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-347", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Toronto change from frame 35 to frame 40?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "65~70 W/m²", + "Answer Choices": [ + "(A) 65~70 W/m²", + "(B) 80~85 W/m²", + "(C) 30~35 W/m²", + "(D) 50~55 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-348", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 20 to frame 41?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-349", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 24 to frame 35?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-350", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 26 to frame 36?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-351", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Mumbai change from frame 24 to frame 29?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-20~-15 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -10~-5 W/m²", + "(C) -30~-25 W/m²", + "(D) -20~-15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-352", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 0 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-353", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Nairobi change from frame 20 to frame 25?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-354", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 21 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-355", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Cairo change from frame 16 to frame 38?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-356", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Kinshasa change from frame 1 to frame 36?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "35~40 W/m²", + "Answer Choices": [ + "(A) 45~50 W/m²", + "(B) 35~40 W/m²", + "(C) 15~20 W/m²", + "(D) 25~30 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-357", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 9 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-358", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 25 to frame 31?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-359", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 19 to frame 33?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-360", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Auckland change from frame 7 to frame 15?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 W/m²", + "Answer Choices": [ + "(A) 18~23 W/m²", + "(B) 12~17 W/m²", + "(C) 0~4 W/m²", + "(D) 5~10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-361", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 4 to frame 29?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-362", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 4 to frame 16?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-363", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at London change from frame 21 to frame 36?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "20~25 W/m²", + "Answer Choices": [ + "(A) 30~35 W/m²", + "(B) 10~15 W/m²", + "(C) 20~25 W/m²", + "(D) 5~10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-364", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at New York change from frame 7 to frame 14?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) -2~3 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-365", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 12 to frame 17?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-366", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 37 to frame 42?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-367", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Ulaanbaatar change from frame 14 to frame 28?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-368", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 24 to frame 36?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-369", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Mumbai change from frame 3 to frame 10?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-30~-25 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -10~-5 W/m²", + "(C) -30~-25 W/m²", + "(D) -45~-40 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-370", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 16 to frame 35?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-371", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 7 to frame 35?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-372", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 7 to frame 22?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-373", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at New York change from frame 22 to frame 26?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-60~-55 W/m²", + "Answer Choices": [ + "(A) -60~-55 W/m²", + "(B) -75~-70 W/m²", + "(C) -10~-5 W/m²", + "(D) -30~-25 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-374", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 6 to frame 42?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-375", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 1 to frame 24?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) −5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-376", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 28 to frame 41?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-377", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Ulaanbaatar change from frame 24 to frame 38?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-20~-15 W/m²", + "Answer Choices": [ + "(A) -10~-5 W/m²", + "(B) -20~-15 W/m²", + "(C) -30~-25 W/m²", + "(D) 0~5 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-378", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 21 to frame 34?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -2~3 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-379", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Madrid change from frame 3 to frame 5?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) -2~3 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-380", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 18 to frame 31?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-381", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 9 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-382", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Auckland change from frame 10 to frame 26?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-383", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 0 to frame 26?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-384", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Wellington change from frame 6 to frame 7?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-110~-105 W/m²", + "Answer Choices": [ + "(A) -130~-125 W/m²", + "(B) -110~-105 W/m²", + "(C) -80~-75 W/m²", + "(D) -95~-90 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-385", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Nairobi change from frame 5 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -2~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-386", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Cairo change from frame 33 to frame 34?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-387", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 22 to frame 23?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-388", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Madrid change from frame 14 to frame 38?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-389", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Madrid change from frame 20 to frame 35?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "20~25 W/m²", + "Answer Choices": [ + "(A) 5~10 W/m²", + "(B) 10~15 W/m²", + "(C) 20~25 W/m²", + "(D) 30~35 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-390", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 0 to frame 19?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -3~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-391", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 5 to frame 20?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-392", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at São Paulo change from frame 21 to frame 22?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-393", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at São Paulo change from frame 24 to frame 25?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-394", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 3 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_030.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-395", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 22 to frame 23?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-396", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 9 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-397", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Tokyo change from frame 23 to frame 28?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_030.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "45~50 W/m²", + "Answer Choices": [ + "(A) 20~25 W/m²", + "(B) 30~35 W/m²", + "(C) 45~50 W/m²", + "(D) 55~60 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-398", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 11 to frame 26?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-399", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Nairobi change from frame 6 to frame 40?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 W/m²", + "Answer Choices": [ + "(A) 10~15 W/m²", + "(B) 30~35 W/m²", + "(C) 0~5 W/m²", + "(D) 20~25 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-400", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 9 to frame 17?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-401", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 2 to frame 4?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-402", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 7 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-403", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Sydney change from frame 9 to frame 12?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-30~-25 W/m²", + "Answer Choices": [ + "(A) -30~-25 W/m²", + "(B) -10~-5 W/m²", + "(C) -45~-40 W/m²", + "(D) 0~5 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-404", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Cairo change from frame 7 to frame 35?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-405", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 16 to frame 39?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-406", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 2 to frame 40?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~2 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-407", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Athens change from frame 4 to frame 19?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-35~-30 W/m²", + "Answer Choices": [ + "(A) -20~-15 W/m²", + "(B) -35~-30 W/m²", + "(C) 0~5 W/m²", + "(D) -45~-40 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-408", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 4 to frame 41?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-409", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 11 to frame 28?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-410", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 0 to frame 28?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-411", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Ulaanbaatar change from frame 17 to frame 42?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-25~-20 W/m²", + "Answer Choices": [ + "(A) -15~-10 W/m²", + "(B) -35~-30 W/m²", + "(C) -5~0 W/m²", + "(D) -25~-20 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-412", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 9 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-413", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 0 to frame 27?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-414", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Toronto change from frame 6 to frame 15?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-80~-75 W/m²", + "Answer Choices": [ + "(A) -100~-95 W/m²", + "(B) -40~-35 W/m²", + "(C) -60~-55 W/m²", + "(D) -80~-75 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-415", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 3 to frame 22?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~2 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-416", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 26 to frame 37?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-417", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Toronto change from frame 24 to frame 28?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-25~-20 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -25~-20 W/m²", + "(C) -35~-30 W/m²", + "(D) -10~-5 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-418", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 5 to frame 37?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-419", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 24 to frame 40?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-420", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 6 to frame 21?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-421", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Sydney change from frame 3 to frame 19?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) -25~-20 W/m²", + "(B) 0~5 W/m²", + "(C) -15~-10 W/m²", + "(D) -5~0 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-422", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 8 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-423", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 22 to frame 30?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-424", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 2 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-425", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Beijing change from frame 3 to frame 21?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "100~105 W/m²", + "Answer Choices": [ + "(A) 100~105 W/m²", + "(B) 85~90 W/m²", + "(C) 110~115 W/m²", + "(D) 70~75 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-426", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 0 to frame 15?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -15~-10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-427", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Ulaanbaatar change from frame 6 to frame 15?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-428", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 8 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-429", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Tokyo change from frame 5 to frame 16?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) 5~10 W/m²", + "(C) 15~20 W/m²", + "(D) 10~15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-430", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 1 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-431", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 7 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-432", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Lima change from frame 6 to frame 30?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-433", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Lima change from frame 6 to frame 26?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-434", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Lima change from frame 7 to frame 38?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-65~-60 W/m²", + "Answer Choices": [ + "(A) -65~-60 W/m²", + "(B) -50~-45 W/m²", + "(C) -80~-75 W/m²", + "(D) -30~-25 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-435", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 39 to frame 40?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-436", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 32 to frame 37?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-437", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 14 to frame 37?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-438", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Sydney change from frame 3 to frame 9?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-90~-85 W/m²", + "Answer Choices": [ + "(A) -90~-85 W/m²", + "(B) -60~-55 W/m²", + "(C) -100~-95 W/m²", + "(D) -70~-65 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-439", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 2 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-440", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Madrid change from frame 0 to frame 6?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -2~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-441", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 6 to frame 10?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-442", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Moscow change from frame 8 to frame 9?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) -5~0 W/m²", + "(B) 0~5 W/m²", + "(C) -25~-20 W/m²", + "(D) -15~-10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-443", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 5 to frame 25?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-444", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at London change from frame 24 to frame 26?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~2 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-445", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 3 to frame 25?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-446", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 31 to frame 37?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -20~-15 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-447", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at New York change from frame 20 to frame 27?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-448", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 2 to frame 29?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-449", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Toronto change from frame 19 to frame 38?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "20~25 W/m²", + "Answer Choices": [ + "(A) 20~25 W/m²", + "(B) 30~35 W/m²", + "(C) 5~10 W/m²", + "(D) 10~15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-450", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 14 to frame 23?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-451", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 20 to frame 21?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-452", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 9 to frame 24?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-453", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Tokyo change from frame 21 to frame 27?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 W/m²", + "Answer Choices": [ + "(A) -10~-5 W/m²", + "(B) -5~0 W/m²", + "(C) -20~-15 W/m²", + "(D) 0~5 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-454", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 4 to frame 25?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-455", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 5 to frame 23?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-456", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 1 to frame 15?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-457", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 17 to frame 22?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-458", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 6 to frame 20?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-459", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Wellington change from frame 18 to frame 28?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-460", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 11 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-461", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Auckland change from frame 7 to frame 11?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_030.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~-95 W/m²", + "Answer Choices": [ + "(A) -85~-80 W/m²", + "(B) -100~-95 W/m²", + "(C) -110~-105 W/m²", + "(D) -70~-65 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-462", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 15 to frame 21?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-463", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Beijing change from frame 29 to frame 33?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-464", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 23 to frame 37?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) -10~-5 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-465", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Mumbai change from frame 6 to frame 42?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -25~-20 W/m²", + "(C) -5~0 W/m²", + "(D) -15~-10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-466", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 5 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-467", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 28 to frame 40?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-468", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 26 to frame 38?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-469", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Sydney change from frame 5 to frame 30?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-70~-65 W/m²", + "Answer Choices": [ + "(A) -80~-75 W/m²", + "(B) -50~-45 W/m²", + "(C) -70~-65 W/m²", + "(D) -60~-55 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-470", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 9 to frame 20?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-471", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Madrid change from frame 21 to frame 31?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-472", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 26 to frame 41?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_042.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-473", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Madrid change from frame 7 to frame 38?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 W/m²", + "Answer Choices": [ + "(A) 20~25 W/m²", + "(B) 0~5 W/m²", + "(C) −5~0 W/m²", + "(D) 10~15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-474", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Nairobi change from frame 35 to frame 42?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_042.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-475", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 4 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-476", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 6 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-477", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at New York change from frame 4 to frame 6?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "15~20 W/m²", + "Answer Choices": [ + "(A) 15~20 W/m²", + "(B) 0~5 W/m²", + "(C) 5~10 W/m²", + "(D) 25~30 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-478", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Kinshasa change from frame 16 to frame 37?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-479", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 22 to frame 39?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_042.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-480", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Cairo change from frame 9 to frame 31?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_038.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_039.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_041.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_042.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "20~25 W/m²", + "Answer Choices": [ + "(A) 5~10 W/m²", + "(B) 10~15 W/m²", + "(C) 30~35 W/m²", + "(D) 20~25 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-481", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 26 to frame 42?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_000.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-482", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 16 to frame 29?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_000.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-6 °C", + "(B) 1~6 °C", + "(C) 6~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-483", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 7 to frame 36?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_000.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-484", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Auckland change from frame 14 to frame 27?", + "Variable": "mtnlwrf", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_000.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "110~115 W/m²", + "Answer Choices": [ + "(A) 90~95 W/m²", + "(B) 120~125 W/m²", + "(C) 100~105 W/m²", + "(D) 110~115 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-485", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 15 to frame 17?", + "Variable": "t2m", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -20~-15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-486", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Mumbai change from frame 25 to frame 38?", + "Variable": "skt", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-487", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 27 to frame 31?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-488", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Beijing change from frame 10 to frame 12?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) 15~20 W/m²", + "(C) 5~10 W/m²", + "(D) 10~15 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-489", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mexico City change from frame 7 to frame 22?", + "Variable": "t2m", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-490", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Toronto change from frame 1 to frame 14?", + "Variable": "skt", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-491", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 20 to frame 42?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-492", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Mexico City change from frame 0 to frame 13?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) -5~0 W/m²", + "(B) 0~5 W/m²", + "(C) -25~-20 W/m²", + "(D) -15~-10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-493", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Nairobi change from frame 8 to frame 15?", + "Variable": "skt", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) -2~3 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-494", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 21 to frame 37?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-495", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Athens change from frame 1 to frame 3?", + "Variable": "skt", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-496", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 12 to frame 42?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-497", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Moscow change from frame 0 to frame 35?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -10~-5 W/m²", + "(C) 5~10 W/m²", + "(D) -5~0 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-498", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 16 to frame 28?", + "Variable": "t2m", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-499", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Tokyo change from frame 6 to frame 39?", + "Variable": "skt", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -2~3 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-500", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 0 to frame 21?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~2 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-501", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Beijing change from frame 16 to frame 33?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -25~-20 W/m²", + "(C) -5~0 W/m²", + "(D) -15~-10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-502", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at London change from frame 19 to frame 33?", + "Variable": "t2m", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-503", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 31 to frame 34?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-504", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Lima change from frame 14 to frame 35?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-505", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at São Paulo change from frame 22 to frame 42?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 W/m²", + "Answer Choices": [ + "(A) -5~0 W/m²", + "(B) -10~-5 W/m²", + "(C) 0~5 W/m²", + "(D) 5~10 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-506", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Cairo change from frame 20 to frame 41?", + "Variable": "skt", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-507", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 3 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-508", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Nairobi change from frame 3 to frame 13?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 W/m²", + "Answer Choices": [ + "(A) 0~5 W/m²", + "(B) -25~-20 W/m²", + "(C) -15~-10 W/m²", + "(D) -5~0 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-509", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 9 to frame 26?", + "Variable": "t2m", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) −5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-510", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of skt at Sydney change from frame 24 to frame 35?", + "Variable": "skt", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-511", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 12 to frame 31?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-512", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of mtnlwrf at Sydney change from frame 11 to frame 40?", + "Variable": "mtnlwrf", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-50~-45 W/m²", + "Answer Choices": [ + "(A) -50~-45 W/m²", + "(B) -65~-60 W/m²", + "(C) -10~-5 W/m²", + "(D) -30~-25 W/m²", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-513", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 0 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-514", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Madrid change from frame 4 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 10~15 %", + "(C) 0~5 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-515", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 0 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-516", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 4 to frame 5?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-517", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 0 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -2~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-518", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Wellington change from frame 4 to frame 10?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "80~85 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 90~95 %", + "(C) 80~85 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-519", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 4 to frame 6?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 10~15 %", + "(C) 0~5 %", + "(D) 30~35 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-520", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 3 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) -2~3 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-521", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Cairo change from frame 2 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "20~25 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 5~10 %", + "(C) 30~35 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-522", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 8 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-523", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 8 to frame 13?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-524", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 4 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 20~25 %", + "(C) 5~10 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-525", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Athens change from frame 0 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -2~2 °C", + "(C) 0~5 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-526", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 3 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-527", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Nairobi change from frame 7 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~2 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-528", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 0 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-529", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 9 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-530", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Auckland change from frame 0 to frame 13?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-95~-90 %", + "Answer Choices": [ + "(A) -80~-75 %", + "(B) -95~-90 %", + "(C) -70~-65 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-531", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 9 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-532", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Toronto change from frame 0 to frame 13?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "45~50 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 55~60 %", + "(C) 45~50 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-533", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 3 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-534", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 3 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-535", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Tokyo change from frame 4 to frame 9?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "90~95 %", + "Answer Choices": [ + "(A) 90~95 %", + "(B) 40~45 %", + "(C) 75~80 %", + "(D) 60~65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-536", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 7 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-537", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mexico City change from frame 7 to frame 10?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "35~40 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 25~30 %", + "(C) 45~50 %", + "(D) 35~40 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-538", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 8 to frame 21?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-539", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 0 to frame 4?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "100~105 %", + "Answer Choices": [ + "(A) 70~75 %", + "(B) 85~90 %", + "(C) 60~65 %", + "(D) 100~105 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-540", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 13 to frame 20?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-541", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Tokyo change from frame 4 to frame 17?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -2~3 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-542", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 14 to frame 17?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 5~10 %", + "(C) -10~-5 %", + "(D) -5~0 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-543", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Nairobi change from frame 4 to frame 11?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-544", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 6 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-545", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Wellington change from frame 0 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-546", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Wellington change from frame 4 to frame 10?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 %", + "Answer Choices": [ + "(A) -25~-20 %", + "(B) 0~5 %", + "(C) -15~-10 %", + "(D) -5~0 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-547", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 2 to frame 21?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-548", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Beijing change from frame 5 to frame 17?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-549", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mumbai change from frame 13 to frame 19?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-80~-75 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) -90~-85 %", + "(C) -80~-75 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-550", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 0 to frame 25?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-551", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 23 to frame 24?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-552", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 7 to frame 12?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -20~-15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-553", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 3 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-554", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 4 to frame 13?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-25~-20 %", + "Answer Choices": [ + "(A) -35~-30 %", + "(B) 0~5 %", + "(C) -10~-5 %", + "(D) -25~-20 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-555", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 1 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 15~20 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-556", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mexico City change from frame 0 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-40~-35 %", + "Answer Choices": [ + "(A) -50~-45 %", + "(B) -40~-35 %", + "(C) -10~-5 %", + "(D) -25~-20 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-557", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 5 to frame 13?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 16~20 mm", + "(B) 0~5 mm", + "(C) 11~15 mm", + "(D) 6~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-558", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Madrid change from frame 4 to frame 14?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-559", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Madrid change from frame 9 to frame 11?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "15~20 %", + "Answer Choices": [ + "(A) 25~30 %", + "(B) 5~10 %", + "(C) 35~40 %", + "(D) 15~20 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-560", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 8 to frame 11?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-561", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 4 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-562", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Auckland change from frame 3 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 %", + "Answer Choices": [ + "(A) 10~15 %", + "(B) 15~20 %", + "(C) 0~5 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-563", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Tokyo change from frame 2 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -10~-5 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-564", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 5 to frame 7?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-565", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Tokyo change from frame 2 to frame 11?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) 15~20 %", + "(C) 0~5 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-566", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-567", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Cairo change from frame 5 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 20~25 %", + "(C) 30~35 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-568", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 1 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-569", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Auckland change from frame 5 to frame 6?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-570", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 2 to frame 3?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "30~35 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 30~35 %", + "(C) 10~15 %", + "(D) 40~45 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-571", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 2 to frame 8?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-572", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at New York change from frame 0 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-573", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Toronto change from frame 3 to frame 6?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) 5~10 %", + "(B) -5~0 %", + "(C) 0~5 %", + "(D) -10~-5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-574", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Cairo change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-575", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 3 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-576", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Kinshasa change from frame 5 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) 5~10 %", + "(C) -20~-15 %", + "(D) -10~-5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-577", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 6 to frame 9?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-578", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Mumbai change from frame 4 to frame 13?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-579", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 4 to frame 8?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~-95 %", + "Answer Choices": [ + "(A) -85~-80 %", + "(B) -100~-95 %", + "(C) -70~-65 %", + "(D) -60~-55 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-580", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Moscow change from frame 5 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 20~25 %", + "(B) 0~5 %", + "(C) 5~10 %", + "(D) 10~15 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-581", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Cairo change from frame 2 to frame 12?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-582", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Nairobi change from frame 5 to frame 7?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-45~-40 %", + "Answer Choices": [ + "(A) -30~-25 %", + "(B) -60~-55 %", + "(C) -45~-40 %", + "(D) -10~-5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-583", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 2 to frame 23?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-584", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Moscow change from frame 13 to frame 22?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-585", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 0 to frame 3?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-586", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 0 to frame 3?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-587", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at New York change from frame 0 to frame 6?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 30~35 %", + "(B) 0~5 %", + "(C) 10~15 %", + "(D) 20~25 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-588", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 5 to frame 17?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-589", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Beijing change from frame 0 to frame 1?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-590", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Beijing change from frame 2 to frame 11?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_017.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~-95 %", + "Answer Choices": [ + "(A) -80~-75 %", + "(B) -100~-95 %", + "(C) -90~-85 %", + "(D) -70~-65 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-591", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 8 to frame 13?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-592", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 0 to frame 10?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) -2~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-593", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Sydney change from frame 2 to frame 9?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) -5~0 %", + "(C) -10~-5 %", + "(D) 5~10 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-594", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Kinshasa change from frame 5 to frame 9?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-595", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 0 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-596", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Ulaanbaatar change from frame 2 to frame 4?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-597", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Mumbai change from frame 3 to frame 5?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_007.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 %", + "Answer Choices": [ + "(A) 15~20 %", + "(B) 10~15 %", + "(C) 5~10 %", + "(D) 0~5 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-598", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 11 to frame 16?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-599", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Toronto change from frame 6 to frame 15?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -20~-15 °C", + "(B) -5~0 °C", + "(C) -15~-10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-600", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Toronto change from frame 15 to frame 19?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-65~-60 %", + "Answer Choices": [ + "(A) -40~-35 %", + "(B) -10~-5 %", + "(C) -65~-60 %", + "(D) -80~-75 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-601", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 2 to frame 4?", + "Variable": "tp6h", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-602", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of t2m at Sydney change from frame 2 to frame 8?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-603", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tcc at Auckland change from frame 9 to frame 12?", + "Variable": "tcc", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-35~-30 %", + "Answer Choices": [ + "(A) 0~5 %", + "(B) -50~-45 %", + "(C) -10~-5 %", + "(D) -35~-30 %", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-604", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 0 to frame 14?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-605", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 6 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 0~5 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-606", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 5 to frame 8?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-607", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 3 to frame 11?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-608", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Tokyo change from frame 6 to frame 8?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-609", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 4 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-610", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at New York change from frame 0 to frame 7?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-611", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Ulaanbaatar change from frame 0 to frame 12?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) -100~-50 hPa", + "(B) -50~0 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-612", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 4 to frame 10?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -5~0 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-613", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 5 to frame 12?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 0~100 hPa", + "(C) -200~-100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-614", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 0 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-615", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 1 to frame 5?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) 5~10 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-616", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Madrid change from frame 5 to frame 8?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-617", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Athens change from frame 6 to frame 8?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-618", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Nairobi change from frame 2 to frame 10?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) −100~0 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-619", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 3 to frame 9?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) −100~0 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-620", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Sydney change from frame 4 to frame 8?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-621", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at New York change from frame 1 to frame 6?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 100~200 hPa", + "(C) -200~-100 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-622", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 5 to frame 11?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) -10~-5 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-623", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 3 to frame 5?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-624", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 2 to frame 6?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-625", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Cairo change from frame 1 to frame 15?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) -50~0 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-626", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Nairobi change from frame 0 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-627", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Auckland change from frame 5 to frame 7?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) −50~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-628", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 0 to frame 5?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) -5~0 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-629", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Tokyo change from frame 5 to frame 7?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-630", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 0 to frame 2?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-631", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 3 to frame 7?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 0~50 hPa", + "(D) 50~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-632", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 4 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-633", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Toronto change from frame 7 to frame 10?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) −100~0 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-634", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 5 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-635", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Auckland change from frame 6 to frame 19?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) 0~50 hPa", + "(C) -200~-100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-636", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 1 to frame 15?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 10~15 mm", + "(C) 0~5 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-637", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 1 to frame 3?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-638", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 3 to frame 5?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-639", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 3 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 10~15 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-640", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 4 to frame 11?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~-50 hPa", + "(C) -50~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-641", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 7 to frame 11?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 6~10 mm", + "(B) 11~15 mm", + "(C) 0~5 mm", + "(D) 16~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-642", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 1 to frame 2?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 15~20 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-643", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 6 to frame 12?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-644", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 1 to frame 8?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 150~200 hPa", + "(B) 100~150 hPa", + "(C) 200~300 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-645", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 3 to frame 4?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-646", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 3 to frame 19?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) −100~0 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-647", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Ulaanbaatar change from frame 0 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) -10~-5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-648", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 3 to frame 5?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) −100~0 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-649", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 2 to frame 3?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 0~5 mm", + "(C) 10~15 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-650", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Athens change from frame 1 to frame 3?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -100~0 hPa", + "(C) -200~-100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-651", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Moscow change from frame 0 to frame 3?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-652", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 4 to frame 17?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-653", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Auckland change from frame 12 to frame 14?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) 15~20 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-654", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Toronto change from frame 11 to frame 15?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-655", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Toronto change from frame 0 to frame 12?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 15~20 mm", + "(C) 5~10 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-656", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at São Paulo change from frame 1 to frame 7?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-657", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at São Paulo change from frame 3 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 5~10 mm", + "(C) -5~0 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-658", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at London change from frame 6 to frame 12?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -200~-100 hPa", + "(C) 100~200 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-659", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Cairo change from frame 14 to frame 16?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~0 hPa", + "(C) -200~-100 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-660", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Sydney change from frame 3 to frame 4?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) −100~0 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-661", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 5 to frame 8?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) 0~5 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) -5~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-662", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Beijing change from frame 8 to frame 16?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) -50~0 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-663", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Beijing change from frame 3 to frame 15?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) -10~-5 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-664", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Madrid change from frame 1 to frame 11?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 5~10 mm", + "(C) 10~15 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-665", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mumbai change from frame 8 to frame 9?", + "Variable": "msl", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -200~-100 hPa", + "(C) -100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-666", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mumbai change from frame 4 to frame 6?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 0~5 mm", + "(C) -10~-5 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-667", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Kinshasa change from frame 7 to frame 8?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 15~20 mm", + "(B) 10~15 mm", + "(C) 5~10 mm", + "(D) 0~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-668", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 3 to frame 4?", + "Variable": "msl", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~0 hPa", + "(C) -200~-100 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-669", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at New York change from frame 0 to frame 7?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 mm", + "Answer Choices": [ + "(A) 2~5 mm", + "(B) 10~15 mm", + "(C) 20~25 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-670", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Athens change from frame 6 to frame 12?", + "Variable": "msl", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) 0~50 hPa", + "(C) -200~-100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-671", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at London change from frame 1 to frame 15?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -10~-5 mm", + "(B) 0~5 mm", + "(C) -5~0 mm", + "(D) 5~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-672", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Mexico City change from frame 6 to frame 9?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) −100~0 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-673", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Mexico City change from frame 7 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 mm", + "Answer Choices": [ + "(A) -5~0 mm", + "(B) 5~10 mm", + "(C) 0~5 mm", + "(D) -10~-5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-674", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of msl at Wellington change from frame 2 to frame 10?", + "Variable": "msl", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Event_trend_analysis-675", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. How does the intensity of tp6h at Wellington change from frame 7 to frame 9?", + "Variable": "tp6h", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 mm", + "Answer Choices": [ + "(A) 5~10 mm", + "(B) 15~20 mm", + "(C) 0~5 mm", + "(D) 10~15 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Geopotential_pattern_identification.json b/jsons/Atmosphere/medium_term/Perception/Geopotential_pattern_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..084cc6afb2c63c80c9c1a12bf7b366bf893fd502 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Geopotential_pattern_identification.json @@ -0,0 +1,1160 @@ +[ + { + "Question_id": "Geopotential pattern identification/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/00_24h/z-500_015.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Front", + "(B) Trough", + "(C) Ridge", + "(D) Jet", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/01_24h/z-500_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Meridional", + "(B) Blocking", + "(C) Zonal", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/02_24h/z-500_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Cut-off low", + "(B) Col", + "(C) Ridge", + "(D) Trough", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/03_24h/z-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Ridge", + "(B) Low", + "(C) Trough", + "(D) Col", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/04_24h/z-500_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Blocked", + "(B) Zonal", + "(C) Meridional", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/05_24h/z-500_011.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Ridge", + "(B) Blocking High", + "(C) Zonal Flow", + "(D) Trough", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/06_24h/z-500_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Trough", + "(B) Zonal flow", + "(C) Blocking high", + "(D) Ridge", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/07_24h/z-500_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Trough", + "(B) Ridge", + "(C) Zonal flow", + "(D) Blocking high", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/08_24h/z-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Col", + "(B) Cut-off Low", + "(C) Ridge", + "(D) Trough", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/09_24h/z-500_010.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Meridional", + "(B) N/A", + "(C) Blocking", + "(D) Zonal", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/10_6h/z-500_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) High pressure ridge", + "(B) Low pressure trough", + "(C) Zonal flow", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/11_24h/z-500_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Omega", + "(B) Blocking", + "(C) N/A", + "(D) Zonal", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/12_24h/z-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Ridge", + "(B) Col", + "(C) Trough", + "(D) Cut-off low", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/13_24h/z-500_014.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Trough", + "(B) Ridge", + "(C) Col", + "(D) Zonal flow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/14_24h/z-500_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Zonal Flow", + "(B) Ridge", + "(C) Trough", + "(D) Cut-off Low", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/15_24h/z-500_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Meridional", + "(B) Zonal", + "(C) Blocked", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/16_24h/z-500_018.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Cut-off Low", + "(B) Trough", + "(C) Col", + "(D) Ridge", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/17_24h/z-500_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Ridge", + "(B) Col", + "(C) Trough", + "(D) Cut-off Low", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/tropical_cyclone/18_24h/z-500_010.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Zonal flow", + "(B) Ridge", + "(C) Trough", + "(D) Blocking high", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/z-500_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Blocking high", + "(B) Zonal flow", + "(C) Trough", + "(D) Ridge", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/z-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) N/A", + "(B) 35", + "(C) 60", + "(D) 45", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/z-500_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Ridge", + "(B) Trough", + "(C) Zonal", + "(D) Blocking", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/z-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) N/A", + "(B) 500", + "(C) 700", + "(D) 850", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/z-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) N/A", + "(B) 46", + "(C) 52", + "(D) 48", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/z-500_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Trough", + "(B) Zonal flow", + "(C) Ridge", + "(D) Col", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/z-500_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Low-pressure trough", + "(B) Zonal flow", + "(C) Ridge pattern", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/z-500_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Col", + "(B) Trough", + "(C) Cut-off Low", + "(D) Ridge", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/z-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Trough", + "(B) Col", + "(C) Closed Low", + "(D) Ridge", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/z-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) N/A", + "(B) 48", + "(C) 42", + "(D) 60", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/z-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) N/A", + "(B) 1000", + "(C) 850", + "(D) 500", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/z-500_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Trough", + "Answer Choices": [ + "(A) Col", + "(B) Ridge", + "(C) Zonal flow", + "(D) Trough", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/z-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "Ridge", + "Answer Choices": [ + "(A) Ridge", + "(B) Zonal Flow", + "(C) Trough", + "(D) Cut-off Low", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geopotential pattern identification/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a MEDIUM_EVENTS event. Temporal resolution of 6 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What is the geopotential pattern of shown status?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/z-500_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Geopotential pattern identification", + "Dataset": "ERA5", + "Answer": "N/A", + "Answer Choices": [ + "(A) Zonal flow", + "(B) Blocking pattern", + "(C) Low pressure system", + "(D) N/A", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/Moisture_flux_analysis.json b/jsons/Atmosphere/medium_term/Perception/Moisture_flux_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..786b195e759a4361e50c4a499f137f61a7eaf5c8 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/Moisture_flux_analysis.json @@ -0,0 +1,11373 @@ +[ + { + "Question_id": "medium_term-Moisture_flux_analysis-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.29e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.29e-3 kg*m/s", + "(B) 0.15e-3 kg*m/s", + "(C) 0.22e-3 kg*m/s", + "(D) 0.35e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v-500_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.55e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.95e-3 kg*m/s", + "(B) 2.55e-3 kg*m/s", + "(C) 2.10e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-850_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.13e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.13e-3 kg*m/s", + "(B) 1.67e-3 kg*m/s", + "(C) 1.85e-3 kg*m/s", + "(D) 2.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v-500_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.79e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.71e-3 kg*m/s", + "(B) 0.92e-3 kg*m/s", + "(C) 0.79e-3 kg*m/s", + "(D) 0.65e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v-500_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.43e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.10e-3 kg*m/s", + "(B) 2.65e-3 kg*m/s", + "(C) 2.43e-3 kg*m/s", + "(D) 1.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.42e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 7.85e-3 kg*m/s", + "(C) 8.97e-3 kg*m/s", + "(D) 8.42e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.56e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.09e-3 kg*m/s", + "(B) 1.72e-3 kg*m/s", + "(C) 1.56e-3 kg*m/s", + "(D) 1.21e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-850_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "35.27e-3 kg*m/s", + "Answer Choices": [ + "(A) 35.27e-3 kg*m/s", + "(B) 39.12e-3 kg*m/s", + "(C) 28.49e-3 kg*m/s", + "(D) 31.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v-500_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.88e-3 kg*m/s", + "(B) 0.65e-3 kg*m/s", + "(C) 0.74e-3 kg*m/s", + "(D) 1.02e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-850_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "17.93e-3 kg*m/s", + "Answer Choices": [ + "(A) 17.93e-3 kg*m/s", + "(B) 13.42e-3 kg*m/s", + "(C) 15.87e-3 kg*m/s", + "(D) 18.65e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v-500_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.30e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.60e-3 kg*m/s", + "(B) 1.85e-3 kg*m/s", + "(C) 2.75e-3 kg*m/s", + "(D) 2.30e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.17e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.17e-3 kg*m/s", + "(B) 9.63e-3 kg*m/s", + "(C) 7.92e-3 kg*m/s", + "(D) 8.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v-500_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.95e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.65e-3 kg*m/s", + "(B) 1.10e-3 kg*m/s", + "(C) 2.30e-3 kg*m/s", + "(D) 1.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-850_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.54e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.54e-3 kg*m/s", + "(B) 2.76e-3 kg*m/s", + "(C) 2.12e-3 kg*m/s", + "(D) 1.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v-500_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.49e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.12e-3 kg*m/s", + "(B) 1.35e-3 kg*m/s", + "(C) 1.49e-3 kg*m/s", + "(D) 1.68e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.00e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.50e-3 kg*m/s", + "(B) 3.00e-3 kg*m/s", + "(C) 2.90e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v-500_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.19e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.85e-3 kg*m/s", + "(B) 2.19e-3 kg*m/s", + "(C) 2.31e-3 kg*m/s", + "(D) 2.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.28e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.28e-3 kg*m/s", + "(B) 1.05e-3 kg*m/s", + "(C) 1.34e-3 kg*m/s", + "(D) 0.98e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-850_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.58e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.58e-3 kg*m/s", + "(B) 13.21e-3 kg*m/s", + "(C) 10.34e-3 kg*m/s", + "(D) 11.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v-500_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.51e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.87e-3 kg*m/s", + "(B) 7.92e-3 kg*m/s", + "(C) 7.45e-3 kg*m/s", + "(D) 8.51e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.98e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.32e-3 kg*m/s", + "(B) 8.98e-3 kg*m/s", + "(C) 7.45e-3 kg*m/s", + "(D) 9.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v-500_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.93e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.35e-3 kg*m/s", + "(B) 5.93e-3 kg*m/s", + "(C) 4.87e-3 kg*m/s", + "(D) 6.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-850_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.25e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.80e-4 kg*m/s", + "(B) 7.50e-4 kg*m/s", + "(C) 1.60e-3 kg*m/s", + "(D) 1.25e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v-500_017.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.43e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.29e-3 kg*m/s", + "(B) 1.12e-3 kg*m/s", + "(C) 1.43e-3 kg*m/s", + "(D) 1.67e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-850_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.63e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.95e-3 kg*m/s", + "(B) 8.63e-3 kg*m/s", + "(C) 8.01e-3 kg*m/s", + "(D) 9.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v-500_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.68e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.68e-3 kg*m/s", + "(B) 0.53e-3 kg*m/s", + "(C) 0.72e-3 kg*m/s", + "(D) 0.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-850_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.71e-3 kg*m/s", + "Answer Choices": [ + "(A) 11.23e-3 kg*m/s", + "(B) 9.85e-3 kg*m/s", + "(C) 10.02e-3 kg*m/s", + "(D) 10.71e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v-500_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.00e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.00e-4 kg*m/s", + "(B) 1.00e-3 kg*m/s", + "(C) 1.20e-3 kg*m/s", + "(D) 8.50e-4 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.27e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.32e-3 kg*m/s", + "(B) 4.89e-3 kg*m/s", + "(C) 5.75e-3 kg*m/s", + "(D) 5.27e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.22e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.31e-3 kg*m/s", + "(B) 9.85e-4 kg*m/s", + "(C) 1.22e-3 kg*m/s", + "(D) 1.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.67e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.67e-3 kg*m/s", + "(B) 2.95e-3 kg*m/s", + "(C) 4.12e-3 kg*m/s", + "(D) 3.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-850_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.65e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.65e-3 kg*m/s", + "(B) 8.47e-3 kg*m/s", + "(C) 1.12e-2 kg*m/s", + "(D) 7.82e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v-500_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.61e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.61e-3 kg*m/s", + "(B) 2.45e-3 kg*m/s", + "(C) 2.78e-3 kg*m/s", + "(D) 2.13e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.49e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.68e-3 kg*m/s", + "(B) 1.31e-3 kg*m/s", + "(C) 1.49e-3 kg*m/s", + "(D) 1.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v-500_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.82e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.82e-3 kg*m/s", + "(B) 0.65e-3 kg*m/s", + "(C) 0.91e-3 kg*m/s", + "(D) 0.76e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v-500_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.48e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.75e-3 kg*m/s", + "(B) 5.48e-3 kg*m/s", + "(C) 4.38e-3 kg*m/s", + "(D) 5.92e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.59e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.02e-3 kg*m/s", + "(B) 4.87e-3 kg*m/s", + "(C) 5.59e-3 kg*m/s", + "(D) 5.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.32e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.32e-3 kg*m/s", + "(B) 5.43e-3 kg*m/s", + "(C) 5.87e-3 kg*m/s", + "(D) 6.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.37e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.91e-3 kg*m/s", + "(B) 4.75e-3 kg*m/s", + "(C) 5.37e-3 kg*m/s", + "(D) 4.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.80e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.65e-3 kg*m/s", + "(B) 2.10e-3 kg*m/s", + "(C) 1.80e-3 kg*m/s", + "(D) 1.25e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v-500_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.12e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.08e-3 kg*m/s", + "(B) 0.12e-3 kg*m/s", + "(C) 0.15e-3 kg*m/s", + "(D) 0.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "18.85e-3 kg*m/s", + "Answer Choices": [ + "(A) 18.85e-3 kg*m/s", + "(B) 17.67e-3 kg*m/s", + "(C) 12.98e-3 kg*m/s", + "(D) 15.42e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.85e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.85e-3 kg*m/s", + "(B) 8.10e-3 kg*m/s", + "(C) 9.34e-3 kg*m/s", + "(D) 7.92e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "17.65e-3 kg*m/s", + "Answer Choices": [ + "(A) 18.49e-3 kg*m/s", + "(B) 17.65e-3 kg*m/s", + "(C) 16.87e-3 kg*m/s", + "(D) 15.22e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.89e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.89e-3 kg*m/s", + "(B) 3.02e-3 kg*m/s", + "(C) 2.15e-3 kg*m/s", + "(D) 2.47e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.24e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.45e-3 kg*m/s", + "(B) 4.24e-3 kg*m/s", + "(C) 4.76e-3 kg*m/s", + "(D) 3.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v-500_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.84e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.65e-3 kg*m/s", + "(B) 0.84e-3 kg*m/s", + "(C) 0.72e-3 kg*m/s", + "(D) 0.91e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.22e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.18e-3 kg*m/s", + "(B) 0.25e-3 kg*m/s", + "(C) 0.22e-3 kg*m/s", + "(D) 0.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v-500_021.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.02e-3 kg*m/s", + "(B) 0.65e-3 kg*m/s", + "(C) 0.73e-3 kg*m/s", + "(D) 0.88e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.75e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.10e-3 kg*m/s", + "(B) 6.80e-3 kg*m/s", + "(C) 7.20e-3 kg*m/s", + "(D) 7.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.04e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.04e-3 kg*m/s", + "(B) 3.56e-3 kg*m/s", + "(C) 2.89e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.18e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.32e-3 kg*m/s", + "(B) 1.18e-3 kg*m/s", + "(C) 8.60e-4 kg*m/s", + "(D) 9.75e-4 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v-500_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.92e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.75e-3 kg*m/s", + "(B) 0.92e-3 kg*m/s", + "(C) 0.69e-3 kg*m/s", + "(D) 0.88e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.67e-3 kg*m/s", + "(B) 1.12e-3 kg*m/s", + "(C) 1.88e-3 kg*m/s", + "(D) 2.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v-500_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.32e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.48e-3 kg*m/s", + "(B) 1.21e-3 kg*m/s", + "(C) 1.32e-3 kg*m/s", + "(D) 1.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-850_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.20e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.20e-3 kg*m/s", + "(B) 1.35e-3 kg*m/s", + "(C) 9.80e-4 kg*m/s", + "(D) 1.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v-500_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.93e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.75e-3 kg*m/s", + "(B) 0.60e-3 kg*m/s", + "(C) 0.93e-3 kg*m/s", + "(D) 1.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v-500_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.04e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.75e-3 kg*m/s", + "(B) 2.04e-3 kg*m/s", + "(C) 1.89e-3 kg*m/s", + "(D) 2.37e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-850_005.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "16.34e-3 kg*m/s", + "Answer Choices": [ + "(A) 16.34e-3 kg*m/s", + "(B) 14.89e-3 kg*m/s", + "(C) 17.25e-3 kg*m/s", + "(D) 15.47e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v-500_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.47e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.78e-3 kg*m/s", + "(B) 3.47e-3 kg*m/s", + "(C) 2.95e-3 kg*m/s", + "(D) 3.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "11.42e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.63e-3 kg*m/s", + "(B) 11.42e-3 kg*m/s", + "(C) 12.15e-3 kg*m/s", + "(D) 9.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v-500_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.60e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.10e-3 kg*m/s", + "(B) 8.75e-3 kg*m/s", + "(C) 7.90e-3 kg*m/s", + "(D) 9.60e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-850_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.20e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.75e-3 kg*m/s", + "(B) 4.60e-3 kg*m/s", + "(C) 4.85e-3 kg*m/s", + "(D) 5.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v-500_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.92e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.92e-3 kg*m/s", + "(B) 9.38e-3 kg*m/s", + "(C) 7.45e-3 kg*m/s", + "(D) 8.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.84e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.10e-3 kg*m/s", + "(B) 4.84e-3 kg*m/s", + "(C) 4.21e-3 kg*m/s", + "(D) 3.92e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v-500_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.36e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.60e-3 kg*m/s", + "(B) 2.85e-3 kg*m/s", + "(C) 3.75e-3 kg*m/s", + "(D) 3.36e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.47e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.95e-3 kg*m/s", + "(B) 4.88e-3 kg*m/s", + "(C) 4.47e-3 kg*m/s", + "(D) 4.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/q-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u-500_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v-500_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.51e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.51e-3 kg*m/s", + "(B) 0.47e-3 kg*m/s", + "(C) 0.42e-3 kg*m/s", + "(D) 0.56e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.91e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.91e-3 kg*m/s", + "(B) 8.75e-3 kg*m/s", + "(C) 9.62e-3 kg*m/s", + "(D) 12.30e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v-500_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.33e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.33e-3 kg*m/s", + "(B) 2.10e-3 kg*m/s", + "(C) 1.89e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "13.08e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.72e-3 kg*m/s", + "(B) 13.08e-3 kg*m/s", + "(C) 11.89e-3 kg*m/s", + "(D) 12.35e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "18.38e-3 kg*m/s", + "Answer Choices": [ + "(A) 13.64e-3 kg*m/s", + "(B) 18.38e-3 kg*m/s", + "(C) 15.72e-3 kg*m/s", + "(D) 19.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "20.51e-3 kg*m/s", + "Answer Choices": [ + "(A) 19.89e-3 kg*m/s", + "(B) 22.13e-3 kg*m/s", + "(C) 20.51e-3 kg*m/s", + "(D) 18.47e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.22e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.88e-3 kg*m/s", + "(B) 1.95e-3 kg*m/s", + "(C) 2.22e-3 kg*m/s", + "(D) 2.40e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-850_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.25e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.90e-3 kg*m/s", + "(B) 6.80e-3 kg*m/s", + "(C) 6.50e-3 kg*m/s", + "(D) 7.25e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v-500_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.80e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.25e-3 kg*m/s", + "(B) 4.20e-3 kg*m/s", + "(C) 4.80e-3 kg*m/s", + "(D) 5.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v-850_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.44e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.12e-3 kg*m/s", + "(B) 1.44e-3 kg*m/s", + "(C) 1.65e-3 kg*m/s", + "(D) 1.30e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "21.26e-3 kg*m/s", + "Answer Choices": [ + "(A) 19.89e-3 kg*m/s", + "(B) 24.15e-3 kg*m/s", + "(C) 18.73e-3 kg*m/s", + "(D) 21.26e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.59e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.87e-3 kg*m/s", + "(B) 4.05e-3 kg*m/s", + "(C) 3.59e-3 kg*m/s", + "(D) 3.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.94e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.94e-3 kg*m/s", + "(B) 6.72e-3 kg*m/s", + "(C) 7.10e-3 kg*m/s", + "(D) 8.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v-500_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.66e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.59e-3 kg*m/s", + "(B) 0.45e-3 kg*m/s", + "(C) 0.72e-3 kg*m/s", + "(D) 0.66e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.79e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.94e-3 kg*m/s", + "(B) 9.79e-3 kg*m/s", + "(C) 1.05e-2 kg*m/s", + "(D) 8.21e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/q-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u-500_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v-500_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.09e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.75e-4 kg*m/s", + "(B) 9.68e-4 kg*m/s", + "(C) 1.09e-3 kg*m/s", + "(D) 1.32e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v-850_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.12e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.12e-3 kg*m/s", + "(B) 9.43e-3 kg*m/s", + "(C) 11.05e-3 kg*m/s", + "(D) 8.76e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/v-850_010.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.13e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.88e-3 kg*m/s", + "(B) 3.97e-3 kg*m/s", + "(C) 4.25e-3 kg*m/s", + "(D) 4.13e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/v-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "14.50e-3 kg*m/s", + "Answer Choices": [ + "(A) 14.50e-3 kg*m/s", + "(B) 13.20e-3 kg*m/s", + "(C) 15.10e-3 kg*m/s", + "(D) 12.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/v-850_005.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.57e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.21e-3 kg*m/s", + "(B) 9.02e-3 kg*m/s", + "(C) 7.94e-3 kg*m/s", + "(D) 9.57e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.62e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.05e-3 kg*m/s", + "(B) 5.87e-3 kg*m/s", + "(C) 6.62e-3 kg*m/s", + "(D) 7.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/v-850_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "33.99e-3 kg*m/s", + "Answer Choices": [ + "(A) 28.47e-3 kg*m/s", + "(B) 35.12e-3 kg*m/s", + "(C) 33.99e-3 kg*m/s", + "(D) 30.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/v-850_010.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.46e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.46e-3 kg*m/s", + "(B) 11.89e-3 kg*m/s", + "(C) 10.32e-3 kg*m/s", + "(D) 13.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/v-850_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.32e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.88e-3 kg*m/s", + "(B) 3.32e-3 kg*m/s", + "(C) 3.10e-3 kg*m/s", + "(D) 2.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.82e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.45e-3 kg*m/s", + "(B) 9.10e-3 kg*m/s", + "(C) 8.82e-3 kg*m/s", + "(D) 8.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/q-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/u-850_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/v-850_037.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "35.29e-3 kg*m/s", + "Answer Choices": [ + "(A) 35.29e-3 kg*m/s", + "(B) 31.75e-3 kg*m/s", + "(C) 39.12e-3 kg*m/s", + "(D) 28.47e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/q-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/u-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/v-850_030.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "30.72e-3 kg*m/s", + "Answer Choices": [ + "(A) 33.40e-3 kg*m/s", + "(B) 26.89e-3 kg*m/s", + "(C) 28.15e-3 kg*m/s", + "(D) 30.72e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/v-850_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.68e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.72e-3 kg*m/s", + "(B) 0.51e-3 kg*m/s", + "(C) 0.45e-3 kg*m/s", + "(D) 0.68e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/v-850_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.67e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.67e-3 kg*m/s", + "(B) 7.45e-3 kg*m/s", + "(C) 9.12e-3 kg*m/s", + "(D) 8.01e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/v-850_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "11.00e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.60e-3 kg*m/s", + "(B) 11.00e-3 kg*m/s", + "(C) 8.75e-3 kg*m/s", + "(D) 10.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.32e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.32e-3 kg*m/s", + "(B) 6.75e-3 kg*m/s", + "(C) 5.87e-3 kg*m/s", + "(D) 5.40e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/v-850_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.24e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.20e-3 kg*m/s", + "(B) 3.75e-3 kg*m/s", + "(C) 4.24e-3 kg*m/s", + "(D) 4.90e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.59e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.95e-3 kg*m/s", + "(B) 11.42e-3 kg*m/s", + "(C) 10.59e-3 kg*m/s", + "(D) 8.73e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/v-850_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "16.14e-3 kg*m/s", + "Answer Choices": [ + "(A) 14.02e-3 kg*m/s", + "(B) 16.14e-3 kg*m/s", + "(C) 12.87e-3 kg*m/s", + "(D) 17.65e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/v-850_021.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.68e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.92e-3 kg*m/s", + "(B) 5.68e-3 kg*m/s", + "(C) 5.21e-3 kg*m/s", + "(D) 6.15e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/v-850_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "25.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 22.47e-3 kg*m/s", + "(B) 28.13e-3 kg*m/s", + "(C) 19.86e-3 kg*m/s", + "(D) 25.88e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/v-850_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "13.57e-3 kg*m/s", + "Answer Choices": [ + "(A) 14.21e-3 kg*m/s", + "(B) 11.42e-3 kg*m/s", + "(C) 9.87e-3 kg*m/s", + "(D) 13.57e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/v-850_005.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.16e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.85e-3 kg*m/s", + "(B) 5.72e-3 kg*m/s", + "(C) 6.16e-3 kg*m/s", + "(D) 4.98e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/q-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/u-850_037.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_026.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_027.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_029.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_030.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_031.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_033.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_034.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_035.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/v-850_037.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "21.90e-3 kg*m/s", + "Answer Choices": [ + "(A) 19.85e-3 kg*m/s", + "(B) 18.75e-3 kg*m/s", + "(C) 23.40e-3 kg*m/s", + "(D) 21.90e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/v-850_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.44e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.03e-3 kg*m/s", + "(B) 6.44e-3 kg*m/s", + "(C) 5.12e-3 kg*m/s", + "(D) 6.01e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.12e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.12e-3 kg*m/s", + "(B) 2.97e-3 kg*m/s", + "(C) 3.45e-3 kg*m/s", + "(D) 2.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/v-850_025.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.07e-3 kg*m/s", + "Answer Choices": [ + "(A) 13.22e-3 kg*m/s", + "(B) 12.07e-3 kg*m/s", + "(C) 11.68e-3 kg*m/s", + "(D) 10.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.09e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.09e-3 kg*m/s", + "(B) 3.20e-3 kg*m/s", + "(C) 4.50e-3 kg*m/s", + "(D) 3.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at São Paulo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/v-850_005.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.50e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.75e-3 kg*m/s", + "(B) 10.50e-3 kg*m/s", + "(C) 9.95e-3 kg*m/s", + "(D) 12.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.37e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 5.90e-3 kg*m/s", + "(C) 6.37e-3 kg*m/s", + "(D) 4.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.63e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.89e-3 kg*m/s", + "(B) 5.12e-3 kg*m/s", + "(C) 4.63e-3 kg*m/s", + "(D) 4.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/v-850_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "19.27e-3 kg*m/s", + "Answer Choices": [ + "(A) 19.27e-3 kg*m/s", + "(B) 21.03e-3 kg*m/s", + "(C) 17.65e-3 kg*m/s", + "(D) 15.84e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/v-850_009.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.56e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.56e-3 kg*m/s", + "(B) 9.12e-3 kg*m/s", + "(C) 8.45e-3 kg*m/s", + "(D) 8.73e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v-850_007.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.94e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.21e-3 kg*m/s", + "(B) 10.94e-3 kg*m/s", + "(C) 8.87e-3 kg*m/s", + "(D) 11.58e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.15e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.00e-3 kg*m/s", + "(B) 1.15e-3 kg*m/s", + "(C) 1.32e-3 kg*m/s", + "(D) 9.80e-4 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.12e-3 kg*m/s", + "(B) 7.45e-3 kg*m/s", + "(C) 6.02e-3 kg*m/s", + "(D) 6.88e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.76e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.89e-3 kg*m/s", + "(B) 6.76e-3 kg*m/s", + "(C) 7.12e-3 kg*m/s", + "(D) 6.02e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v-850_017.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.72e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.02e-3 kg*m/s", + "(B) 9.85e-3 kg*m/s", + "(C) 11.34e-3 kg*m/s", + "(D) 10.72e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.18e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.85e-3 kg*m/s", + "(B) 2.30e-3 kg*m/s", + "(C) 2.18e-3 kg*m/s", + "(D) 2.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.19e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.42e-3 kg*m/s", + "(B) 7.19e-3 kg*m/s", + "(C) 6.85e-3 kg*m/s", + "(D) 7.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v-850_013.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.71e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.71e-3 kg*m/s", + "(B) 8.45e-3 kg*m/s", + "(C) 1.02e-2 kg*m/s", + "(D) 7.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.05e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.20e-3 kg*m/s", + "(B) 8.75e-4 kg*m/s", + "(C) 1.05e-3 kg*m/s", + "(D) 9.95e-4 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.18e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.92e-3 kg*m/s", + "(B) 6.87e-3 kg*m/s", + "(C) 8.18e-3 kg*m/s", + "(D) 7.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v-850_025.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.19e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.19e-3 kg*m/s", + "(B) 3.77e-3 kg*m/s", + "(C) 4.02e-3 kg*m/s", + "(D) 3.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v-850_021.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.21e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.85e-3 kg*m/s", + "(B) 2.05e-3 kg*m/s", + "(C) 2.21e-3 kg*m/s", + "(D) 2.35e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v-850_021.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.38e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.38e-3 kg*m/s", + "(B) 1.12e-3 kg*m/s", + "(C) 1.45e-3 kg*m/s", + "(D) 1.29e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.64e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.20e-3 kg*m/s", + "(B) 4.10e-3 kg*m/s", + "(C) 2.95e-3 kg*m/s", + "(D) 3.64e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.87e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.01e-3 kg*m/s", + "(B) 6.45e-3 kg*m/s", + "(C) 8.22e-3 kg*m/s", + "(D) 7.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.75e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.70e-3 kg*m/s", + "(B) 0.82e-3 kg*m/s", + "(C) 0.75e-3 kg*m/s", + "(D) 0.68e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v-850_025.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.68e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.12e-3 kg*m/s", + "(B) 4.91e-3 kg*m/s", + "(C) 5.03e-3 kg*m/s", + "(D) 5.68e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.08e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.92e-3 kg*m/s", + "(B) 1.75e-3 kg*m/s", + "(C) 2.08e-3 kg*m/s", + "(D) 2.50e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v-850_009.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.54e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.39e-3 kg*m/s", + "(B) 1.68e-3 kg*m/s", + "(C) 1.12e-3 kg*m/s", + "(D) 1.54e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v-850_015.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.93e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.95e-3 kg*m/s", + "(B) 1.12e-2 kg*m/s", + "(C) 8.47e-3 kg*m/s", + "(D) 9.93e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "10.99e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.45e-3 kg*m/s", + "(B) 12.30e-3 kg*m/s", + "(C) 10.99e-3 kg*m/s", + "(D) 9.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.36e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.28e-3 kg*m/s", + "(B) 0.36e-3 kg*m/s", + "(C) 0.42e-3 kg*m/s", + "(D) 0.31e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.01e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.78e-3 kg*m/s", + "(B) 4.89e-3 kg*m/s", + "(C) 5.01e-3 kg*m/s", + "(D) 4.32e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v-850_009.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "11.17e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.03e-3 kg*m/s", + "(B) 11.17e-3 kg*m/s", + "(C) 10.42e-3 kg*m/s", + "(D) 9.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v-850_009.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.09e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.67e-3 kg*m/s", + "(B) 1.85e-3 kg*m/s", + "(C) 2.09e-3 kg*m/s", + "(D) 2.34e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.45e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.87e-3 kg*m/s", + "(B) 4.10e-3 kg*m/s", + "(C) 4.92e-3 kg*m/s", + "(D) 4.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v-850_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.74e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 5.89e-3 kg*m/s", + "(C) 6.74e-3 kg*m/s", + "(D) 6.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v-850_013.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.81e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.45e-3 kg*m/s", + "(B) 4.12e-3 kg*m/s", + "(C) 3.81e-3 kg*m/s", + "(D) 2.97e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/q-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u-850_025.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_018.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_019.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_021.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_022.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_023.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v-850_025.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "11.77e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.21e-3 kg*m/s", + "(B) 12.65e-3 kg*m/s", + "(C) 11.77e-3 kg*m/s", + "(D) 9.84e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/q-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u-850_017.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_014.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_015.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v-850_017.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.61e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.61e-3 kg*m/s", + "(B) 5.20e-3 kg*m/s", + "(C) 3.95e-3 kg*m/s", + "(D) 4.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "16.32e-3 kg*m/s", + "Answer Choices": [ + "(A) 15.60e-3 kg*m/s", + "(B) 16.32e-3 kg*m/s", + "(C) 17.45e-3 kg*m/s", + "(D) 14.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v-850_013.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.35e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.92e-3 kg*m/s", + "(B) 5.80e-3 kg*m/s", + "(C) 4.65e-3 kg*m/s", + "(D) 5.35e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v-850_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.69e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.21e-3 kg*m/s", + "(B) 7.69e-3 kg*m/s", + "(C) 7.02e-3 kg*m/s", + "(D) 8.15e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v-850_007.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.74e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.68e-3 kg*m/s", + "(B) 0.71e-3 kg*m/s", + "(C) 0.74e-3 kg*m/s", + "(D) 0.79e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/q-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u-850_013.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_001.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_002.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_003.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_005.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_006.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_007.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_009.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_010.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_011.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v-850_013.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.00e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.75e-3 kg*m/s", + "(B) 5.00e-3 kg*m/s", + "(C) 5.80e-3 kg*m/s", + "(D) 4.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.27e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.70e-3 kg*m/s", + "(B) 3.27e-3 kg*m/s", + "(C) 2.95e-3 kg*m/s", + "(D) 3.60e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.64e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.45e-3 kg*m/s", + "(B) 1.21e-3 kg*m/s", + "(C) 1.64e-3 kg*m/s", + "(D) 1.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.95e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.10e-3 kg*m/s", + "(B) 1.95e-3 kg*m/s", + "(C) 1.50e-3 kg*m/s", + "(D) 1.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.50e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.90e-3 kg*m/s", + "(B) 3.50e-3 kg*m/s", + "(C) 2.95e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.40e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.40e-3 kg*m/s", + "(B) 6.20e-3 kg*m/s", + "(C) 6.85e-3 kg*m/s", + "(D) 7.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.91e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.62e-3 kg*m/s", + "(B) 0.75e-3 kg*m/s", + "(C) 0.91e-3 kg*m/s", + "(D) 1.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.44e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.44e-3 kg*m/s", + "(B) 9.15e-3 kg*m/s", + "(C) 6.92e-3 kg*m/s", + "(D) 7.38e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.10e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.70e-3 kg*m/s", + "(B) 3.10e-3 kg*m/s", + "(C) 3.45e-3 kg*m/s", + "(D) 2.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.37e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.12e-3 kg*m/s", + "(B) 6.37e-3 kg*m/s", + "(C) 6.01e-3 kg*m/s", + "(D) 7.05e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "18.14e-3 kg*m/s", + "Answer Choices": [ + "(A) 20.03e-3 kg*m/s", + "(B) 18.14e-3 kg*m/s", + "(C) 12.75e-3 kg*m/s", + "(D) 15.62e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.02e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.10e-3 kg*m/s", + "(B) 6.02e-3 kg*m/s", + "(C) 6.85e-3 kg*m/s", + "(D) 4.93e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "38.55e-3 kg*m/s", + "Answer Choices": [ + "(A) 35.20e-3 kg*m/s", + "(B) 32.90e-3 kg*m/s", + "(C) 41.75e-3 kg*m/s", + "(D) 38.55e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.96e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.45e-3 kg*m/s", + "(B) 1.96e-3 kg*m/s", + "(C) 1.72e-3 kg*m/s", + "(D) 2.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.55e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.20e-3 kg*m/s", + "(B) 9.10e-3 kg*m/s", + "(C) 8.55e-3 kg*m/s", + "(D) 8.00e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.96e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.45e-3 kg*m/s", + "(B) 6.32e-3 kg*m/s", + "(C) 8.96e-3 kg*m/s", + "(D) 9.87e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.66e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.21e-3 kg*m/s", + "(B) 5.66e-3 kg*m/s", + "(C) 6.12e-3 kg*m/s", + "(D) 4.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.14e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.85e-3 kg*m/s", + "(B) 6.48e-3 kg*m/s", + "(C) 7.92e-3 kg*m/s", + "(D) 7.14e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.30e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.85e-3 kg*m/s", + "(B) 2.75e-3 kg*m/s", + "(C) 1.60e-3 kg*m/s", + "(D) 2.30e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.36e-3 kg*m/s", + "Answer Choices": [ + "(A) 9.85e-3 kg*m/s", + "(B) 13.42e-3 kg*m/s", + "(C) 12.36e-3 kg*m/s", + "(D) 11.07e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.86e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.86e-3 kg*m/s", + "(B) 4.23e-3 kg*m/s", + "(C) 3.92e-3 kg*m/s", + "(D) 5.14e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.48e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.87e-3 kg*m/s", + "(B) 6.48e-3 kg*m/s", + "(C) 6.95e-3 kg*m/s", + "(D) 5.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.33e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.87e-3 kg*m/s", + "(B) 2.33e-3 kg*m/s", + "(C) 2.10e-3 kg*m/s", + "(D) 2.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.54e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.87e-3 kg*m/s", + "(B) 4.01e-3 kg*m/s", + "(C) 5.12e-3 kg*m/s", + "(D) 4.54e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "0.77e-3 kg*m/s", + "Answer Choices": [ + "(A) 0.71e-3 kg*m/s", + "(B) 0.82e-3 kg*m/s", + "(C) 0.77e-3 kg*m/s", + "(D) 0.65e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.89e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 8.32e-3 kg*m/s", + "(C) 7.89e-3 kg*m/s", + "(D) 6.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.47e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.47e-3 kg*m/s", + "(B) 2.12e-3 kg*m/s", + "(C) 1.85e-3 kg*m/s", + "(D) 2.91e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.17e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.88e-3 kg*m/s", + "(B) 9.92e-3 kg*m/s", + "(C) 8.45e-3 kg*m/s", + "(D) 9.17e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Cairo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.45e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.92e-3 kg*m/s", + "(B) 3.45e-3 kg*m/s", + "(C) 3.87e-3 kg*m/s", + "(D) 4.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.39e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.47e-3 kg*m/s", + "(B) 6.39e-3 kg*m/s", + "(C) 5.82e-3 kg*m/s", + "(D) 6.95e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Auckland?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.30e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.30e-3 kg*m/s", + "(B) 2.95e-3 kg*m/s", + "(C) 3.75e-3 kg*m/s", + "(D) 2.60e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.93e-3 kg*m/s", + "Answer Choices": [ + "(A) 11.62e-3 kg*m/s", + "(B) 10.47e-3 kg*m/s", + "(C) 13.85e-3 kg*m/s", + "(D) 12.93e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.53e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.53e-3 kg*m/s", + "(B) 1.12e-3 kg*m/s", + "(C) 1.39e-3 kg*m/s", + "(D) 1.78e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.38e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.95e-3 kg*m/s", + "(B) 2.38e-3 kg*m/s", + "(C) 2.65e-3 kg*m/s", + "(D) 2.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.82e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.10e-3 kg*m/s", + "(B) 3.82e-3 kg*m/s", + "(C) 2.95e-3 kg*m/s", + "(D) 3.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.22e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.22e-3 kg*m/s", + "(B) 1.95e-3 kg*m/s", + "(C) 1.80e-3 kg*m/s", + "(D) 2.40e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mexico City?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.84e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.03e-3 kg*m/s", + "(B) 1.67e-3 kg*m/s", + "(C) 1.21e-3 kg*m/s", + "(D) 1.84e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.55e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.20e-3 kg*m/s", + "(B) 8.55e-3 kg*m/s", + "(C) 6.85e-3 kg*m/s", + "(D) 9.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.46e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.02e-3 kg*m/s", + "(B) 6.12e-3 kg*m/s", + "(C) 5.46e-3 kg*m/s", + "(D) 4.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.82e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.82e-3 kg*m/s", + "(B) 5.21e-3 kg*m/s", + "(C) 4.67e-3 kg*m/s", + "(D) 6.15e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Madrid?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.05e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.05e-3 kg*m/s", + "(B) 3.89e-3 kg*m/s", + "(C) 2.47e-3 kg*m/s", + "(D) 2.92e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "13.85e-3 kg*m/s", + "Answer Choices": [ + "(A) 14.32e-3 kg*m/s", + "(B) 13.85e-3 kg*m/s", + "(C) 12.47e-3 kg*m/s", + "(D) 11.98e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.50e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.00e-3 kg*m/s", + "(B) 2.85e-3 kg*m/s", + "(C) 3.50e-3 kg*m/s", + "(D) 3.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "22.29e-3 kg*m/s", + "Answer Choices": [ + "(A) 22.29e-3 kg*m/s", + "(B) 20.43e-3 kg*m/s", + "(C) 18.75e-3 kg*m/s", + "(D) 25.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.45e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.45e-3 kg*m/s", + "(B) 6.37e-3 kg*m/s", + "(C) 7.91e-3 kg*m/s", + "(D) 6.82e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.53e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.53e-3 kg*m/s", + "(B) 6.12e-3 kg*m/s", + "(C) 5.01e-3 kg*m/s", + "(D) 4.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.21e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.78e-3 kg*m/s", + "(B) 2.45e-3 kg*m/s", + "(C) 1.96e-3 kg*m/s", + "(D) 2.21e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.58e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 6.91e-3 kg*m/s", + "(C) 6.85e-3 kg*m/s", + "(D) 7.58e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.68e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.20e-3 kg*m/s", + "(B) 6.10e-3 kg*m/s", + "(C) 4.95e-3 kg*m/s", + "(D) 5.68e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "16.10e-3 kg*m/s", + "Answer Choices": [ + "(A) 16.10e-3 kg*m/s", + "(B) 17.25e-3 kg*m/s", + "(C) 15.40e-3 kg*m/s", + "(D) 14.85e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.42e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.95e-3 kg*m/s", + "(B) 3.45e-3 kg*m/s", + "(C) 3.87e-3 kg*m/s", + "(D) 4.42e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.61e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.61e-3 kg*m/s", + "(B) 3.12e-3 kg*m/s", + "(C) 2.98e-3 kg*m/s", + "(D) 2.75e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.03e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.03e-3 kg*m/s", + "(B) 6.12e-3 kg*m/s", + "(C) 7.85e-3 kg*m/s", + "(D) 5.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.37e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.89e-3 kg*m/s", + "(B) 2.75e-3 kg*m/s", + "(C) 1.52e-3 kg*m/s", + "(D) 2.37e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.69e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.69e-3 kg*m/s", + "(B) 1.85e-3 kg*m/s", + "(C) 2.12e-3 kg*m/s", + "(D) 3.04e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "11.89e-3 kg*m/s", + "Answer Choices": [ + "(A) 10.45e-3 kg*m/s", + "(B) 9.88e-3 kg*m/s", + "(C) 12.73e-3 kg*m/s", + "(D) 11.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.03e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.03e-3 kg*m/s", + "(B) 6.89e-3 kg*m/s", + "(C) 4.97e-3 kg*m/s", + "(D) 5.12e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.88e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.60e-3 kg*m/s", + "(B) 1.25e-3 kg*m/s", + "(C) 1.88e-3 kg*m/s", + "(D) 2.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "15.25e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.80e-3 kg*m/s", + "(B) 14.45e-3 kg*m/s", + "(C) 15.25e-3 kg*m/s", + "(D) 16.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.90e-3 kg*m/s", + "Answer Choices": [ + "(A) 4.90e-3 kg*m/s", + "(B) 5.60e-3 kg*m/s", + "(C) 3.75e-3 kg*m/s", + "(D) 4.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Lima?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "3.20e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.60e-3 kg*m/s", + "(B) 2.85e-3 kg*m/s", + "(C) 3.45e-3 kg*m/s", + "(D) 3.20e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "7.08e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.88e-3 kg*m/s", + "(B) 7.92e-3 kg*m/s", + "(C) 6.45e-3 kg*m/s", + "(D) 7.08e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Nairobi?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.00e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.20e-3 kg*m/s", + "(B) 4.80e-3 kg*m/s", + "(C) 3.75e-3 kg*m/s", + "(D) 4.00e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Kinshasa?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.26e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.40e-3 kg*m/s", + "(B) 1.85e-3 kg*m/s", + "(C) 2.26e-3 kg*m/s", + "(D) 2.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "17.02e-3 kg*m/s", + "Answer Choices": [ + "(A) 17.02e-3 kg*m/s", + "(B) 16.30e-3 kg*m/s", + "(C) 15.87e-3 kg*m/s", + "(D) 18.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Wellington?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "2.82e-3 kg*m/s", + "Answer Choices": [ + "(A) 2.82e-3 kg*m/s", + "(B) 2.47e-3 kg*m/s", + "(C) 2.15e-3 kg*m/s", + "(D) 3.01e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Beijing?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "4.55e-3 kg*m/s", + "Answer Choices": [ + "(A) 3.87e-3 kg*m/s", + "(B) 5.12e-3 kg*m/s", + "(C) 4.01e-3 kg*m/s", + "(D) 4.55e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Mumbai?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.59e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.12e-3 kg*m/s", + "(B) 1.74e-3 kg*m/s", + "(C) 1.35e-3 kg*m/s", + "(D) 1.59e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Athens?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "13.14e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.35e-3 kg*m/s", + "(B) 11.87e-3 kg*m/s", + "(C) 13.14e-3 kg*m/s", + "(D) 14.02e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Moscow?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.20e-3 kg*m/s", + "Answer Choices": [ + "(A) 5.75e-3 kg*m/s", + "(B) 6.80e-3 kg*m/s", + "(C) 6.20e-3 kg*m/s", + "(D) 5.10e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Tokyo?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "8.03e-3 kg*m/s", + "Answer Choices": [ + "(A) 7.12e-3 kg*m/s", + "(B) 6.85e-3 kg*m/s", + "(C) 8.94e-3 kg*m/s", + "(D) 8.03e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Ulaanbaatar?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.53e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.67e-3 kg*m/s", + "(B) 1.53e-3 kg*m/s", + "(C) 1.12e-3 kg*m/s", + "(D) 1.39e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Toronto?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "12.09e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.75e-3 kg*m/s", + "(B) 13.67e-3 kg*m/s", + "(C) 12.09e-3 kg*m/s", + "(D) 10.42e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "14.59e-3 kg*m/s", + "Answer Choices": [ + "(A) 15.42e-3 kg*m/s", + "(B) 12.73e-3 kg*m/s", + "(C) 13.88e-3 kg*m/s", + "(D) 14.59e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 6h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at London?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "5.98e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.42e-3 kg*m/s", + "(B) 5.10e-3 kg*m/s", + "(C) 4.75e-3 kg*m/s", + "(D) 5.98e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "13.69e-3 kg*m/s", + "Answer Choices": [ + "(A) 12.47e-3 kg*m/s", + "(B) 13.69e-3 kg*m/s", + "(C) 11.25e-3 kg*m/s", + "(D) 14.82e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at New York?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "9.71e-3 kg*m/s", + "Answer Choices": [ + "(A) 8.45e-3 kg*m/s", + "(B) 1.02e-2 kg*m/s", + "(C) 9.71e-3 kg*m/s", + "(D) 7.89e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "6.67e-3 kg*m/s", + "Answer Choices": [ + "(A) 6.10e-3 kg*m/s", + "(B) 6.67e-3 kg*m/s", + "(C) 5.12e-3 kg*m/s", + "(D) 7.45e-3 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-Moisture_flux_analysis-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24h and starting time is 12:00:00 UTC, variable names are noted in image title. What is the maximum value of moisture flux at Sydney?", + "Variable": "vapor_flux", + "Images": [], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "Moisture flux analysis", + "Dataset": "ERA5", + "Answer": "1.25e-3 kg*m/s", + "Answer Choices": [ + "(A) 1.05e-3 kg*m/s", + "(B) 1.40e-3 kg*m/s", + "(C) 1.25e-3 kg*m/s", + "(D) 9.80e-4 kg*m/s", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/medium_term/Perception/System_identification.json b/jsons/Atmosphere/medium_term/Perception/System_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..ddd28cb480fd05a4cf6c239e53825205cd9712f2 --- /dev/null +++ b/jsons/Atmosphere/medium_term/Perception/System_identification.json @@ -0,0 +1,11760 @@ +[ + { + "Question_id": "medium_term-System_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/00_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Tropical cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/01_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Heatwave", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/02_24h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Coldwave", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/03_24h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/04_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Tropical cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/05_24h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Tropical cyclone", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/06_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Hurricane", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/07_24h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/08_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Heatwave", + "(C) Cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/09_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/10_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Hurricane", + "(C) Heatwave", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/11_6h/v10_024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Coldwave", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/12_24h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical cyclone", + "(C) Coldwave", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/13_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/14_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Tropical cyclone", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/15_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/16_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Tropical cyclone", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/17_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/18_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/19_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/20_24h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Coldwave", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/21_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Tropical cyclone", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/22_24h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical cyclone", + "(C) Coldwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/23_24h/v10_024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/24_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/25_24h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical cyclone", + "(C) Coldwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/26_24h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical cyclone", + "(C) Heatwave", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/27_24h/v10_028.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/28_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/29_24h/v10_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Tropical cyclone", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/30_24h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical cyclone", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/31_24h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Coldwave", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/32_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/33_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Coldwave", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/34_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Coldwave", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/35_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Coldwave", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/36_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Coldwave", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/37_24h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Coldwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/38_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cyclone", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/39_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Coldwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/40_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/41_24h/v10_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/coldwave/42_24h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Coldwave", + "Answer Choices": [ + "(A) Coldwave", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/00_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/01_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Extratropical cyclone", + "(C) Mesoscale convective system", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/02_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Mesoscale convective system", + "(C) Tropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/03_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Monsoon system", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/04_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Anticyclone", + "(C) Extratropical cyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/05_6h/v10_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/06_6h/v10_004.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Tropical cyclone", + "(C) Mesoscale convective system", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/07_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/08_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Tropical cyclone", + "(C) Monsoon system", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/09_6h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Anticyclone", + "(C) Monsoon system", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/10_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Extratropical cyclone", + "(C) Anticyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/11_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/12_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Tropical cyclone", + "(C) Extratropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/13_6h/v10_016.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/14_6h/v10_004.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/15_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Mesoscale convective system", + "(C) Anticyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/16_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/17_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Extratropical cyclone", + "(C) Anticyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/18_6h/v10_016.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Extratropical cyclone", + "(C) Mesoscale convective system", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/19_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Tropical cyclone", + "(C) Extratropical cyclone", + "(D) Monsoon system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/20_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/21_6h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Extratropical cyclone", + "(C) Mesoscale convective system", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/22_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Extratropical cyclone", + "(C) Tropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/23_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/24_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Monsoon system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/25_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Mesoscale convective system", + "(C) Tropical cyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/26_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/27_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Extratropical cyclone", + "(C) Tropical cyclone", + "(D) Monsoon system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/28_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Monsoon system", + "(C) Anticyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/29_6h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Tropical cyclone", + "(C) Monsoon system", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/30_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/31_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Mesoscale convective system", + "(C) Tropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/32_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Mesoscale convective system", + "(C) Extratropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/33_6h/v10_004.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Anticyclone", + "(C) Extratropical cyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/34_6h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Extratropical cyclone", + "(C) Anticyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/35_6h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Monsoon system", + "(B) Extratropical cyclone", + "(C) Tropical cyclone", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/36_6h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Tropical cyclone", + "(C) Mesoscale convective system", + "(D) Anticyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/37_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/38_6h/v10_016.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/39_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Mesoscale convective system", + "(C) Anticyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/40_6h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/41_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Tropical cyclone", + "(C) Anticyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/42_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Anticyclone", + "(C) Extratropical cyclone", + "(D) Mesoscale convective system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/43_6h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Tropical cyclone", + "(D) Monsoon system", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/44_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Mesoscale convective system", + "(B) Anticyclone", + "(C) Extratropical cyclone", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/45_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Extratropical cyclone", + "(C) Mesoscale convective system", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/46_6h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Tropical cyclone", + "(C) Mesoscale convective system", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/47_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Extratropical cyclone", + "(B) Anticyclone", + "(C) Mesoscale convective system", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/extratropical_cyclone/48_6h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Extratropical cyclone", + "Answer Choices": [ + "(A) Anticyclone", + "(B) Mesoscale convective system", + "(C) Tropical cyclone", + "(D) Extratropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/00_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Wildfire", + "(C) Flood", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/01_24h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Drought", + "(C) Wildfire", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/02_24h/tp6h_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Snowstorm", + "(B) Heatwave", + "(C) Flood", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/03_6h/tp6h_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Flood", + "(C) Wildfire", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/04_6h/tp6h_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Flood", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/05_6h/tp6h_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Flood", + "(C) Wildfire", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/06_24h/tp6h_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Heatwave", + "(C) Wildfire", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/07_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Wildfire", + "(C) Flood", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/08_6h/tp6h_024.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Wildfire", + "(C) Drought", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/09_24h/tp6h_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Wildfire", + "(C) Heatwave", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/10_6h/tp6h_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Wildfire", + "(C) Drought", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/11_6h/tp6h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Drought", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/sst_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/12_24h/tp6h_036.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Drought", + "(C) Flood", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/13_24h/tp6h_028.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Drought", + "(C) Wildfire", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/14_24h/tp6h_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Heatwave", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/15_6h/tp6h_024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Drought", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/16_24h/tp6h_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Drought", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/17_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Heatwave", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/18_24h/tp6h_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Drought", + "(C) Flood", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/19_6h/tp6h_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Drought", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/20_6h/tp6h_024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Flood", + "(C) Wildfire", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/21_24h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Flood", + "(C) Wildfire", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/22_6h/tp6h_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Heatwave", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/23_6h/tp6h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Flood", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/24_6h/tp6h_024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Wildfire", + "(C) Drought", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/25_24h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Drought", + "(C) Wildfire", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/26_6h/tp6h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Wildfire", + "(C) Flood", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/27_6h/tp6h_016.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Wildfire", + "(C) Drought", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/28_24h/tp6h_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Wildfire", + "(C) Flood", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/29_6h/tp6h_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Drought", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/sst_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/30_24h/tp6h_036.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Flood", + "(C) Wildfire", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/sst_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/swvl1_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tcc_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/31_24h/tp6h_036.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Wildfire", + "(C) Flood", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/32_24h/tp6h_016.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Wildfire", + "(C) Flood", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/33_24h/tp6h_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Drought", + "(B) Flood", + "(C) Heatwave", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/34_6h/tp6h_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Drought", + "(C) Flood", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/sst_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/swvl1_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/35_6h/tp6h_024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Heatwave", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/36_6h/tp6h_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Heatwave", + "(C) Drought", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/37_6h/tp6h_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Flood", + "(C) Drought", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/sst_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/swvl1_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/38_6h/tp6h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Heatwave", + "(C) Wildfire", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/39_6h/tp6h_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Heatwave", + "(B) Flood", + "(C) Drought", + "(D) Wildfire", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/sst_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/swvl1_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/40_6h/tp6h_016.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Flood", + "(B) Wildfire", + "(C) Heatwave", + "(D) Drought", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/sst_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/sst_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/sst_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/swvl1_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/flood/41_6h/tp6h_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Flood", + "Answer Choices": [ + "(A) Wildfire", + "(B) Heatwave", + "(C) Drought", + "(D) Flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/00_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/01_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Cold front", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/02_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical storm", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/03_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/04_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/05_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cyclone", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/06_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/07_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/08_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Tropical storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/09_6h/v10_016.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/10_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical storm", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/11_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Heatwave", + "(C) Cyclone", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/12_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Heatwave", + "(C) Cold front", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/13_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Heatwave", + "(C) Cold front", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/14_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Heatwave", + "(C) Tropical storm", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/15_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Tropical storm", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/16_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical cyclone", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/17_24h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Tropical storm", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/18_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/19_24h/v10_028.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cyclone", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/20_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Tropical storm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/21_24h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/22_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/23_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Heatwave", + "(C) Tropical storm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/24_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/25_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/26_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Tropical storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/27_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Cold front", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/28_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Heatwave", + "(C) Cold front", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/29_24h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Cold front", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/30_24h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Cold front", + "(D) Tropical storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/31_24h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Tropical storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/32_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/33_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Tropical storm", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/34_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Heatwave", + "(C) Cold front", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/35_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Heatwave", + "(C) Cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/36_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical cyclone", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/37_24h/v10_024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/38_6h/v10_024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/39_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Cyclone", + "(C) Cold front", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/40_24h/v10_028.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/41_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Heatwave", + "(C) Cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/42_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Cyclone", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/43_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/44_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/45_24h/v10_008.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/46_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/47_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Thunderstorm", + "(C) Cold front", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/48_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Tropical storm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/49_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Cold front", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/50_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cyclone", + "(B) Heatwave", + "(C) Cold front", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/51_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Cold front", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/52_24h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Heatwave", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Tropical storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/53_24h/v10_036.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Cold front", + "(C) Heatwave", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/54_24h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heatwave", + "(C) Cyclone", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/55_24h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical storm", + "(C) Heatwave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/mtnlwrf_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/skt_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/tp6h_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/u10_040.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_028.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_032.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_036.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/heatwave/56_24h/v10_040.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Heatwave", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Cyclone", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/00_24h/v10_004.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/01_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/02_6h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Blizzards", + "(C) Thunderstorms", + "(D) Snow squalls", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/03_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/04_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/05_6h/v10_016.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Lake-effect snow", + "(C) Snow squalls", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/06_6h/v10_016.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Thunderstorms", + "(B) Cold fronts", + "(C) Blizzards", + "(D) Snow squalls", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/07_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/08_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/09_6h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Cold fronts", + "(C) Blizzards", + "(D) Snow squalls", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/10_6h/v10_008.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Snow squalls", + "(B) Blizzards", + "(C) Cold fronts", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/11_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Snow squalls", + "(C) Lake-effect snow", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/12_6h/v10_024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/13_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Winter storms", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/14_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Thunderstorms", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/15_6h/v10_012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Lake-effect snow", + "(C) Cold fronts", + "(D) Snow squalls", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/16_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Snow squalls", + "(C) Blizzards", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/17_24h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/18_6h/v10_024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/19_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Snow squalls", + "(C) Blizzards", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/20_6h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Thunderstorms", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/21_24h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/22_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Snow squalls", + "(B) Cold fronts", + "(C) Blizzards", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/23_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Snow squalls", + "(C) Blizzards", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/24_6h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Snow squalls", + "(C) Lake-effect snow", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/25_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/26_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/27_6h/v10_008.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/28_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Snow squalls", + "(B) Cold fronts", + "(C) Lake-effect snow", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/29_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Snow squalls", + "(C) Lake-effect snow", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/30_6h/v10_012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Snow squalls", + "(B) Blizzards", + "(C) Cold fronts", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tcc_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/tp6h_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/31_6h/v10_024.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Snow squalls", + "(C) Lake-effect snow", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/32_24h/v10_004.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/33_6h/v10_016.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Blizzards", + "(C) Snow squalls", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/34_6h/v10_012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Winter storms", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/35_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Blizzards", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Lake-effect snow", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/36_24h/v10_008.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Snow squalls", + "(C) Cold fronts", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-229", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 96 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/37_24h/v10_004.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Snow squalls", + "(B) Lake-effect snow", + "(C) Blizzards", + "(D) Cold fronts", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-230", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tcc_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/tp6h_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/38_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Cold fronts", + "(B) Lake-effect snow", + "(C) Snow squalls", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "medium_term-System_identification-231", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a medium_term event. Temporal resolution of 24 hours and starting time is 12:00:00 UTC, variable names are noted in image title. What type of system represented in given images?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tcc_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/tp6h_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/MEDIUM_EVENTS/region/snow_squalls/39_6h/v10_012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "medium term", + "L3-task": "Perception", + "L4-task": "System identification", + "Dataset": "ERA5", + "Answer": "Snow squalls", + "Answer Choices": [ + "(A) Lake-effect snow", + "(B) Cold fronts", + "(C) Snow squalls", + "(D) Blizzards", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/seasonal_term/Perception/Precipitation_anomaly_identification.json b/jsons/Atmosphere/seasonal_term/Perception/Precipitation_anomaly_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..2962dee07203ef76281965efe78a04f194689ccf --- /dev/null +++ b/jsons/Atmosphere/seasonal_term/Perception/Precipitation_anomaly_identification.json @@ -0,0 +1,2477 @@ +[ + { + "Question_id": "seasonal_term-precipitation_anomaly-000", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2010. During which season in 2010 did New Zealand experience the most significant precipitation deficit?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Summer (December–February)", + "B. Autumn (March–May)", + "C. Winter (June–August)", + "D. Spring (September–November)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-001", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2010. Based on the precipitation anomaly dot plot for 2010, which season shows the highest global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (December–February)", + "B. Spring (March–May)", + "C. Summer (June–August)", + "D. Fall (September–November)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-002", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2010. Which season in 2010 contributed most to Australia’s record wet year, according to the global precipitation anomaly dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Spring (September–November)", + "B. Summer (December–February)", + "C. Winter (June–August)", + "D. Autumn (March–May)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-003", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2010. According to the dot plot, during which season did global precipitation anomalies likely correspond to the flooding in Pakistan?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Spring (March–May)", + "B. Summer (June–August)", + "C. Fall (September–November)", + "D. Winter (December–February)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-004", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2010. According to the dot plot, what was the trend in global precipitation anomalies during the first half of 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Consistently below average", + "B. Fluctuating with no clear trend", + "C. Increasingly above average", + "D. Consistently above average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-005", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2011. Based on the dot plot of monthly global precipitation anomaly for 2011, which season showed the highest positive anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-006", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2011. During which season of 2011 did global land precipitation anomaly dip closest to the 1961–1990 average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-007", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2011. According to the monthly global precipitation anomaly dot plot for 2011, which month had the lowest precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-008", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2011. Using the dot plot, identify the quarter of 2011 with the most consistent positive precipitation anomalies.", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Q1 (Jan–Mar)", + "B. Q2 (Apr–Jun)", + "C. Q3 (Jul–Sep)", + "D. Q4 (Oct–Dec)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-009", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2011. According to the dot plot of monthly global precipitation anomalies, which of the following months in 2011 had the highest positive anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. June", + "C. August", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-010", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2012. According to the image, which month in 2012 showed the largest positive global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. July", + "D. September", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-011", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2012. Based on the dot plot, during which season (Northern Hemisphere) did global precipitation anomalies remain consistently below average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-012", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2012. From the given image, which month exhibited the lowest (most negative) global precipitation anomaly in 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. August", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-013", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2012. Looking at the seasonal precipitation pattern in the image, what can be inferred about the global precipitation anomaly trend from January to December 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increasing trend throughout the year", + "B. Decreasing trend throughout the year", + "C. Fluctuating anomalies with a mid-year dip", + "D. Consistently above average anomalies", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-014", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2012. According to the chart, during which quarter did global precipitation anomalies transition from above average to below average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Q1 (Jan–Mar)", + "B. Q2 (Apr–Jun)", + "C. Q3 (Jul–Sep)", + "D. Q4 (Oct–Dec)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-015", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2013. Based on the dot plot of global precipitation anomalies in 2013, which season experienced the highest positive anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-016", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2013. Looking at the dot plot for monthly precipitation anomalies in 2013, which month had the lowest anomaly value?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. July", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-017", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2013. According to the dot plot of monthly global precipitation anomalies in 2013, what was the general trend during Spring (Mar–May)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increasing anomalies", + "B. Stable anomalies", + "C. Decreasing anomalies", + "D. Fluctuating anomalies", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-018", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2013. Referencing the dot plot for 2013, which of the following months had a precipitation anomaly closest to the yearly average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. May", + "C. August", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-019", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2013. Based on the monthly anomaly dot plot, which season in 2013 had the most consistent anomaly values (least variation)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-020", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2014. During which month in 2014 did the global land-based precipitation anomaly appear to be the highest above average according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. July", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-021", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2014. Which season in 2014 showed the most negative precipitation anomaly globally based on the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-022", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2014. Looking at the dot plot for 2014, which of the following months had precipitation anomalies closest to the 1961–1990 average (i.e., near zero anomaly)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. April", + "C. June", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-023", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2014. According to the dot plot, which quarter of 2014 had the highest average global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Jan–Mar", + "B. Apr–Jun", + "C. Jul–Sep", + "D. Oct–Dec", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-024", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2014. Based on the dot plot of global precipitation anomalies in 2014, which month showed the lowest anomaly value across the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. September", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-025", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2015. According to the dot plot of global precipitation anomaly in 2015, which month had the highest positive precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. April", + "C. May", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-026", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2015. Which season (3-month period) in 2015 showed the most negative global precipitation anomaly based on the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-027", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2015. Based on the dot plot, which month in 2015 showed the lowest global precipitation anomaly value?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. August", + "C. October", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-028", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2015. In which season did the global precipitation anomaly shift from negative to positive in 2015, according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter to Spring", + "B. Spring to Summer", + "C. Summer to Autumn", + "D. Autumn to Winter", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-029", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2015. According to the dot plot of global monthly precipitation anomalies in 2015, which of the following sequences correctly ranks the seasons from wettest to driest?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter > Autumn > Spring > Summer", + "B. Autumn > Winter > Spring > Summer", + "C. Spring > Autumn > Winter > Summer", + "D. Summer > Spring > Autumn > Winter", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-030", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2016. During which month of 2016 did Australia experience its lowest precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. May", + "C. June", + "D. September", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-031", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2016. Based on the precipitation anomaly plot for 2016, which month had the highest positive precipitation anomaly globally?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. May", + "C. June", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-032", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2016. According to the precipitation anomaly plot, which month showed a noticeable increase in rainfall in the Sahel region, including flooding in Niger?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. July", + "B. August", + "C. September", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-033", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2016. Which of the following months showed a global negative precipitation anomaly corresponding with reports of drought in Finland and Norway?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. August", + "B. September", + "C. October", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-034", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2016. What month had a significant positive precipitation anomaly likely influenced by heavy rainfall in the Yangtze basin and The Netherlands?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. May", + "C. June", + "D. July", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-035", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2017. Which month in 2017 had the highest global precipitation anomaly according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-036", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2017. During which season (MAM, JJA, SON, DJF) did the global precipitation anomaly in 2017 show the lowest values?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. MAM (March–May)", + "B. JJA (June–August)", + "C. SON (September–November)", + "D. DJF (December–February)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-037", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2017. What was the global precipitation anomaly trend during the second half of 2017 (July to December)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increasing", + "B. Decreasing", + "C. Fluctuating with no clear trend", + "D. Constant", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-038", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2017. Which of the following months had a below-average global precipitation anomaly in 2017?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. August", + "C. November", + "D. May", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-039", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2017. Based on the dot plot, which season had the most above-average global precipitation anomalies in 2017?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. DJF (December–February)", + "B. MAM (March–May)", + "C. JJA (June–August)", + "D. SON (September–November)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-040", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2018. According to the dot plot of global precipitation anomaly for 2018, which season had the highest overall global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-041", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2018. Based on the dot plot, which month in 2018 had the lowest global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. June", + "C. July", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-042", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2018. Examine the dot plot for 2018: during which season did the global precipitation anomaly transition from predominantly above average to below average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-043", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2018. According to the dot plot of global precipitation anomaly for 2018, which month had the highest positive anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-044", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2018. Reviewing the dot plot for global precipitation anomalies in 2018, during which quarter did the anomalies show the most fluctuation month-to-month?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-045", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2019. During which month of 2019 did the global precipitation anomaly reach its highest positive value?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-046", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2019. What was the global precipitation anomaly in June 2019 compared to other months of that year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was among the highest", + "B. It was average", + "C. It was among the lowest", + "D. It was zero", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-047", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2019. Looking at the precipitation anomaly dot plot for 2019, which season (Northern Hemisphere) had the most consistent above-average precipitation anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-048", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2019. According to the global precipitation anomaly chart, which month had a negative anomaly following a notably high positive anomaly the previous month?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. May", + "C. July", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-049", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2019. Which quarter of 2019 (Jan–Mar, Apr–Jun, Jul–Sep, Oct–Dec) had the lowest average global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Jan–Mar", + "B. Apr–Jun", + "C. Jul–Sep", + "D. Oct–Dec", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-050", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2020. Which month in 2020 shows the highest global precipitation anomaly according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. December", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-051", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2020. During which season did the global precipitation anomaly appear to be the lowest in 2020?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-052", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2020. Based on the dot plot, which quarter of 2020 had the most consistent positive precipitation anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Jan-Mar", + "B. Apr-Jun", + "C. Jul-Sep", + "D. Oct-Dec", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-053", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2020. Which month in 2020 had a negative global precipitation anomaly despite floods in Bangladesh and Nepal?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-054", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2020. What was the general trend of global precipitation anomalies during the second half of 2020 (Jul-Dec)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Mostly increasing", + "B. Mostly decreasing", + "C. Stable with minor fluctuations", + "D. Alternating positive and negative anomalies", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-055", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2021. Which season in 2021 showed the highest global precipitation anomaly based on the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-056", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2021. During which season of 2021 was the global precipitation anomaly the lowest according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-057", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2021. Based on the dot plot, which month in 2021 had a precipitation anomaly closest to zero?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. May", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-058", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2021. According to the dot plot, which of the following months had the highest positive precipitation anomaly in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. July", + "C. August", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-059", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2021. Which three consecutive months in 2021 had a consistent increasing trend in global precipitation anomaly according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. March–May", + "C. May–July", + "D. September–November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-060", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2022. Which season in 2022 showed the highest global precipitation anomaly according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec 2021–Feb 2022)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-061", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2022. During which season in 2022 did global precipitation anomaly appear to be the lowest or most negative?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec 2021–Feb 2022)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-062", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2022. Based on the dot plot, which month in 2022 had the greatest positive global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. May", + "C. September", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-063", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2022. According to the dot plot, what was the general trend of global precipitation anomaly during the summer months (June–August) of 2022?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increasing anomaly each month", + "B. Decreasing anomaly each month", + "C. Consistently below average", + "D. Consistently above average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-064", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2022. Which season had the most consistent monthly precipitation anomaly values according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec 2021–Feb 2022)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Fall (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-065", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2023. Which month in 2023 showed the highest global precipitation anomaly according to the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. June", + "C. August", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-066", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2023. During which season (Northern Hemisphere) did the global precipitation anomaly remain consistently above average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-067", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2023. Which month in 2023 had the lowest global precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. May", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-068", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2023. What was the global precipitation anomaly trend during the second half of 2023 (July to December)?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Mostly increasing", + "B. Mostly decreasing", + "C. Highly variable", + "D. Stayed near average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-069", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2023. During which month did the global precipitation anomaly likely reflect the impact of Cyclone Mocha and heavy rain in Pakistan and India?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-070", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2024. Which season had the highest global precipitation anomaly in 2024 based on the dot plot?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-071", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2024. During which season did the global precipitation anomaly reach its lowest point in 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-072", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2024. Which of the following months had a precipitation anomaly above the global average for 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-073", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2024. Which season in 2024 had the most consistent (least variable) monthly global precipitation anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec-Feb)", + "B. Spring (Mar-May)", + "C. Summer (Jun-Aug)", + "D. Fall (Sep-Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-precipitation_anomaly-074", + "Text": "You are given visualization for monthly global climate anomaly of precipitation in 2024. Based on the dot plot, which month in 2024 had a global precipitation anomaly closest to zero?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Precipitation anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. May", + "C. August", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/seasonal_term/Perception/Seasonal_comparison.json b/jsons/Atmosphere/seasonal_term/Perception/Seasonal_comparison.json new file mode 100644 index 0000000000000000000000000000000000000000..b474b569b8e9e9e5dd87039a40eececad7e3be8a --- /dev/null +++ b/jsons/Atmosphere/seasonal_term/Perception/Seasonal_comparison.json @@ -0,0 +1,4547 @@ +[ + { + "Question_id": "seasonal_term-seasonal_comparison-000", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which season in 2010 saw the transition from El Niño to La Niña and how did this affect global ocean surface temperatures?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter; resulted in the warmest ocean temperatures on record", + "B. Spring; ocean temperatures peaked due to El Niño", + "C. Summer; ocean temperatures cooled as La Niña developed", + "D. Autumn; ocean temperatures reached their annual peak", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-001", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. During which period of 2010 did the globally averaged ocean surface temperature rank the 10th warmest on record, reflecting the full establishment of La Niña conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. September–November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-002", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which season in Australia during 2010 was its coolest spring on record due to La Niña's influence?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March–May", + "B. June–August", + "C. September–November", + "D. December–February", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-003", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which region experienced extreme heat during the summer (June–August) of 2010, leading to its warmest summer on record?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Canada", + "B. Australia", + "C. Russia", + "D. China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-004", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. When did Pakistan experience devastating flooding due to heavy rainfall associated with monsoonal patterns and blocking systems in 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April–May", + "B. June–July", + "C. July–August", + "D. September–October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-005", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2010. Which hemisphere experienced the warmest winter (December–February) on record in 2010?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere", + "B. Southern Hemisphere", + "C. Canada", + "D. Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-006", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. Which months in 2011 had the coolest global temperature anomalies due to the ongoing La Niña at the start of the year?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January and February", + "B. March and April", + "C. May and June", + "D. November and December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-007", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. During which months did global temperature anomalies increase, coinciding with a transition to ENSO-neutral conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January to March", + "B. May to September", + "C. October to December", + "D. June to November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-008", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. How did the return of La Niña in October 2011 affect global temperature anomalies in the final quarter of the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Temperatures warmed significantly", + "B. Temperatures remained steady", + "C. Temperatures cooled compared to mid-year values", + "D. No noticeable impact was observed", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-009", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. Which season in Australia was recorded as the coolest since 2001 due to the La Niña conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (June–August)", + "B. Summer (December 2010–February 2011)", + "C. Autumn (March–May)", + "D. Spring (September–November)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-010", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. What pattern of precipitation was observed in Australia during the first part of 2011?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Exceptionally dry conditions", + "B. Normal precipitation levels", + "C. Record wet conditions including the wettest March on record", + "D. Sporadic rainfall with long dry spells", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-011", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2011. What was the trend in precipitation in Central America during October 2011?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Drought conditions prevailed", + "B. Near-normal rainfall", + "C. Extremely heavy rainfall from two storm systems", + "D. Below-average precipitation due to El Niño", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-012", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. Which month in 2012 had the highest global land temperature anomaly?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. September", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-013", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. What trend did the global ocean temperature anomaly show throughout 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Steady increase from January to December", + "B. Peaked in January and declined steadily", + "C. Peaked in September with smaller monthly variations", + "D. Showed extreme monthly fluctuations like land temperatures", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-014", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. Which seasonal transition in the Northern Hemisphere marked a shift to widespread warmer-than-average temperatures in 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter to Spring", + "B. Spring to Summer", + "C. Summer to Autumn", + "D. Autumn to Winter", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-015", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. Which month in 2012 recorded the only globally-averaged record warm temperature for land and ocean surfaces?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-016", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. During which part of the year did drought conditions peak in the United States in 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. May", + "C. July", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-017", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. What was the general precipitation pattern in Australia during the second half of 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Above average rainfall due to La Niña", + "B. Below average rainfall due to ENSO-neutral and Indian Ocean dipole", + "C. Record flooding from monsoon", + "D. No significant deviation from average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-018", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2012. How did the Arctic Oscillation (AO) affect Eurasian temperatures late in 2012?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Made them warmer than average", + "B. Had no impact", + "C. Caused extreme cold from November through December", + "D. Increased rainfall across Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-019", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which month in 2013 had the highest global land temperature anomaly?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. August", + "C. November", + "D. January", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-020", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. During which season did the contiguous United States experience its first cooler-than-average season since winter 2010/11?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Fall", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-021", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which season did Australia record its warmest on record in 2013?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Summer (Dec–Feb)", + "B. Winter (Jun–Aug)", + "C. Spring (Sep–Nov)", + "D. Fall (Mar–May)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-022", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which country experienced record-breaking rainfall in early April 2013, resulting in one of its worst weather disasters?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. India", + "B. Argentina", + "C. China", + "D. Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-023", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which region experienced the most intense and extended flooding in the Danube and Elbe river catchments since at least 1950 during late spring to early summer?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Africa", + "B. Eastern United States", + "C. Central Europe", + "D. South Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-024", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which month in 2013 had the highest global ocean temperature anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-025", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2013. Which season contributed to Argentina’s second warmest year on record due to an extreme heat wave?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Fall", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-026", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which month in 2014 had the highest global land temperature anomaly?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-027", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. During which consecutive months in 2014 did the global ocean surface temperature either tie or surpass the all-time record anomaly prior to 2014?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–June", + "B. May–November", + "C. April–October", + "D. June–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-028", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which six months in 2014 were record warm globally for land and ocean surfaces?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January, March, June, July, November, December", + "B. February, May, June, August, October, December", + "C. May, June, August, September, October, December", + "D. April, May, July, August, November, December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-029", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. What was the trend in land temperature anomalies from February to March 2014?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Decreased by over 1°C", + "B. Remained nearly constant", + "C. Increased by over 1°C", + "D. Dropped slightly then increased", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-030", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which month in 2014 had the lowest global monthly land temperature anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. July", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-031", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which month in 2014 had the highest global ocean surface temperature anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. June", + "B. July", + "C. August", + "D. September", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-032", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2014. Which season in Europe contributed significantly to its warmest year on record in 2014?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Summer", + "B. Winter", + "C. Spring", + "D. Both B and C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-033", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which part of 2015 experienced the highest monthly global temperature anomaly on record?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. July", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-034", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. During which consecutive months in 2015 did the global ocean temperatures set new all-time monthly records?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May to July", + "B. August to October", + "C. February to April", + "D. November to January", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-035", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which months in 2015 had the largest difference in global land temperature anomalies?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January and December", + "B. March and August", + "C. June and December", + "D. April and November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-036", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. When did the strong El Niño conditions, which contributed to the record warmth, begin to develop in 2015?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere winter", + "B. Northern Hemisphere spring", + "C. Northern Hemisphere summer", + "D. Northern Hemisphere autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-037", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which season in Australia during 2015 was among the three warmest on record due to El Niño and Indian Ocean warmth?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (June–August)", + "B. Spring (September–November)", + "C. Summer (December–February)", + "D. Autumn (March–May)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-038", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2015. Which month in 2015 marked Australia's driest February on record in terms of precipitation?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-039", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Which months in 2016 experienced the highest global land surface temperature anomalies?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January, February, March", + "B. February, March, April", + "C. March, April, May", + "D. April, May, June", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-040", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. How did global ocean temperature anomalies change from January to December in 2016?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. They remained constant throughout the year", + "B. They increased steadily over the year", + "C. They decreased slightly from January to December", + "D. They fluctuated dramatically month to month", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-041", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Which part of the year 2016 contributed most to the record global temperatures due to El Niño?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January to March", + "B. April to June", + "C. July to September", + "D. October to December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-042", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. Which continent experienced its wettest May and second wettest June in 2016, following a dry April?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Europe", + "B. South America", + "C. Australia", + "D. North America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-043", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. In which month did Argentina experience heavy rainfall and flooding due to record-breaking precipitation in 2016?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. July", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-044", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2016. During which months did the Yangtze basin in China experience consistent high rainfall leading to severe flooding in 2016?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January to March", + "B. March to May", + "C. April to July", + "D. August to November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-045", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which month in 2017 experienced the highest global temperature anomaly, despite the absence of an El Niño?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. June", + "D. September", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-046", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. How did global temperatures trend during the second half of 2017 after peaking earlier in the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Increased steadily", + "B. Declined sharply", + "C. Decreased gradually but remained among the warmest", + "D. Remained constant", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-047", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which region experienced a shift from wetter-than-average conditions early in 2017 to drier conditions by the end of the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Australia", + "B. New Zealand", + "C. Europe", + "D. South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-048", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which season in France during 2017 ranked as the second warmest since national records began in 1900?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-049", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. What significant precipitation event occurred in the Dominican Republic in March 2017?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Record low rainfall for March", + "B. Record high snowfall", + "C. March precipitation total was nearly double the average", + "D. March precipitation was 96% above average, breaking records", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-050", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. Which month in 2017 had record-breaking rainfall in parts of Canada, especially in Ottawa?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-051", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2017. In Portugal, which part of the year saw the most significant precipitation deficit contributing to one of its driest years on record?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–December", + "C. June–August", + "D. October–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-052", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which month in 2018 experienced record-breaking temperatures in both France and Pakistan?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. July", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-053", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which region experienced its warmest January on record in 2018?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Australia", + "B. South America", + "C. New Zealand", + "D. Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-054", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. During which month of 2018 did the Arctic Circle experience unusually high temperatures exceeding 30°C?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. May", + "C. July", + "D. September", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-055", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. In which month did France experience its wettest January since 1959 with precipitation 80% above average?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-056", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which month in 2018 saw unusually high March temperatures across central and southern Asia, with some areas reaching May or June-like conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. February", + "B. March", + "C. April", + "D. May", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-057", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which region had its driest July on record in 2018, receiving only 60% of its long-term average rainfall?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Australia", + "B. Mexico", + "C. Argentina", + "D. South Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-058", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2018. Which country experienced its second wettest June since 2000, with 150% of normal precipitation?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201812.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. United Kingdom", + "B. Portugal", + "C. France", + "D. Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-059", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which months in 2019 were record warm globally, contributing significantly to the annual high temperature anomaly?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January and February", + "B. June and July", + "C. April and May", + "D. November and December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-060", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. What seasonal transition occurred in the ENSO phase during 2019, and how might that have influenced global temperature trends?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. La Niña to El Niño, cooling global temperatures", + "B. Neutral to strong El Niño, warming temperatures", + "C. Weak-to-moderate El Niño to ENSO-neutral, sustaining warm anomalies", + "D. Strong El Niño to La Niña, increasing precipitation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-061", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which continent experienced severe heat waves in both June and July 2019, setting multiple national temperature records?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Asia", + "C. Europe", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-062", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. During which season did India experience its wettest monsoon since 1994, contributing to a significant precipitation anomaly?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Spring", + "B. Summer", + "C. Fall", + "D. Winter", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-063", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. In which month did South America experience exceptionally heavy rainfall in northern Argentina and southern Brazil, setting new records?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. May", + "D. July", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-064", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which country experienced a prolonged dry spell during the late summer season, registering 34 consecutive dry days from mid-August to late September?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Australia", + "B. France", + "C. New Zealand", + "D. Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-065", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2019. Which region had its driest year on record in 2019, largely due to a strong positive Indian Ocean Dipole and consistent heatwaves throughout the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. South America", + "B. Asia", + "C. Oceania", + "D. Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-066", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which month in 2020 had the smallest global temperature anomaly compared to the 20th-century average?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. May", + "C. September", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-067", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. During which season did Canada experience unusually warm temperatures, including Montreal’s record May heat?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-068", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which months in 2020 were record warm globally according to the NOAA report?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January, June, October", + "B. January, May, September", + "C. February, July, November", + "D. March, August, December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-069", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. What trend was observed in the global temperature anomalies from January to December of 2020?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Steady increase throughout the year", + "B. Steady decrease throughout the year", + "C. High anomalies early in the year with a slight decline by December", + "D. Low anomalies early in the year with a sudden increase in December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-070", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which region experienced a heat wave in April 2020, with a national record temperature set in Cuba?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. Africa", + "C. Caribbean", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-071", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. When did La Niña conditions develop during 2020, potentially influencing seasonal temperature patterns?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. April", + "C. August", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-072", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2020. Which months had record warm temperatures in Mexico during 2020?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March, June, October", + "B. May, July, November", + "C. February, April, December", + "D. January, September, December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-073", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which month in 2021 had the lowest global temperature anomaly of the year?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-074", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which month marked North America's warmest June on record in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-075", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. In South America, which month had the highest temperature anomaly compared to all other months in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. August", + "B. September", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-076", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which month in Europe marked the second warmest June on record in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. May", + "C. June", + "D. July", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-077", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which two months in Oceania were among the four warmest for their respective months despite a generally cooler start to 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March and April", + "B. May and June", + "C. July and August", + "D. October and November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-078", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. In Asia, which month saw the highest temperature anomaly of the year in 2021?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-079", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2021. Which month in 2021 had the driest conditions in the Northern Rockies and Plains region of the U.S. due to a major heatwave?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202112.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. May", + "B. June", + "C. July", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-080", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which month in 2022 had the highest global temperature departure from the 20th century average?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. March", + "B. July", + "C. August", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-081", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. In North America, which month in 2022 had the warmest temperature departure?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. August", + "B. September", + "C. July", + "D. June", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-082", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. For South America, which month in 2022 recorded the highest temperature departure?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. May", + "C. July", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-083", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which continent experienced its highest monthly temperature departure in April 2022?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Asia", + "C. Oceania", + "D. South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-084", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which region had a below-average temperature in November 2022, making it the only such month for that region in the year?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Oceania", + "C. Asia", + "D. South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-085", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. Which month had the largest precipitation anomalies in eastern Australia, contributing to extreme flooding?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-086", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2022. During which season did Europe experience widespread drought and wildfires due to warm and dry conditions?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-087", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which consecutive months in 2023 were all the warmest on record globally, contributing to the year's record-breaking warmth?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–June", + "B. March–August", + "C. June–December", + "D. July–November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-088", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which continent experienced its warmest September on record, with temperatures exceeding those in July and August?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. South America", + "C. Europe", + "D. North America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-089", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. During which season did the Northern Hemisphere experience the largest positive seasonal temperature anomaly on record?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Spring (March–May)", + "B. Summer (June–August)", + "C. Autumn (September–November)", + "D. Winter (December–February)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-090", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which month had the largest positive global monthly temperature anomaly on record during 2023?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. July", + "B. August", + "C. September", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-091", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. What was the coldest month of the year for North America in 2023?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. February", + "C. March", + "D. April", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-092", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which region had its smallest temperature anomaly in May 2023, making it the coolest May since 2011?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Oceania", + "C. Asia", + "D. Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-093", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2023. Which month in 2023 had the smallest temperature anomaly for Antarctica, making it the third-coldest such month on record?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. March", + "C. August", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-094", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which season in the Northern Hemisphere recorded the highest temperature anomaly in 2024?", + "Variable": "temperature and precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-095", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. During which quarter of 2024 did global monthly temperature records begin to fall below 2023 records?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January–March", + "B. April–June", + "C. July–September", + "D. September–December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-096", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which continent experienced the largest monthly temperature anomaly in May 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Asia", + "C. South America", + "D. Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-097", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. In which season did Oceania experience its largest positive temperature anomaly in 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Summer", + "B. Autumn", + "C. Winter", + "D. Spring", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-098", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which region had the greatest contrast between wet and dry conditions during 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. South America", + "B. Africa", + "C. Asia", + "D. Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-099", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. When did the global ocean temperature streak of record highs end in 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. June", + "C. August", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-seasonal_comparison-100", + "Text": "You are given visualization for monthly global climate anomaly of temperature and precipitation in 2024. Which hemisphere recorded record warm temperatures for every season in 2024?", + "Variable": "precipitation", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-prcp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Seasonal comparison", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere", + "B. Southern Hemisphere", + "C. Both", + "D. Neither", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/seasonal_term/Perception/Temperature_anomaly_identification.json b/jsons/Atmosphere/seasonal_term/Perception/Temperature_anomaly_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..cef4ff4c2ddbbe574f3fba3479c611024c725d08 --- /dev/null +++ b/jsons/Atmosphere/seasonal_term/Perception/Temperature_anomaly_identification.json @@ -0,0 +1,2477 @@ +[ + { + "Question_id": "seasonal_term-temp_anomaly-000", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2010. In which season of 2010 did Canada experience its warmest temperature anomaly since national records began?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (December–February)", + "B. Spring (March–May)", + "C. Summer (June–August)", + "D. Autumn (September–November)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-001", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2010. What was the temperature anomaly during Australia's spring (September–November) in 2010?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 1.23°C below normal", + "B. 1.35°C below normal", + "C. 0.19°C above normal", + "D. 0.30°C below normal", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-002", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2010. What was the temperature anomaly recorded in December 2010 for the UK, marking the coldest December in more than 100 years?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 5°C below the 1971–2000 average", + "B. 1.35°C below normal", + "C. 0.6°C below average", + "D. 9°C above average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-003", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2010. During the summer of 2010, which country recorded its warmest summer on record since national records began in 1898?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Canada", + "B. Japan", + "C. Australia", + "D. Finland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-004", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2010. In 2010, India's mean annual temperature anomaly was reported as the warmest since records began. What was the anomaly value above the 1961–1990 average?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 0.93°C", + "B. 0.62°C", + "C. 0.73°C", + "D. 0.49°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-005", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2011. What was the global temperature anomaly for 2011 compared to the 20th century average?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 0.51°C above average", + "B. 1.0°C above average", + "C. 0.92°F above average", + "D. 0.64°C above average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-006", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2011. Which region experienced the greatest above-average annual temperature anomalies in 2011?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere high latitude land areas", + "B. Eastern and central Pacific Ocean", + "C. Southern Hemisphere", + "D. North America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-007", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2011. What was the primary reason for Australia’s cooler-than-average year in 2011?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. La Niña conditions", + "B. High-pressure systems", + "C. Arctic Oscillation", + "D. Solar minimum", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-008", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2011. Which month in 2011 had the warmest global ocean temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. July", + "B. December", + "C. January", + "D. October", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-009", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2011. Which country had its warmest autumn on record in 2011?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Norway", + "B. Finland", + "C. United Kingdom", + "D. Spain", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-010", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2012. Based on the 2012 temperature anomaly dot plot, which month showed the highest land temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. December", + "B. April", + "C. June", + "D. August", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-011", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2012. During 2012, which ocean surface temperature anomaly was recorded as the highest in the year?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. January", + "B. September", + "C. March", + "D. November", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-012", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2012. Referring to the anomaly data, which region experienced the most significant below-average temperatures during December 2012?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere land areas", + "B. Arctic Seas", + "C. Parts of Siberia and Eurasia", + "D. Central North America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-013", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2012. From the anomaly dot plot, which season in the Northern Hemisphere was notably warmer than average in 2012?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-014", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2012. Based on the anomaly data, which climate pattern was associated with the extreme cold experienced in Eurasia at the end of 2012?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. El Niño", + "B. Arctic Oscillation (AO) negative phase", + "C. La Niña", + "D. Pacific Decadal Oscillation", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-015", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2013. Which month in 2013 had the highest global average land temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. April", + "B. August", + "C. November", + "D. January", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-016", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2013. What was the global ocean temperature anomaly during September 2013?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. +0.40°C", + "B. +0.48°C", + "C. +0.56°C", + "D. +0.62°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-017", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2013. Which region experienced record warm temperatures during summer 2013?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Mexico", + "B. Siberia", + "C. Greenland", + "D. South Korea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-018", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2013. In 2013, which country observed its warmest year since national records began?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Argentina", + "B. Finland", + "C. Australia", + "D. Switzerland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-019", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2013. What was the temperature anomaly for Russia during its record warm November 2013?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. 4.6°C above average", + "B. 2.75°C above average", + "C. 5.3°C above average", + "D. 1.20°C above average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-020", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2014. Based on the seasonal temperature anomalies shown in the image for 2014, which region experienced record warmth during the boreal summer (June–August)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western United States", + "B. Eastern Canada", + "C. Central Russia", + "D. Southern Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-021", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2014. From the seasonal dot plot of temperature anomalies for 2014, which ocean region shows the highest anomaly during the austral winter (June–August)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Southern Indian Ocean", + "B. Central equatorial Pacific", + "C. South Atlantic off the coast of Brazil", + "D. Norwegian and Barents Seas", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-022", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2014. According to the image, during boreal spring (March–May), which of the following regions experienced below-average temperature anomalies?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Central North America", + "B. Northern Africa", + "C. Western Europe", + "D. Eastern China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-023", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2014. Referencing the seasonal anomalies in the image, which part of the globe had record cold temperature anomalies during the austral spring (September–November)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Near Antarctica in the Southern Ocean", + "B. Western equatorial Pacific", + "C. Gulf of Alaska", + "D. Indian Ocean south of Indonesia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-024", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2014. From the 2014 seasonal anomaly image, which of these regions showed consistent record warmth across all seasons?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Far East Russia into western Alaska", + "B. Central South America", + "C. Central Asia", + "D. Southeastern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-025", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2015. Based on the temperature anomaly dot plot for 2015, which month showed the highest global ocean temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. August", + "B. September", + "C. October", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-026", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2015. During 2015, which continent experienced its warmest year on record according to the report?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Africa", + "B. Asia", + "C. South America", + "D. Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-027", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2015. Referring to the temperature anomalies in the dot plot for 2015, which region in the Northern Hemisphere notably contributed to the record warmth in land surfaces?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Arctic Ocean", + "B. Western North Atlantic", + "C. Eastern Siberia", + "D. Southern Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-028", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2015. Looking at the anomaly values from the dot plot, which month in 2015 had the second highest land temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. July", + "B. November", + "C. December", + "D. June", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-029", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2015. Based on the dot plot, which statement best describes the global temperature trend in 2015?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201501.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201502.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201503.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201504.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201505.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201506.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201507.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201508.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201509.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201510.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201511.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201512.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. It was the coldest year in decades.", + "B. It had anomalies close to the 20th-century average.", + "C. It was one of the warmest years on record, with significant monthly and annual anomalies.", + "D. The anomalies were highly variable, with no clear trend.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-030", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2016. What was the approximate temperature anomaly in the Northern Pacific near Alaska during 2016?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Much cooler than average", + "B. Near average", + "C. Much warmer than average", + "D. Cooler than average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-031", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2016. Which of the following regions showed record warm anomalies in the Southern Hemisphere winter and spring due to the negative phase of the Indian Ocean Dipole (IOD)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Eastern Europe", + "B. Southern and eastern Indian Ocean near Southeast Asia", + "C. Western United States", + "D. Northern Atlantic Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-032", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2016. What temperature anomaly is observed in the Drake Passage near the Antarctic Peninsula in 2016?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Record warm", + "B. Near average", + "C. Record cold", + "D. Slightly warmer than average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-033", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2016. During 2016, what seasonal anomaly was recorded across Central America and northern South America?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Much cooler than average", + "B. Record warmth", + "C. Slightly above average", + "D. Below average", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-034", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2016. Which of the following regions displayed cooler-than-average temperatures at any point in 2016 according to the anomaly map?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201601.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201602.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201603.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201604.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201605.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201606.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201607.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201608.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201609.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201610.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201611.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201612.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western Canada", + "B. Eastern United States", + "C. Southern tip of South America", + "D. East of the Drake Passage near Antarctica", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-035", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2017. Based on the 2017 temperature anomaly dot plot, which region experienced the warmest anomalies during March 2017?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western and central Pacific Ocean", + "B. Northern Europe", + "C. Central Africa", + "D. Eastern Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-036", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2017. According to the 2017 dot plot, what was the approximate temperature anomaly in the southwestern contiguous United States during the summer months?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Around -0.5°C", + "B. Near 0.0°C", + "C. Between +1.5°C and +2.0°C", + "D. Greater than +3.0°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-037", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2017. From the seasonal temperature anomaly dot plot for 2017, what anomaly value is observed in southern South America during the Southern Hemisphere summer (Dec 2016–Feb 2017)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Around -1.0°C", + "B. Between +1.0°C and +1.5°C", + "C. Near 0.0°C", + "D. Greater than +2.5°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-038", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2017. Referring to the dot plot of temperature anomalies in 2017, which of the following regions had a notably cold anomaly during January?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Central Asia", + "B. Austria", + "C. South America", + "D. Southern Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-039", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2017. Looking at the 2017 seasonal dot plot, what was the general temperature anomaly in the Kingdom of Bahrain during July?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201701.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201702.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201703.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201704.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201705.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201706.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201707.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201708.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201709.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201710.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201711.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201712.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Slightly below average", + "B. Near average", + "C. Around +1.0°C", + "D. Around +3.0°C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-040", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2018. According to the dot plot of global temperature anomalies for 2018, which region recorded the highest positive temperature anomaly during the July heat wave?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Scandinavia", + "B. South America", + "C. North America", + "D. Antarctica", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-041", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2018. Based on the dot plot for 2018, which of the following regions had a temperature anomaly closest to +2.4°C during the year?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Alaska", + "B. Europe", + "C. Australia", + "D. Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-042", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2018. Reviewing the dot plot of 2018 temperature anomalies, which region had the coolest anomaly among those listed?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caribbean", + "B. Europe", + "C. Oceania", + "D. Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-043", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2018. Looking at the 2018 temperature anomaly dot plot, which area had one of the highest anomalies in April due to a heat wave?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. France", + "B. Canada", + "C. Greenland", + "D. Japan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-044", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2018. From the 2018 temperature anomaly dot plot, which of the following countries most likely had a recorded national temperature anomaly of approximately +2.2°C?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201801.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201802.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201803.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201804.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201805.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201806.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201807.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201808.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201809.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201810.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201811.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201812.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Germany", + "B. Mexico", + "C. China", + "D. United Kingdom", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-045", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2019. Based on the 2019 seasonal temperature anomaly dot plot, which continent experienced the highest positive temperature anomaly during the summer months (June–August)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Europe", + "B. Asia", + "C. Oceania", + "D. Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-046", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2019. According to the 2019 temperature anomaly dot plot, which region had notable below-average temperatures during January?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western Europe", + "B. Eastern China", + "C. Central Canada", + "D. Northern Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-047", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2019. From the dot plot of 2019 seasonal temperature anomalies, which of the following regions showed the most significant warming during February?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Eastern United States", + "B. Central Europe", + "C. Southern Africa", + "D. Eastern Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-048", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2019. Using the 2019 seasonal temperature anomaly dot plot, which region saw a significant positive anomaly during July?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Western Russia", + "B. Central South America", + "C. Greenland", + "D. Alaska", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-049", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2019. Based on the 2019 dot plot of seasonal temperature anomalies, which area experienced near-average or cooler-than-average temperatures during May?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201901.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201902.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201903.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201904.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201905.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201906.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201907.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201908.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201909.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201910.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201911.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-201912.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. France", + "B. Southeast Asia", + "C. Eastern Australia", + "D. Central Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-050", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2020. Based on the seasonal temperature anomaly dot plot for 2020, which region showed the highest positive temperature anomaly during the summer months (June–August)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. South America", + "C. Africa", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-051", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2020. According to the seasonal temperature anomaly map for 2020, which region experienced the least temperature anomaly during the winter months (December–February)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Europe", + "B. North America", + "C. Africa", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-052", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2020. Referring to the dot plot of seasonal temperature anomalies for 2020, which hemisphere (Northern or Southern) had overall higher temperature anomalies during the spring season (March–May)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere", + "B. Southern Hemisphere", + "C. Both had equal anomalies", + "D. Cannot be determined", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-053", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2020. Based on the seasonal anomaly image for 2020, which region had record-breaking high temperature anomalies during the fall season (September–November)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Caribbean", + "B. Europe", + "C. Australia", + "D. Antarctica", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-054", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2020. Using the seasonal temperature anomaly dot plot for 2020, which of the following regions showed a consistent above-average anomaly across all four seasons?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202001.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202002.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202003.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202004.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202005.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202006.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202007.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202008.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202009.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202010.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202011.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202012.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. Africa", + "C. South America", + "D. All of the above", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-055", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2021. According to the 2021 temperature anomaly dot plot, which region had a February temperature anomaly significantly below average, consistent with the cold Arctic air event described in the report?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern North America", + "B. Southern Africa", + "C. Southeast Asia", + "D. Central South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-056", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2021. Referencing the temperature anomaly dot plot for June 2021, which region likely shows the highest positive anomaly due to a record heat event?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. North America (northwest)", + "B. Antarctica", + "C. Northern Europe", + "D. Eastern Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-057", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2021. Based on the September 2021 anomalies shown in the dot plot, which continent likely exhibits the most extreme positive temperature departure?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. South America", + "B. Oceania", + "C. Europe", + "D. Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-058", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2021. Using the dot plot for April 2021, which region is expected to show below-average anomalies due to record low temperatures mentioned in the summary?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Central Europe", + "B. Northern Africa", + "C. Eastern Australia", + "D. Western South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-059", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2021. Looking at the August 2021 anomaly data, which region likely experienced a significant warm anomaly due to intense heat waves?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202101.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202102.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202103.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202104.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202105.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202106.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202107.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202108.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202109.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202110.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202111.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202112.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Southern Europe and Northern Africa", + "B. Central Canada", + "C. Eastern Russia", + "D. Southern South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-060", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2022. Based on the seasonal temperature anomaly values in the provided image for North America in 2022, which season experienced the highest temperature anomaly?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Fall", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-061", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2022. Referring to the image of seasonal temperature anomalies in 2022, which continent had the greatest positive temperature anomaly during the spring season?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. Europe", + "C. Africa", + "D. South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-062", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2022. According to the seasonal temperature anomaly image for 2022, which region showed a predominantly below-average anomaly during the winter season?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Antarctic region", + "B. Central Pacific Ocean", + "C. Northern Europe", + "D. Northern Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-063", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2022. Based on the seasonal anomaly values shown in the image, which season in Europe had the smallest temperature anomaly in 2022?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Summer", + "C. Fall", + "D. Spring", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-064", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2022. From the seasonal anomaly image, which continent had the coolest relative anomaly during the summer of 2022?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202201.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202202.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202203.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202204.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202205.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202206.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202207.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202208.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202209.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202210.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202211.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202212.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Oceania", + "B. Africa", + "C. Asia", + "D. South America", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-065", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2023. According to the dot plot of seasonal temperature anomalies in 2023, which hemisphere experienced the highest positive temperature anomaly during the Northern Hemisphere autumn (September–November)?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere", + "B. Southern Hemisphere", + "C. Equatorial Region", + "D. Antarctica", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-066", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2023. Based on the dot plot, which month in 2023 shows the highest global temperature anomaly on record?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. August", + "B. July", + "C. September", + "D. December", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-067", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2023. According to the dot plot, during which season did the global ocean temperatures reach record highs in multiple months in 2023?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Autumn (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-068", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2023. Referencing the dot plot, which continent had the greatest seasonal temperature anomaly in August 2023?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. North America", + "B. South America", + "C. Asia", + "D. Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-069", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2023. From the dot plot, which region showed a cooler-than-average seasonal anomaly during October and November 2023?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202301.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202302.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202303.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202304.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202305.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202306.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202307.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202308.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202309.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202310.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202311.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202312.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Fennoscandia (Norway, Sweden, Finland)", + "B. Eastern Asia", + "C. Central America", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-070", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2024. According to the dot plot of temperature anomalies, during which season did Europe experience the highest average temperature anomaly in 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter", + "B. Spring", + "C. Summer", + "D. Autumn", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-071", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2024. Based on the dot plot of seasonal temperature anomalies, which season in South America had the smallest temperature anomaly in 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Summer (Dec–Feb)", + "B. Autumn (Mar–May)", + "C. Winter (Jun–Aug)", + "D. Spring (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-072", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2024. Referring to the dot plot of seasonal temperature anomalies, which season in North America was the most anomalously warm in 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Winter (Dec–Feb)", + "B. Spring (Mar–May)", + "C. Summer (Jun–Aug)", + "D. Autumn (Sep–Nov)", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-073", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2024. Looking at the dot plot of seasonal temperature anomalies, which hemisphere experienced its warmest winter season in 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Northern Hemisphere", + "B. Southern Hemisphere", + "C. Both Hemispheres", + "D. Neither Hemisphere", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "seasonal_term-temp_anomaly-074", + "Text": "You are given visualization for monthly global climate anomaly of temperature in 2024. According to the seasonal anomaly dot plot, which continent had the largest summer temperature anomaly in 2024?", + "Variable": "temperature", + "Images": [ + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202401.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202402.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202403.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202404.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202405.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202406.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202407.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202408.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202409.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202410.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202411.png", + "raw/Atmosphere/atmosphere_final/LONG_EVENTS/map-blended-mntp-202412.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "seasonal term", + "L3-task": "Perception", + "L4-task": "Temperature anomaly identification", + "Dataset": "NOAA_reports", + "Answer Choices": [ + "A. Asia", + "B. Europe", + "C. Africa", + "D. Oceania", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Dynamic_feature_identification.json b/jsons/Atmosphere/short_term/Perception/Dynamic_feature_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..e38d243e9b7c241147b4d047536a14653a14a0d4 --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Dynamic_feature_identification.json @@ -0,0 +1,2918 @@ +[ + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. East europe", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Yes. East europe", + "(C) Central Europe", + "(D) West Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. North pacific", + "Answer Choices": [ + "(A) Yes. North pacific", + "(B) North Atlantic", + "(C) Indian Ocean", + "(D) South Atlantic", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. North pacific", + "Answer Choices": [ + "(A) Yes. North pacific", + "(B) South Atlantic", + "(C) Arctic Ocean", + "(D) Indian Ocean", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the northwest region", + "(C) Yes, near the central area", + "(D) Yes, centered over the southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, near the central area", + "(B) Yes, in the northeast region", + "(C) Yes, in the southwest region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the central region", + "(B) Yes, in the northwest region", + "(C) Yes, in the southeast region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northeast", + "(B) Yes, in the southwest", + "(C) Yes, in the central region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, near the center", + "(C) Yes, in the southeast region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, along the coastal area", + "(C) Yes, in the southwest region", + "(D) Yes, centered over the northeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, near the central area", + "(C) No", + "(D) Yes, centered over the southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southwest quadrant", + "(B) Yes, in the northeast region", + "(C) No", + "(D) Yes, centered in the middle of the region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. England", + "Answer Choices": [ + "(A) Scotland", + "(B) Ireland", + "(C) Yes. England", + "(D) Wales", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the northeast region", + "(C) Yes, near the central area", + "(D) Yes, in the southwest corner", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southwest region", + "(B) Yes, in the central region", + "(C) Yes, in the northeast region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, near the central area", + "(B) No", + "(C) Yes, in the southwest quadrant", + "(D) Yes, in the northeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the southwest quadrant", + "(C) Yes, centered over the central area", + "(D) Yes, in the northeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, near the central area", + "(C) Yes, centered over the southeast", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, centered over the region", + "(C) Yes, in the southeast region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, along the eastern coast", + "(C) Yes, in the central area", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the central area", + "(B) Yes, in the northwest region", + "(C) Yes, in the southeast quadrant", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. England", + "Answer Choices": [ + "(A) Wales", + "(B) Yes. England", + "(C) Scotland", + "(D) Ireland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. Eastern canada", + "Answer Choices": [ + "(A) Yes. Eastern canada", + "(B) Western Canada", + "(C) Greenland", + "(D) Eastern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) No", + "(C) Yes, in the southeast quadrant", + "(D) Yes, near the central area", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) Yes, in the central region", + "(C) No", + "(D) Yes, in the southeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. Eastern u.s.", + "Answer Choices": [ + "(A) Western U.S.", + "(B) Yes. Eastern u.s.", + "(C) Northern U.S.", + "(D) Central U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the northwest region", + "(C) Yes, near the center", + "(D) Yes, in the southeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, near the central area", + "(C) Yes, in the southwest region", + "(D) Yes, centered over the northeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the northwest region", + "(C) Yes, in the southeast region", + "(D) Yes, in the central region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the southwest quadrant", + "(C) Yes, in the northeast region", + "(D) Yes, centered over the coastline", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southwest", + "(B) Yes, in the center", + "(C) Yes, in the northeast", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "Yes. South australia", + "Answer Choices": [ + "(A) Victoria", + "(B) Western Australia", + "(C) Yes. South australia", + "(D) New South Wales", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest region", + "(B) No", + "(C) Yes, in the southeast corner", + "(D) Yes, near the central area", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the northwest", + "(B) Yes, in the central region", + "(C) Yes, in the southeast", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southwest quadrant", + "(B) No", + "(C) Yes, centered over the coastal area", + "(D) Yes, in the northeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southeast corner", + "(B) No", + "(C) Yes, centered over the main landmass", + "(D) Yes, in the northwest region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, centered over the mid-region", + "(B) Yes, in the northwest region", + "(C) Yes, in the southeast quadrant", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) No", + "(B) Yes, in the central region", + "(C) Yes, in the northwest", + "(D) Yes, in the southeast", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, centered over the southwest", + "(B) No", + "(C) Yes, located in the central area", + "(D) Yes, in the northeast region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the southwest area", + "(B) Yes, near the center", + "(C) Yes, in the northeast region", + "(D) No", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Dynamic_feature_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. Is there a vortex structure shown in the region? where is it located?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Dynamic feature identification", + "Dataset": "ERA5", + "Answer": "No", + "Answer Choices": [ + "(A) Yes, in the central area", + "(B) No", + "(C) Yes, near the southeastern edge", + "(D) Yes, in the northwest region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Event_evolution_analysis.json b/jsons/Atmosphere/short_term/Perception/Event_evolution_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..c382b85d061f08a4369c3df818c21b72baf5e424 --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Event_evolution_analysis.json @@ -0,0 +1,6302 @@ +[ + { + "Question_id": "Event evolution analysis/0", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/1", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Decay Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/2", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Transition Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/3", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/4", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/5", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Peak Phase", + "(C) Dissipating Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/6", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/7", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/8", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Decay Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/9", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Growth Phase", + "(B) Decay Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/10", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Onset Phase", + "(C) Transition Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/11", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Decay Phase", + "Answer Choices": [ + "(A) Growth Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/12", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/13", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/14", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/15", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/16", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/17", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/18", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/19", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Peak Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/20", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Decay Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/21", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/22", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/23", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Decay Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/24", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Decay Phase", + "(C) Dissipating Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/25", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/26", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/27", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Peak Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/28", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/29", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipating Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/30", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/31", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Growth Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/32", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/33", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/34", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/35", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Decay Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/36", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/37", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/38", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/39", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/40", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/41", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/42", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/43", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Peak Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/44", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Recovery Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/45", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Developing Phase", + "(D) Dissipating Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/46", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/47", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 8?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Growth Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/48", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Growth Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/49", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Transition Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/50", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Growth Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/51", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/52", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/53", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Transition Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/54", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/55", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/56", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/57", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/58", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/59", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/60", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Peak Phase", + "Answer Choices": [ + "(A) Dissipating Phase", + "(B) Peak Phase", + "(C) Onset Phase", + "(D) Recovery Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/61", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/62", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Peak Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/63", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/64", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Initiation Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/65", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/66", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Decay Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/67", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/68", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 3?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Growth Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/69", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipating Phase", + "(B) Initiation Phase", + "(C) Decay Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/70", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipating Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/71", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/72", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Peak Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/73", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/74", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/75", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/76", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/77", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 0?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Dissipation Phase", + "(D) Peak Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/78", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Growth Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/79", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Mature Phase", + "(C) Dissipating Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/80", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 2?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/81", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 5?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Decay Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/82", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 4?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Decay Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/83", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 1?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Decay Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/84", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Growth Phase", + "(D) Initiation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/85", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 7?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Dissipation Phase", + "(B) Mature Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/86", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 11?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Dissipation Phase", + "(C) Mature Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/87", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 9?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Mature Phase", + "(B) Dissipation Phase", + "(C) Initiation Phase", + "(D) Decay Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/88", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 10?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Growth Phase", + "(B) Initiation Phase", + "(C) Dissipation Phase", + "(D) Mature Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Event evolution analysis/89", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What phase is the event in at frame 6?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event evolution analysis", + "Dataset": "ERA5", + "Answer": "Initiation Phase", + "Answer Choices": [ + "(A) Initiation Phase", + "(B) Peak Phase", + "(C) Mature Phase", + "(D) Dissipation Phase", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Event_intensity_identification.json b/jsons/Atmosphere/short_term/Perception/Event_intensity_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..494d2691af2888403cfb31c7dd4725df5226e719 --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Event_intensity_identification.json @@ -0,0 +1,16268 @@ +[ + { + "Question_id": "short_term-Event_intensity_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 8~10 mm", + "(B) 0~1 mm", + "(C) 2~4 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at London in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Madrid in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mumbai in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Ulaanbaatar in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Nairobi in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cape Town in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Kinshasa in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Kinshasa in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 30~35 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Reykjavík in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Madrid in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mumbai in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_111.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Ulaanbaatar in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at London in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at London in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_111.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 7~9 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "30~35 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 35~40 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Ulaanbaatar in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_111.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_111.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Ulaanbaatar in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at London in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 3~5 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Moscow in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) -15~-10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_047.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 6~8 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Auckland in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Sydney in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Moscow in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Ulaanbaatar in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Buenos Aires in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at São Paulo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Berlin in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 0~1 mm", + "(B) 5~7 mm", + "(C) 2~4 mm", + "(D) 8~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_047.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -2~3 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "4~6 mm", + "Answer Choices": [ + "(A) 7~9 mm", + "(B) 4~6 mm", + "(C) 1~3 mm", + "(D) 10~12 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 5~7 mm", + "(C) 2~4 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cairo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mumbai in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Ulaanbaatar in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 6~8 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Ulaanbaatar in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) −5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Ulaanbaatar in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mumbai in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at London in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Auckland in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Sydney in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Sydney in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) -2~3 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Toronto in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 900~1000 hPa", + "(C) 950~1050 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mumbai in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mumbai in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Beijing in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 850~950 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Nairobi in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cairo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Cairo in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Ulaanbaatar in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Tokyo in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Wellington in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Sydney in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Kinshasa in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cape Town in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Nairobi in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Nairobi in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Cairo in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Wellington in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_027.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Wellington in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1150 hPa", + "(B) 950~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mumbai in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Beijing in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Wellington in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Wellington in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Wellington in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 950~1050 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Nairobi in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cape Town in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -15~-10 °C", + "(C) -20~-15 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Ulaanbaatar in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Madrid in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Kinshasa in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Kinshasa in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at London in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at London in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_039.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_039.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 6~8 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mumbai in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Sydney in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Auckland in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~1 mm", + "(C) 5~7 mm", + "(D) 8~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Sydney in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Moscow in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Madrid in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at São Paulo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at São Paulo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_027.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Lima in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -15~-10 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mumbai in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Nairobi in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cairo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 7~9 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Nairobi in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Auckland in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Auckland in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 0~1 mm", + "(B) 5~7 mm", + "(C) 2~4 mm", + "(D) 8~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Wellington in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Madrid in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Berlin in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at London in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 700~800 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Auckland in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Auckland in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -30~-25 °C", + "(C) -25~-20 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Beijing in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_043.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Tokyo in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Cape Town in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_035.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_035.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Lima in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at São Paulo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 2~4 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Auckland in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Auckland in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 700~800 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Reykjavík in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_031.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Moscow in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 25~30 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mumbai in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Beijing in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 980~990 hPa", + "(B) 1110~1150 hPa", + "(C) 950~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Lagos in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Nairobi in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Beijing in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Beijing in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1150 hPa", + "(B) 980~990 hPa", + "(C) 950~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Tokyo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_043.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Tokyo in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mumbai in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 950~1050 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Lagos in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Kinshasa in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Wellington in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Sydney in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Sydney in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Moscow in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Moscow in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 950~1050 hPa", + "(B) 800~900 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Lima in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Buenos Aires in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Cairo in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Kinshasa in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Nairobi in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Auckland in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Auckland in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Sydney in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Moscow in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 25~30 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Berlin in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-229", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Moscow in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "900~1000 hPa", + "Answer Choices": [ + "(A) 850~950 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-230", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-231", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-232", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-233", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 25~30 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-234", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-235", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at New York in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-236", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-237", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-238", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Toronto in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 900~1000 hPa", + "(C) 850~950 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-239", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-240", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-241", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at New York in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-242", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-243", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-244", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 1000~1100 hPa", + "(C) 800~900 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-245", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-246", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-247", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-248", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-249", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-250", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-251", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-252", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-253", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-254", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1100~1200 hPa", + "(B) 900~1000 hPa", + "(C) 1000~1100 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-255", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-256", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-257", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-258", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Toronto in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 800~900 hPa", + "(C) 1000~1100 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-259", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-260", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~9 mm", + "(B) 5~7 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-261", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-262", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-263", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-264", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Athens in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-265", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Madrid in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-266", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-267", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-268", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-269", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Toronto in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-270", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-271", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-272", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1100~1200 hPa", + "(C) 850~950 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-273", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-274", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-275", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 11~15 °C", + "(B) 0~4 °C", + "(C) 16~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-276", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-277", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-278", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-279", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-280", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-281", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-282", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~1000 hPa", + "(B) 1100~1200 hPa", + "(C) 1000~1100 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-283", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-284", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-285", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-286", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-287", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~9 mm", + "(B) 5~7 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-288", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-289", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 800~900 hPa", + "(C) 1100~1200 hPa", + "(D) 900~1000 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-290", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-291", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-292", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-293", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-294", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Reykjavík in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 1~3 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-295", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Athens in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 26~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-296", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-297", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Toronto in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 800~900 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-298", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Mexico City in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-299", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 21~25 °C", + "(B) 5~9 °C", + "(C) 15~20 °C", + "(D) 10~14 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-300", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 30~35 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-301", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 4~6 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-302", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Mexico City in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 800~900 hPa", + "(B) 1000~1100 hPa", + "(C) 900~1000 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-303", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Toronto in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-304", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-305", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 30~35 °C", + "(B) 25~30 °C", + "(C) 20~25 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-306", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 900~1000 hPa", + "(C) 850~950 hPa", + "(D) 1100~1200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-307", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-308", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Toronto in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-309", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-310", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-311", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 25~30 °C", + "(B) 15~20 °C", + "(C) 20~25 °C", + "(D) 30~35 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-312", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-313", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at New York in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-314", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Athens in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-315", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Berlin in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 4~6 mm", + "(C) 6~8 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-316", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at Athens in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 1000~1100 hPa", + "(B) 1100~1200 hPa", + "(C) 900~1000 hPa", + "(D) 800~900 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-317", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at Mexico City in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 20~25 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-318", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at Los Angeles in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-319", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Toronto in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "20~25 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-320", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum msl at New York in the short-term event?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "1000~1100 hPa", + "Answer Choices": [ + "(A) 900~950 hPa", + "(B) 1100~1200 hPa", + "(C) 950~1000 hPa", + "(D) 1000~1100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-321", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum t2m at New York in the short-term event?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "25~30 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 30~35 °C", + "(C) 25~30 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-322", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum tp1h at New York in the short-term event?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_intensity_identification-323", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. What is the range of maximum skt at Mexico City in the short-term event?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event intensity identification", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 20~25 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Event_localization.json b/jsons/Atmosphere/short_term/Perception/Event_localization.json new file mode 100644 index 0000000000000000000000000000000000000000..2f0e6b66c7d5cc2a8c77d9420f032513f1060164 --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Event_localization.json @@ -0,0 +1,6856 @@ +[ + { + "Question_id": "short_term-Event_localization-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Spain", + "Answer Choices": [ + "(A) Germany", + "(B) Spain", + "(C) Italy", + "(D) France", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southwest united states", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southwest United States", + "(C) Midwest United States", + "(D) Northeast United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Midwestern United States", + "(B) Northeastern United States", + "(C) Pacific Northwest", + "(D) Southern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Mid south united states", + "Answer Choices": [ + "(A) Mid South United States", + "(B) Pacific Northwest", + "(C) Northeast United States", + "(D) Southwest Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) Greenland", + "(B) Mexico", + "(C) Canada", + "(D) United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southwest united states", + "Answer Choices": [ + "(A) Great Lakes Region", + "(B) Northeast United States", + "(C) Southwest United States", + "(D) Pacific Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) Greenland", + "(B) Mexico", + "(C) Canada", + "(D) United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Eastern United States", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Mexico", + "Answer Choices": [ + "(A) Mexico", + "(B) California", + "(C) Texas", + "(D) Arizona", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southwest united states", + "Answer Choices": [ + "(A) Northeast United States", + "(B) Midwest United States", + "(C) Southwest United States", + "(D) Southeast United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) United States", + "(B) Mexico", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sahel region", + "Answer Choices": [ + "(A) Iberian Peninsula", + "(B) Balkans", + "(C) Central Europe", + "(D) Sahel region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Northeastern United States", + "(C) Southern United States", + "(D) Midwestern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Central Mexico", + "(B) Southeastern United States", + "(C) Eastern Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) Canada", + "(B) United States", + "(C) Mexico", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Central Canada", + "(C) Northern Mexico", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Middle united states", + "Answer Choices": [ + "(A) Western Canada", + "(B) Southern Mexico", + "(C) Northeastern United States", + "(D) Middle United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Central Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Western United States", + "(D) Central Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Southeastern Mexico", + "(B) Central Canada", + "(C) Western United States", + "(D) Eastern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Eastern Europe", + "(C) Northern Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Central Canada", + "(B) Northern Mexico", + "(C) Eastern United States", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western united states", + "Answer Choices": [ + "(A) Eastern United States", + "(B) Northern Mexico", + "(C) Central Canada", + "(D) Western United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Midwestern United States", + "(B) Pacific Northwest", + "(C) Northeastern United States", + "(D) Southern United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Mexico", + "Answer Choices": [ + "(A) Mexico", + "(B) California", + "(C) Florida", + "(D) Texas", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southern United States", + "(C) Great Lakes Region", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Southern United States", + "(C) Northeastern United States", + "(D) Great Lakes region", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Eastern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Southern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Middle united states", + "Answer Choices": [ + "(A) Pacific Northwest", + "(B) Northeastern Canada", + "(C) Southern Mexico", + "(D) Middle United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) United States", + "(B) Mexico", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) India", + "(B) Vietnam", + "(C) Thailand", + "(D) Bangladesh", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) Philippines", + "(B) Japan", + "(C) South Korea", + "(D) China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Portugal", + "Answer Choices": [ + "(A) Portugal", + "(B) France", + "(C) Italy", + "(D) Spain", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Mid north u.s.", + "Answer Choices": [ + "(A) Mid North U.S.", + "(B) Western U.S.", + "(C) Southern Canada", + "(D) Southeastern U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) U.S.", + "(C) Mexico", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) Canada", + "(C) Greenland", + "(D) U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Russia", + "Answer Choices": [ + "(A) Poland", + "(B) Ukraine", + "(C) Russia", + "(D) Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) Mexico", + "(C) Central America", + "(D) U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) China", + "(B) Thailand", + "(C) South Korea", + "(D) Japan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Canada", + "(C) Greenland", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "England", + "Answer Choices": [ + "(A) Ireland", + "(B) Belgium", + "(C) France", + "(D) England", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Ehiopia", + "Answer Choices": [ + "(A) Uganda", + "(B) Ehiopia", + "(C) Kenya", + "(D) Sudan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Ehiopia", + "Answer Choices": [ + "(A) Kenya", + "(B) Sudan", + "(C) Somalia", + "(D) Ehiopia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sudan", + "Answer Choices": [ + "(A) Ethiopia", + "(B) Nigeria", + "(C) Chad", + "(D) SUdan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Mexico", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Greenland", + "(C) Canada", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) Canada", + "(C) U.S.", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Turkey", + "Answer Choices": [ + "(A) Turkey", + "(B) Bulgaria", + "(C) Romania", + "(D) Greece", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) U.S.", + "(C) Greenland", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Italy", + "Answer Choices": [ + "(A) Germany", + "(B) Italy", + "(C) France", + "(D) Austria", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Philippines", + "Answer Choices": [ + "(A) Thailand", + "(B) Philippines", + "(C) Indonesia", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_111.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) U.S.", + "(C) Canada", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Saudi arabia", + "Answer Choices": [ + "(A) Pakistan", + "(B) Saudi Arabia", + "(C) Iran", + "(D) India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Portugal", + "Answer Choices": [ + "(A) Portugal", + "(B) Italy", + "(C) France", + "(D) Spain", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_111.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) U.S.", + "(C) Canada", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Greenland", + "(B) U.S.", + "(C) Mexico", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) U.S.", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_111.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Pakistan", + "Answer Choices": [ + "(A) Pakistan", + "(B) Bangladesh", + "(C) Nepal", + "(D) India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) Bangladesh", + "(B) Thailand", + "(C) Vietnam", + "(D) India", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Hungary", + "Answer Choices": [ + "(A) Hungary", + "(B) Austria", + "(C) Romania", + "(D) Slovakia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) Mexico", + "(C) Greenland", + "(D) U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Australia", + "Answer Choices": [ + "(A) Fiji", + "(B) Papua New Guinea", + "(C) Australia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Russia", + "Answer Choices": [ + "(A) Poland", + "(B) Germany", + "(C) Ukraine", + "(D) Russia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Philippine", + "Answer Choices": [ + "(A) Philippine", + "(B) Vietnam", + "(C) Thailand", + "(D) Malaysia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Argentina", + "Answer Choices": [ + "(A) Paraguay", + "(B) Uruguay", + "(C) Chile", + "(D) Argentina", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sardinia", + "Answer Choices": [ + "(A) Crete", + "(B) Corsica", + "(C) Sardinia", + "(D) Sicily", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) Greenland", + "(C) U.S.", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Afghanistan", + "Answer Choices": [ + "(A) Afghanistan", + "(B) Nepal", + "(C) India", + "(D) Pakistan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Greenland", + "(B) Mexico", + "(C) U.S.", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Mexico", + "(C) Canada", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) U.S.", + "(C) Canada", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Egypt", + "Answer Choices": [ + "(A) Egypt", + "(B) Libya", + "(C) Algeria", + "(D) Sudan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Jordan", + "Answer Choices": [ + "(A) Jordan", + "(B) Lebanon", + "(C) Syria", + "(D) Iraq", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) U.S.", + "(C) Greenland", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) U.S.", + "(C) Greenland", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Athens", + "Answer Choices": [ + "(A) Rome", + "(B) Berlin", + "(C) Athens", + "(D) Madrid", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Israel", + "Answer Choices": [ + "(A) Israel", + "(B) Lebanon", + "(C) Jordan", + "(D) Syria", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Canada", + "(B) U.S.", + "(C) Mexico", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Greenland", + "(C) Canada", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) Canada", + "(C) U.S.", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Italy", + "Answer Choices": [ + "(A) Italy", + "(B) Austria", + "(C) Germany", + "(D) France", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Japan", + "Answer Choices": [ + "(A) China", + "(B) South Korea", + "(C) Philippines", + "(D) Japan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "China", + "Answer Choices": [ + "(A) India", + "(B) China", + "(C) Thailand", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "China", + "Answer Choices": [ + "(A) Thailand", + "(B) India", + "(C) China", + "(D) Vietnam", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sweden", + "Answer Choices": [ + "(A) Norway", + "(B) Sweden", + "(C) Denmark", + "(D) Finland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Canada", + "(C) Greenland", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Mexico", + "(B) Canada", + "(C) U.S.", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Greenland", + "(B) Canada", + "(C) Mexico", + "(D) U.S.", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_047.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) Greenland", + "(B) U.S.", + "(C) Mexico", + "(D) Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_047.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s.", + "Answer Choices": [ + "(A) U.S.", + "(B) Greenland", + "(C) Canada", + "(D) Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern australia", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Northern Australia", + "(C) Southern Australia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t-850_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "U.s. & canada", + "Answer Choices": [ + "(A) U.S. & Canada", + "(B) Mexico", + "(C) Cuba", + "(D) Greenland", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t-850_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "East asia", + "Answer Choices": [ + "(A) Central Asia", + "(B) East Asia", + "(C) Southeast Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t-850_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sahel", + "Answer Choices": [ + "(A) Maghreb", + "(B) Horn of Africa", + "(C) Southern Africa", + "(D) Sahel", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t-850_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Western Europe", + "(B) Central Europe", + "(C) Eastern Europe", + "(D) Northern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Eastern u.s.", + "Answer Choices": [ + "(A) Southwestern U.S.", + "(B) Eastern U.S.", + "(C) Western Canada", + "(D) Pacific Northwest", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Eastern Asia", + "(B) Central Asia", + "(C) Western Asia", + "(D) South Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Australia", + "(B) Papua New Guinea", + "(C) Fiji", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t-850_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Eastern u.s.", + "Answer Choices": [ + "(A) Eastern U.S.", + "(B) Western Canada", + "(C) Southwestern U.S.", + "(D) Central Mexico", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Nigeria", + "(B) South Africa", + "(C) Morocco", + "(D) Kenya", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "China", + "Answer Choices": [ + "(A) India", + "(B) China", + "(C) South Korea", + "(D) Japan", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "France", + "Answer Choices": [ + "(A) France", + "(B) Italy", + "(C) Spain", + "(D) Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Nigeria", + "(B) Morocco", + "(C) Kenya", + "(D) South Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Northern Europe", + "(B) Eastern Europe", + "(C) Central Europe", + "(D) Western Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t-850_039.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) Indonesia", + "(B) China", + "(C) India", + "(D) Thailand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern australia", + "Answer Choices": [ + "(A) Southern Australia", + "(B) New Zealand", + "(C) Eastern Indonesia", + "(D) Northern Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t-850_011.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Uk", + "Answer Choices": [ + "(A) Germany", + "(B) UK", + "(C) France", + "(D) Netherlands", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t-850_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Argentina", + "Answer Choices": [ + "(A) Uruguay", + "(B) Argentina", + "(C) Chile", + "(D) Brazil", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t-850_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern and central china", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Northern India", + "(C) Southeast Asia", + "(D) Southern and Central China", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t-850_007.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Souther united states", + "Answer Choices": [ + "(A) Souther United States", + "(B) Pacific Northwest", + "(C) Great Lakes region", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) South Africa", + "(B) Morocco", + "(C) Kenya", + "(D) Nigeria", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Papua New Guinea", + "(B) Fiji", + "(C) New Zealand", + "(D) Australia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "France", + "Answer Choices": [ + "(A) France", + "(B) Italy", + "(C) United Kingdom", + "(D) Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t-850_015.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western australia", + "Answer Choices": [ + "(A) Western Australia", + "(B) Tasmania", + "(C) Eastern Australia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t-850_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Central Asia", + "(B) Eastern Asia", + "(C) South Asia", + "(D) Southeast Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t-850_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Sahel region", + "Answer Choices": [ + "(A) Sahel region", + "(B) Horn of Africa", + "(C) Southern Africa", + "(D) Central Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t-850_035.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "United states", + "Answer Choices": [ + "(A) Canada", + "(B) Greenland", + "(C) Mexico", + "(D) United States", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Argentina", + "Answer Choices": [ + "(A) Paraguay", + "(B) Chile", + "(C) Brazil", + "(D) Argentina", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t-850_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) New Zealand", + "(D) Papua New Guinea", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t-850_031.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t-850_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern china", + "Answer Choices": [ + "(A) Eastern Russia", + "(B) Southern China", + "(C) Northern India", + "(D) Central Mongolia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) Kenya", + "(B) Nigeria", + "(C) Egypt", + "(D) South Africa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t-850_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "India", + "Answer Choices": [ + "(A) Pakistan", + "(B) China", + "(C) India", + "(D) Thailand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t-850_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Eastern asia", + "Answer Choices": [ + "(A) Eastern Asia", + "(B) Southeast Asia", + "(C) South Asia", + "(D) Central Asia", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t-850_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Algeria", + "Answer Choices": [ + "(A) Nigeria", + "(B) Morocco", + "(C) Libya", + "(D) Algeria", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t-850_043.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern united states", + "Answer Choices": [ + "(A) Northeastern United States", + "(B) Pacific Northwest", + "(C) Southern United States", + "(D) Northern Canada", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t-850_019.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Southern anstralia", + "Answer Choices": [ + "(A) Northern Australia", + "(B) Southern Anstralia", + "(C) Eastern Indonesia", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t-850_011.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Uk", + "Answer Choices": [ + "(A) UK", + "(B) Netherlands", + "(C) France", + "(D) Germany", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t-850_019.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Argentina", + "Answer Choices": [ + "(A) Argentina", + "(B) Paraguay", + "(C) Chile", + "(D) Brazil", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t-850_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "South africa", + "Answer Choices": [ + "(A) South Africa", + "(B) Nigeria", + "(C) Kenya", + "(D) Egypt", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t-850_019.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "New zealand", + "Answer Choices": [ + "(A) Australia", + "(B) Fiji", + "(C) Papua New Guinea", + "(D) New Zealand", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_localization-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What is the evolving direction of the system?", + "Variable": "t-850", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t-850_011.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event localization", + "Dataset": "ERA5", + "Answer": "Western europe", + "Answer Choices": [ + "(A) Southern Europe", + "(B) Northern Europe", + "(C) Western Europe", + "(D) Eastern Europe", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Event_trend_analysis.json b/jsons/Atmosphere/short_term/Perception/Event_trend_analysis.json new file mode 100644 index 0000000000000000000000000000000000000000..55bb21ac1caddb8999b3d5c48cd1dc8ecf1f29ac --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Event_trend_analysis.json @@ -0,0 +1,15228 @@ +[ + { + "Question_id": "short_term-Event_trend_analysis-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Beijing change from 11 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 5~7 mm", + "(C) 0~1 mm", + "(D) 8~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 3 to 7 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 16 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 5~7 mm", + "(D) 7~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Ulaanbaatar change from 7 to 15 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-15~-10 °C", + "Answer Choices": [ + "(A) -25~-20 °C", + "(B) -15~-10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 11 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 5~7 mm", + "(C) 7~9 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 3 to 19 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 1 to 15 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 13 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 7~9 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 9 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 12~15 °C", + "(C) 5~10 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 7 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 8 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 2 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~2 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 2 to 6 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -3~-1 mm", + "(B) -2~0 mm", + "(C) 0~1 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 15 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 3 to 10 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -4~-2 mm", + "(B) 2~4 mm", + "(C) -2~0 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 4 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -2~2 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 0 to 1 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 5~7 mm", + "(C) 0~2 mm", + "(D) 7~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 4 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -2~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 9 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~10 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 4 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Nairobi change from 0 to 13 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Nairobi change from 8 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 5 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 0 to 11 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -15~-10 °C", + "(D) -2~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 6 to 14 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 6 to 8 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 0 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 10~12 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 13 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 25~30 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at London change from 19 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -5~-3 mm", + "(B) 3~5 mm", + "(C) 1~3 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at London change from 21 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Beijing change from 10 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~9 mm", + "(B) 5~7 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mumbai change from 16 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 0 to 37 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_111.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 18 to 42 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_111.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Tokyo change from 9 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mumbai change from 4 to 9 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Moscow change from 0 to 4 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 21 to 24 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_111.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 6~8 mm", + "(C) 4~6 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 13 to 14 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 1 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_111.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 1~3 mm", + "(C) 5~7 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 20 to 47 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_059.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_061.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_062.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_063.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_065.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_066.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_067.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_069.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_070.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_071.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_073.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_074.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_075.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_077.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_078.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_079.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_081.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_082.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_083.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_085.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_086.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_087.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_089.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_090.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_091.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_093.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_094.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_095.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_097.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_098.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_099.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_101.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_102.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_103.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_105.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_106.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_107.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_109.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_110.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_111.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 3 to 11 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -2~0 mm", + "(B) 3~5 mm", + "(C) -5~-3 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mumbai change from 20 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 10 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 6 to 39 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 5~7 mm", + "(C) -2~0 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Sydney change from 12 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~9 mm", + "(B) 5~7 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 6 to 8 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 1 to 7 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Beijing change from 7 to 10 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 2~4 mm", + "(C) 6~8 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 2 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Lima change from 8 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Athens change from 18 to 19 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 7~10 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 2 to 15 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 1~3 mm", + "(C) -2~0 mm", + "(D) -5~-3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 3 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 4 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 4 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 4 to 9 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 3 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 0~2 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 6 to 9 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 7~9 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 4 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Cairo change from 3 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 1~3 mm", + "(C) -5~-3 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 13 to 15 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 2 to 13 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 4 to 10 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 2~4 mm", + "(C) 0~2 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 3 to 16 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 11~15 °C", + "(B) 0~5 °C", + "(C) 6~10 °C", + "(D) 16~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 11 to 14 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 4 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~2 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 5 to 14 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 9 to 11 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 4 to 19 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 13 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 22 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 7~9 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 9 to 11 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 17 to 19 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 20 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 18 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 15 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Tokyo change from 8 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -2~0 mm", + "(B) -5~-3 mm", + "(C) 3~5 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Ulaanbaatar change from 10 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Tokyo change from 1 to 11 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) -2~0 mm", + "(C) 2~4 mm", + "(D) -4~-2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 17 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 21 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 1~3 mm", + "(B) 3~5 mm", + "(C) -2~0 mm", + "(D) -5~-3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 12 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Madrid change from 3 to 7 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 1 to 4 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 10 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -4~-2 mm", + "(B) 0~2 mm", + "(C) 2~4 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 36 to 44 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 5 to 26 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_047.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) −5~0 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 39 to 47 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_047.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Wellington change from 5 to 8 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 14 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 2 to 30 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_047.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 5 to 44 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -5~-2 mm", + "(B) 1~3 mm", + "(C) -2~0 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 46 to 47 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_047.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Sydney change from 18 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Wellington change from 6 to 11 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -5~-3 mm", + "(B) -2~0 mm", + "(C) 3~5 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Sydney change from 8 to 13 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) 50~100 hPa", + "(C) -100~0 hPa", + "(D) -150~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 11 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 3 to 10 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) -4~-2 mm", + "(C) 2~4 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 4 to 16 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) 300~400 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 4 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -2~2 °C", + "(C) -15~-12 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 18 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Ulaanbaatar change from 5 to 6 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -200~-100 hPa", + "(C) -100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Cairo change from 10 to 13 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -5~0 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Kinshasa change from 5 to 8 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 7 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at London change from 17 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Moscow change from 0 to 6 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) 0~50 hPa", + "(C) -100~0 hPa", + "(D) 100~150 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 6 to 15 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 19 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 4~6 mm", + "(C) 0~2 mm", + "(D) 2~4 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 1 to 6 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) −5~0 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Tokyo change from 15 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Ulaanbaatar change from 19 to 21 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Sydney change from 3 to 6 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) −5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Sydney change from 2 to 7 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Wellington change from 4 to 14 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) -100~0 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Nairobi change from 4 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Cairo change from 3 to 16 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) 0~50 hPa", + "(C) 50~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Kinshasa change from 2 to 5 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 4 to 6 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 8 to 10 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Sydney change from 6 to 23 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 16 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 16~20 °C", + "(B) 11~15 °C", + "(C) 0~4 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 10 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 8 to 10 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -200~-100 hPa", + "(C) 50~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Ulaanbaatar change from 7 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -20~-15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 14 to 19 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 1~3 mm", + "(B) 5~7 mm", + "(C) 3~5 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mumbai change from 19 to 20 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 0~100 hPa", + "(C) -100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Auckland change from 3 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 18 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 2~4 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 4~6 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Wellington change from 3 to 8 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) -50~0 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 12 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 11 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Toronto change from 5 to 13 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Cairo change from 13 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) -2~2 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Cairo change from 21 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 7~10 mm", + "(B) 5~7 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Nairobi change from 12 to 20 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 3 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -15~-10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 5 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 6~8 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-140", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Tokyo change from 14 to 16 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) 0~50 hPa", + "(C) -200~-100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-141", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Moscow change from 2 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-142", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Kinshasa change from 8 to 10 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_059.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-143", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Nairobi change from 13 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-144", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Cairo change from 3 to 23 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-145", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 0 to 8 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-146", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Athens change from 4 to 8 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-147", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Madrid change from 2 to 22 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) −100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-148", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 1 to 7 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_039.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-149", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Beijing change from 8 to 9 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_039.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 7~9 mm", + "(C) 5~7 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-150", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Beijing change from 17 to 23 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 201~300 hPa", + "(B) 0~100 hPa", + "(C) 101~200 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-151", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 15 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-152", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 7 to 15 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-153", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Wellington change from 9 to 10 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-154", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 8 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-155", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Lima change from 2 to 8 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_027.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-156", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Lima change from 7 to 14 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_027.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-157", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Lima change from 5 to 15 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) −100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-158", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Beijing change from 18 to 19 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-159", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Beijing change from 1 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 7~9 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-160", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Ulaanbaatar change from 4 to 20 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 300~400 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-161", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 3 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-162", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 4 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-163", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Toronto change from 6 to 18 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -150~-100 hPa", + "(C) 50~100 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-164", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Kinshasa change from 0 to 3 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-165", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Auckland change from 1 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-166", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 13 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "2~4 mm", + "Answer Choices": [ + "(A) 8~10 mm", + "(B) 0~1 mm", + "(C) 2~4 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-167", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Sydney change from 5 to 17 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -150~-100 hPa", + "(C) 50~100 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-168", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Athens change from 20 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 7~10 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-169", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at London change from 0 to 2 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 300~400 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-170", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Auckland change from 8 to 16 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-171", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 9 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) -2~0 mm", + "(C) -5~-3 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-172", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Sydney change from 0 to 3 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -100~0 hPa", + "(C) 50~100 hPa", + "(D) -150~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-173", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mumbai change from 11 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-174", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mumbai change from 3 to 15 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_043.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-175", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mumbai change from 11 to 23 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -150~-100 hPa", + "(B) -100~0 hPa", + "(C) 0~50 hPa", + "(D) 50~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-176", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Nairobi change from 15 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-177", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Kinshasa change from 10 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -2~0 mm", + "(B) 3~5 mm", + "(C) 1~3 mm", + "(D) -5~-3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-178", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Kinshasa change from 5 to 14 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -200~-100 hPa", + "(C) 50~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-179", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 12 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_035.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 6~8 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-180", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at São Paulo change from 1 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-181", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at São Paulo change from 2 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-182", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at São Paulo change from 11 to 19 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -150~-100 hPa", + "(B) 50~100 hPa", + "(C) -100~0 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-183", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 0 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) -2~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-184", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Auckland change from 7 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -2~0 mm", + "(B) 5~7 mm", + "(C) 3~5 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-185", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Wellington change from 9 to 11 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) -200~-100 hPa", + "(C) -100~0 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-186", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 6 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_031.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-187", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Athens change from 14 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_031.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-188", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at London change from 1 to 17 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) -50~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-189", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mumbai change from 13 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-190", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Tokyo change from 2 to 20 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-191", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Beijing change from 3 to 11 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 100~200 hPa", + "(C) -100~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-192", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Nairobi change from 0 to 2 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-193", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Cairo change from 5 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-194", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Kinshasa change from 9 to 22 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 50~100 hPa", + "(C) -100~0 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-195", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Ulaanbaatar change from 9 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_059.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-196", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 15 to 23 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 3~5 mm", + "(C) 7~10 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-197", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mumbai change from 1 to 12 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -150~-100 hPa", + "(C) 50~100 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-198", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Tokyo change from 14 to 17 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 5~10 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-199", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Ulaanbaatar change from 7 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_043.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 3~5 mm", + "(C) 9~11 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-200", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mumbai change from 13 to 21 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 300~400 hPa", + "(C) 200~300 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-201", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Nairobi change from 1 to 15 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-202", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 3 to 16 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-203", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 14 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_043.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 5~7 mm", + "(D) 7~9 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-204", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Wellington change from 19 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-205", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Sydney change from 0 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 3~5 mm", + "(C) 0~2 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-206", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Auckland change from 21 to 22 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 300~400 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-207", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 10 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) −5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-208", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Athens change from 0 to 10 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -150~-100 hPa", + "(C) 50~100 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-209", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Lima change from 1 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-210", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Lima change from 6 to 17 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 200~300 hPa", + "(C) 0~100 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-211", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Nairobi change from 13 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -5~-3 mm", + "(B) 1~3 mm", + "(C) 3~5 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-212", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Sydney change from 7 to 11 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-213", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Sydney change from 18 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 5~7 mm", + "(C) 0~2 mm", + "(D) 7~10 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-214", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Auckland change from 1 to 16 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) 200~300 hPa", + "(C) −100~0 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-215", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 6h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at London change from 3 to 15 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 100~200 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-216", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Athens change from 7 to 13 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 20~25 °C", + "(B) 0~2 °C", + "(C) 5~10 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-217", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Moscow change from 12 to 15 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-218", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Athens change from 0 to 14 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) -100~0 hPa", + "(C) 100~200 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-219", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 8 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 0~2 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-220", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 15 to 21 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "4~6 mm", + "Answer Choices": [ + "(A) 8~10 mm", + "(B) 0~2 mm", + "(C) 4~6 mm", + "(D) 12~14 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-221", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 13 to 17 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-222", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 11 to 22 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) -100~0 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-223", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 3 to 4 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-224", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 17 to 18 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-225", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 5 to 20 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "15~20 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 25~30 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-226", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 0 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-227", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 2 to 9 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 5~7 mm", + "(B) 7~10 mm", + "(C) 3~5 mm", + "(D) 0~2 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-228", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 6 to 17 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) -100~0 hPa", + "(C) 0~50 hPa", + "(D) -150~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-229", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 6 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 5~10 °C", + "(C) 10~15 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-230", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 0 to 5 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-231", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 12 to 13 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 300~400 hPa", + "(B) 0~100 hPa", + "(C) 200~300 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-232", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 4 to 22 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 6~10 °C", + "(C) 0~5 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-233", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 5 to 12 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) -10~-5 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-234", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 5 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-235", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 7 to 21 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~2 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-236", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at New York change from 10 to 13 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 300~400 hPa", + "(B) 100~200 hPa", + "(C) 200~300 hPa", + "(D) 0~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-237", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 9 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 15~20 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-238", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 0 to 23 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -2~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-239", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Toronto change from 10 to 20 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 50~100 hPa", + "(B) -150~-100 hPa", + "(C) -100~0 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-240", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 5 to 14 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 11~15 °C", + "(B) 16~20 °C", + "(C) 5~10 °C", + "(D) 1~3 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-241", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at New York change from 6 to 14 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 200~300 hPa", + "(C) −100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-242", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 3 to 5 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-243", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 1 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 0~2 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-244", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 7 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-245", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 4 to 11 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-246", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Athens change from 14 to 22 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 6~8 mm", + "(B) 9~11 mm", + "(C) 0~2 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-247", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 15 to 16 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) −5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-248", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 5 to 16 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 16~20 °C", + "(C) 11~15 °C", + "(D) 1~4 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-249", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 11 to 14 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-250", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 6 to 23 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~2 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-251", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 0 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 0~2 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-252", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 8 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-253", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 8 to 14 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-254", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 10 to 11 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 300~400 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-255", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 3 to 13 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) -2~0 mm", + "(C) 1~3 mm", + "(D) -5~-3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-256", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 9 to 19 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 2~5 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-257", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 17 to 21 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-258", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 0 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -5~-3 mm", + "(B) -2~0 mm", + "(C) 3~5 mm", + "(D) 1~3 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-259", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 0 to 21 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) -2~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-260", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 8 to 15 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 15~20 °C", + "(C) 10~15 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-261", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 2 to 11 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 1~3 mm", + "(B) 3~5 mm", + "(C) -5~-3 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-262", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 2 to 5 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -5~0 °C", + "(B) 0~5 °C", + "(C) 5~10 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-263", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at New York change from 15 to 22 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 300~400 hPa", + "(B) 100~200 hPa", + "(C) 0~100 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-264", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 1 to 4 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 5~10 °C", + "(C) -10~-5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-265", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 1 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 6~8 mm", + "(C) 3~5 mm", + "(D) 10~12 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-266", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 12 to 16 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 2~5 °C", + "(C) 20~25 °C", + "(D) 5~8 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-267", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 17 to 20 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 15~20 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-268", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 11 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 3~5 mm", + "(C) 6~8 mm", + "(D) 9~11 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-269", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 0 to 3 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -2~2 °C", + "(D) -15~-10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-270", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at New York change from 9 to 15 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 300~400 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-271", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Madrid change from 15 to 22 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -2~2 °C", + "(B) -15~-10 °C", + "(C) -10~-5 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-272", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Moscow change from 0 to 12 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 0~2 mm", + "(C) 9~11 mm", + "(D) 6~8 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-273", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 0 to 13 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) -5~0 °C", + "(D) -10~-5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-274", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 6 to 16 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 10~15 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-275", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 4 to 11 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 0~50 hPa", + "(B) -100~0 hPa", + "(C) -200~-100 hPa", + "(D) 50~100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-276", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 6 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 3~5 mm", + "(B) 7~10 mm", + "(C) 0~2 mm", + "(D) 5~7 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-277", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 2 to 10 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-278", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Toronto change from 1 to 6 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 200~300 hPa", + "(B) 0~100 hPa", + "(C) 100~200 hPa", + "(D) 300~400 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-279", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 0 to 8 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) -15~-10 °C", + "(C) -5~0 °C", + "(D) 0~5 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-280", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at New York change from 12 to 20 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -200~-100 hPa", + "(B) 0~100 hPa", + "(C) -100~0 hPa", + "(D) 100~200 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-281", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at New York change from 10 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 5~10 °C", + "(B) 0~5 °C", + "(C) 10~15 °C", + "(D) 15~20 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-282", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 8 to 17 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 20~25 °C", + "(C) 0~2 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-283", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Toronto change from 4 to 11 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~100 hPa", + "Answer Choices": [ + "(A) 0~100 hPa", + "(B) 300~400 hPa", + "(C) 100~200 hPa", + "(D) 200~300 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-284", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Mexico City change from 17 to 18 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) -5~0 °C", + "(C) 0~5 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-285", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Toronto change from 3 to 8 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-286", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 6 to 14 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) 100~200 hPa", + "(B) -100~0 hPa", + "(C) 0~100 hPa", + "(D) -200~-100 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-287", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 1 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "5~10 °C", + "Answer Choices": [ + "(A) 15~20 °C", + "(B) 0~2 °C", + "(C) 5~10 °C", + "(D) 10~15 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-288", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Mexico City change from 5 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) 1~3 mm", + "(B) 3~5 mm", + "(C) -5~-3 mm", + "(D) -2~0 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-289", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at New York change from 2 to 6 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-5~0 °C", + "Answer Choices": [ + "(A) -10~-5 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-290", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did msl at Mexico City change from 12 to 16 UTC?", + "Variable": "msl", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-100~0 hPa", + "Answer Choices": [ + "(A) -100~0 hPa", + "(B) -200~-100 hPa", + "(C) 50~100 hPa", + "(D) 0~50 hPa", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-291", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Moscow change from 15 to 23 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-10~-5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) -10~-5 °C", + "(C) -2~2 °C", + "(D) -15~-11 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-292", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at Moscow change from 3 to 16 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 9~11 mm", + "(B) 0~2 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-293", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 5 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~2 mm", + "Answer Choices": [ + "(A) 0~2 mm", + "(B) 9~11 mm", + "(C) 6~8 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-294", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Mexico City change from 9 to 19 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "10~15 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 3~5 °C", + "(C) 0~2 °C", + "(D) 20~25 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-295", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did t2m at Toronto change from 8 to 11 UTC?", + "Variable": "t2m", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 10~15 °C", + "(B) 5~10 °C", + "(C) 0~5 °C", + "(D) -5~0 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-296", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did tp1h at New York change from 16 to 17 UTC?", + "Variable": "tp1h", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "-2~0 mm", + "Answer Choices": [ + "(A) -2~0 mm", + "(B) 1~3 mm", + "(C) -5~-3 mm", + "(D) 3~5 mm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_trend_analysis-297", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 1h and starting time is 00:00:00 UTC, variable names are noted in image title. How much did skt at Toronto change from 2 to 22 UTC?", + "Variable": "skt", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event trend analysis", + "Dataset": "ERA5", + "Answer": "0~5 °C", + "Answer Choices": [ + "(A) 0~5 °C", + "(B) 10~15 °C", + "(C) 15~20 °C", + "(D) 5~10 °C", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Event_type_identification.json b/jsons/Atmosphere/short_term/Perception/Event_type_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..5da28f2be61a001271b989e1a92a5ead7087c08f --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Event_type_identification.json @@ -0,0 +1,6628 @@ +[ + { + "Question_id": "short_term-Event_type_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Dust storm", + "(B) Microburst", + "(C) Heat burst", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Heat burst", + "(D) Tropical depression", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Microburst", + "(C) Thunderstorm", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Dust storm", + "(B) Thunderstorm", + "(C) Heat burst", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Microburst", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Heat burst", + "(B) Flash flood", + "(C) Dust storm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Microburst", + "(B) Thunderstorm", + "(C) Heat burst", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Hailstorm", + "(B) Cold front", + "(C) Heat burst", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Heat burst", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical depression", + "(C) Cold front", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical depression", + "(C) Thunderstorm", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Microburst", + "(B) Cold front", + "(C) Dust storm", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Tropical depression", + "(B) Heat burst", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical depression", + "(C) Thunderstorm", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Tropical depression", + "(C) Heat burst", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Tornado", + "(B) Heat burst", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Dust storm", + "(B) Heat burst", + "(C) Cold front", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Dust storm", + "(B) Heat burst", + "(C) Tropical storm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Tornado", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat burst", + "(C) Cold front", + "(D) Microburst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Microburst", + "(B) Cold front", + "(C) Heat burst", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Cold front", + "(B) Thunderstorm", + "(C) Heat burst", + "(D) Tropical depression", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Heat burst", + "(B) Microburst", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Cold front", + "(C) Heat burst", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Dust storm", + "(B) Heat burst", + "(C) Microburst", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Microburst", + "(C) Cold front", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Cold front", + "(C) Heat burst", + "(D) Tropical depression", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Microburst", + "(C) Heat burst", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Dust storm", + "(C) Cold front", + "(D) Heat burst", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/skt_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Heat burst", + "Answer Choices": [ + "(A) Heat burst", + "(B) Microburst", + "(C) Thunderstorm", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/00_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Snow squall", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/01_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Cold front", + "(C) Thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/02_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tornado", + "(B) Flash flood", + "(C) Severe thunderstorm", + "(D) Hailstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/03_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Hailstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/04_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/05_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tropical storm", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/06_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/07_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/08_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Flash flood", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/09_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Hailstorm", + "(B) Tornado", + "(C) Flash flood", + "(D) Severe thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-041", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/10_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Dust storm", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-042", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/11_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Severe thunderstorm", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-043", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/12_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-044", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/13_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-045", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/14_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Cold front", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-046", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/15_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Dust storm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-047", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/16_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Flash flood", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-048", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/17_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Tornado", + "(C) Severe thunderstorm", + "(D) Hailstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-049", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/18_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Dust storm", + "(C) Thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-050", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/19_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Cold front", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-051", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/20_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-052", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/21_6h/tp1h_108.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Snowstorm", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Heatwave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-053", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/22_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Tornado", + "(C) Flash flood", + "(D) Severe thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-054", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/23_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-055", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/24_6h/tp1h_108.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-056", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/25_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Dust storm", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-057", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/26_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Hailstorm", + "(C) Tornado", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-058", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/t2m_108.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_060.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_064.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_068.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_072.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_076.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_080.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_084.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_088.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_092.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_096.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_100.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_104.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/27_6h/tp1h_108.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-059", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/28_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-060", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/29_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Hailstorm", + "(B) Tornado", + "(C) Flash flood", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-061", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/30_6h/tp1h_044.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Dust storm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-062", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/31_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-063", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/32_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Heat wave", + "(C) Dust storm", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-064", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/33_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Hailstorm", + "(C) Thunderstorm", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-065", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/34_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Cold front", + "(C) Flash flood", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-066", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/35_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Dust storm", + "(C) Thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-067", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/36_6h/tp1h_044.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tornado", + "(B) Hailstorm", + "(C) Flash flood", + "(D) Severe thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-068", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/37_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Snow squall", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-069", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/38_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Severe thunderstorm", + "(C) Tornado", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-070", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/39_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Dust storm", + "(C) Flash flood", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-071", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/40_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Tornado", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-072", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/41_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Thunderstorm", + "(C) Tornado", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-073", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/42_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-074", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/43_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Flash flood", + "(C) Thunderstorm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-075", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/44_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Dust storm", + "(C) Thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-076", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/45_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Tornado", + "(C) Heat wave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-077", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/46_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tornado", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-078", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/47_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-079", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/48_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-080", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/49_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Heat wave", + "(C) Severe thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-081", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/50_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Snow squall", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-082", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/51_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Tornado", + "(B) Heat wave", + "(C) Severe thunderstorm", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-083", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/52_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Flash flood", + "(C) Heat wave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-084", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/53_1h/tp1h_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Flash flood", + "(C) Heat wave", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-085", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/54_1h/tp1h_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Flash flood", + "(B) Thunderstorm", + "(C) Dust storm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-086", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/55_1h/tp1h_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tornado", + "(C) Heat wave", + "(D) Flash flood", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-087", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/56_6h/tp1h_044.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Flash flood", + "(C) Heat wave", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-088", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/57_6h/tp1h_044.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Flash flood", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-089", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 4 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/58_1h/tp1h_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Dust storm", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-090", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/59_6h/tp1h_044.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Heat wave", + "(B) Thunderstorm", + "(C) Flash flood", + "(D) Tornado", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-091", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/flash_flood/60_6h/tp1h_044.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Flash flood", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Flash flood", + "(C) Heat wave", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-092", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-093", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/v10_040.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-094", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Heatwave", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-095", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/v10_056.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Front passage", + "(C) Heat wave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-096", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/v10_024.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Tropical cyclone", + "(C) Front passage", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-097", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Tropical cyclone", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-098", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/v10_056.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-099", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Front passage", + "(C) Heat wave", + "(D) Cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-100", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-101", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-102", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/10_6h/v10_024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Tropical cyclone", + "(C) Heat wave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-103", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/11_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-104", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/12_6h/v10_056.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Fog event", + "(B) Front passage", + "(C) Thunderstorm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-105", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/13_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-106", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/14_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Front passage", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-107", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/15_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Tropical cyclone", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-108", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/16_6h/v10_056.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heatwave", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-109", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/17_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Front passage", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-110", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/18_6h/v10_056.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-111", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/19_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Tropical cyclone", + "(C) Heat wave", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-112", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/20_6h/v10_036.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Front passage", + "(C) Heatwave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-113", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/21_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Heatwave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-114", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/22_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Tropical cyclone", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-115", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/23_6h/v10_024.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Heatwave", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-116", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/24_6h/v10_056.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heatwave", + "(B) Front passage", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-117", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/25_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-118", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/26_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Front passage", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-119", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/27_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-120", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/28_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Tropical cyclone", + "(C) Thunderstorm development", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-121", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/29_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-122", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/30_6h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Heat wave", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-123", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/31_6h/v10_056.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-124", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/32_6h/v10_032.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-125", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/33_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-126", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/34_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Hurricane", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-127", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/35_6h/v10_028.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Tropical cyclone", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-128", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/36_6h/v10_056.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Hurricane", + "(C) Thunderstorm", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-129", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/37_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Front passage", + "(C) Thunderstorm", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-130", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/tp1h_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/u10_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/38_6h/v10_056.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Front passage", + "(C) Heat wave", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-131", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/39_6h/v10_040.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Tropical cyclone", + "(C) Heat wave", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-132", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/40_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-133", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/tp1h_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/u10_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/41_6h/v10_040.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Heat wave", + "(C) Front passage", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-134", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/42_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Front passage", + "(C) Heat wave", + "(D) Dust storm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-135", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/43_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Tropical cyclone", + "(B) Thunderstorm", + "(C) Heat wave", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-136", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/44_6h/v10_020.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Cyclone", + "(B) Heat wave", + "(C) Thunderstorm", + "(D) Front passage", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-137", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/45_6h/v10_020.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Heat wave", + "(B) Front passage", + "(C) Fog formation", + "(D) Thunderstorm", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-138", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/46_6h/v10_020.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Thunderstorm", + "(B) Heat wave", + "(C) Front passage", + "(D) Tropical cyclone", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "short_term-Event_type_identification-139", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a short_term event. Temporal resolution of 24 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What type of short-term event is most likely occurring in this region?", + "Variable": null, + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/tp1h_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/u10_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/47_6h/v10_020.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Event type identification", + "Dataset": "ERA5", + "Answer": "Front passage", + "Answer Choices": [ + "(A) Front passage", + "(B) Thunderstorm", + "(C) Tropical cyclone", + "(D) Heat wave", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Atmosphere/short_term/Perception/Thermodynamic_feature_identification.json b/jsons/Atmosphere/short_term/Perception/Thermodynamic_feature_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..9211ef60f53ab53cac13681b1632efa99aeb60cb --- /dev/null +++ b/jsons/Atmosphere/short_term/Perception/Thermodynamic_feature_identification.json @@ -0,0 +1,2909 @@ +[ + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-001", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/00_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Warm front", + "(B) Stationary front", + "(C) Occluded front", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-002", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/01_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Occluded front", + "(B) Warm front", + "(C) Cold front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-003", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/02_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Warm front", + "(C) Occluded front", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-004", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/03_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Occluded front", + "(B) Cold front", + "(C) Warm front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-005", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/04_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Warm front", + "(B) Cold front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-006", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/05_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Cold front", + "(B) Stationary front", + "(C) Occluded front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-007", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/06_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Warm front", + "(B) Stationary front", + "(C) Cold front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-008", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/07_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Cold front", + "(B) Warm front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-009", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/08_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Warm front", + "Answer Choices": [ + "(A) Warm front", + "(B) Cold front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-010", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/09_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Cold front", + "(B) Warm front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-011", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/10_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Cold front", + "(C) Warm front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-012", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/11_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Occluded front", + "(B) Warm front", + "(C) Stationary front", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-013", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/12_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Occluded front", + "(C) Warm front", + "(D) Cold front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-014", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/13_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Cold front", + "(C) Occluded front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-015", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/14_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Occluded front", + "(B) Warm front", + "(C) Cold front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-016", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/15_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Warm front", + "(B) Occluded front", + "(C) Cold front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-017", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/16_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Stationary front", + "(B) Occluded front", + "(C) Warm front", + "(D) ", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-018", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/17_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) ", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-019", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/18_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Occluded front", + "(B) ", + "(C) Stationary front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-020", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/19_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Occluded front", + "(B) Cold front", + "(C) ", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-021", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/20_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) ", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-022", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/21_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Occluded front", + "(B) Warm front", + "(C) ", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-023", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/22_1h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Occluded front", + "(B) Warm front", + "(C) ", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-024", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/23_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) ", + "(B) Stationary front", + "(C) Warm front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-025", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/24_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Stationary front", + "(B) ", + "(C) Warm front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-026", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/25_1h/t2m_023.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Cold frontold", + "(B) Occluded front", + "(C) Stationary front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-027", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/26_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Occluded front", + "(B) Stationary front", + "(C) Warm front", + "(D) Cold frontold", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-028", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/27_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Cold front", + "(B) ", + "(C) Stationary front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-029", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/28_1h/t2m_023.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Warm front", + "(B) Stationary front", + "(C) Occluded front", + "(D) Cold frontold", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-030", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 1 hour and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/heat_burst/29_1h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) Occluded front", + "(B) ", + "(C) Warm front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-031", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/00_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Stationary front", + "(B) Warm front", + "(C) Cold frontold", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-032", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/01_6h/t2m_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Cold frontold", + "(B) Stationary frontold", + "(C) Occluded frontold", + "(D) Warm frontold", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-033", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/02_6h/t2m_043.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold frontold", + "Answer Choices": [ + "(A) Cold frontold", + "(B) Occluded front", + "(C) Stationary front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-034", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/03_6h/t2m_059.png" + ], + "Ground Truth": "D", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Warm front", + "(B) Cold front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-035", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/04_6h/t2m_027.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Stationary front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Cold front", + "(C) Warm front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-036", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/05_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Occluded front", + "(C) Cold front", + "(D) Warm front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-037", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_024.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_025.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_026.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_027.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_028.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_029.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_030.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_031.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_032.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_033.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_034.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_035.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_036.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_037.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_038.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_039.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_040.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_041.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_042.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_043.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_044.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_045.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_046.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_047.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_048.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_049.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_050.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_051.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_052.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_053.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_054.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_055.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_056.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_057.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_058.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/06_6h/t2m_059.png" + ], + "Ground Truth": "A", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "", + "Answer Choices": [ + "(A) ", + "(B) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-038", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/07_6h/t2m_023.png" + ], + "Ground Truth": "C", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Warm front", + "(C) Cold front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-039", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/08_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Cold front", + "Answer Choices": [ + "(A) Stationary front", + "(B) Cold front", + "(C) Warm front", + "(D) Occluded front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SHORT_EVENTS-Thermodynamic_feature_identification-040", + "Text": "The provided image sequence represent the evolution of atmosphere variables in a SHORT_EVENTS event. Temporal resolution of 6 hours and starting time is 00:00:00 UTC, variable names are noted in image title. What kind of front shown in the region?", + "Variable": "", + "Images": [ + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/msl_023.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_000.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_001.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_002.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_003.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_004.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_005.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_006.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_007.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_008.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_009.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_010.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_011.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_012.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_013.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_014.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_015.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_016.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_017.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_018.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_019.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_020.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_021.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_022.png", + "raw/Atmosphere/atmosphere_final/SHORT_EVENTS/region/front_passage/09_6h/t2m_023.png" + ], + "Ground Truth": "B", + "L1-task": "Atmosphere", + "L2-task": "short term", + "L3-task": "Perception", + "L4-task": "Thermodynamic feature identification", + "Dataset": "ERA5", + "Answer": "Warm front", + "Answer Choices": [ + "(A) Cold front", + "(B) Warm front", + "(C) Occluded front", + "(D) Stationary front", + "(E) Unable to decide" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_counting.json b/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_counting.json new file mode 100644 index 0000000000000000000000000000000000000000..8321970eb6262f46a9b57cd101a588678040b08b --- /dev/null +++ b/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_counting.json @@ -0,0 +1,17390 @@ +[ + { + "Question_id": "Dead Oil Palm identification/0000", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1341_257.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0001", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 5", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4373_3549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0002", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3295_3885.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0003", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 12", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10747_2371.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0004", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13606_3450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0005", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2030_2309.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0006", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7084_1243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0007", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7516_1178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0008", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5852_1836.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0009", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/432_3336.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0010", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 8", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10172_1970.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0011", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10465_340.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0012", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12503_3842.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0013", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12763_3276.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0014", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 5", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5435_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0015", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13188_3817.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0016", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4501_623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0017", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7246_198.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0018", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8233_2875.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0019", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9776_561.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0020", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2693_3950.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0021", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6048_1881.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0022", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/750_2656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0023", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8540_505.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0024", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6410_1244.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0025", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/999_1174.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0026", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1235_3022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0027", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1132_2848.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0028", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1406_2471.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0029", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 11", + "(C) 2", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3989_1900.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0030", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12985_2885.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0031", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 4", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4921_2502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0032", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 8", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6971_2427.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0033", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11736_1091.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0034", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7781_2136.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0035", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10093_275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0036", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10179_2308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0037", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3780_983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0038", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7880_1167.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0039", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11878_3438.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0040", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9960_3046.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0041", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12862_1693.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0042", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1354_3681.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0043", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5162_1696.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0044", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5590_3365.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0045", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7838_1110.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0046", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13470_3421.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0047", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4387_1123.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0048", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 10", + "(C) 11", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12755_2449.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0049", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 9", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13973_2202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0050", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4047_572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0051", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12470_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0052", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8253_117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0053", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2548_827.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0054", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 9", + "(C) 1", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3344_1960.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0055", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/837_1368.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0056", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9184_62.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0057", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 10", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7842_926.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0058", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 10", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4033_3844.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0059", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 10", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2045_821.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0060", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9392_490.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0061", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 11", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11080_2359.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0062", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 5", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8102_4.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0063", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/224_2436.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0064", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1437_2853.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0065", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1971_2626.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0066", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11006_294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0067", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12159_2154.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0068", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/258_3667.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0069", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 17", + "(B) 8", + "(C) 2", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10425_2415.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0070", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9418_526.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0071", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 15", + "(C) 2", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10681_2799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0072", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12813_261.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0073", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7473_338.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0074", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/681_2527.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0075", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7424_3117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0076", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9144_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0077", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5888_2583.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0078", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2203_1178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0079", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9168_537.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0080", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 11", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3213_2658.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0081", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12367_3724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0082", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8045_1880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0083", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/89_835.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0084", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 2", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13464_2251.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0085", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1180_279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0086", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3565_1720.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0087", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2538_3391.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0088", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1039_954.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0089", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12451_3578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0090", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1359_2155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0091", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7326_1350.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0092", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2371_502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0093", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10136_3488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0094", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7666_2830.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0095", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1093_3474.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0096", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6622_348.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0097", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9677_3243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0098", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3071_892.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0099", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 3", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6186_2598.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0100", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 7", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12531_315.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0101", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12403_731.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0102", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5643_1030.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0103", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7781_2601.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0104", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9806_160.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0105", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4223_762.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0106", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6919_1889.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0107", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4932_3550.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0108", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10752_3.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0109", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5694_2272.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0110", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11954_986.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0111", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 2", + "(C) 1", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4378_2436.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0112", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1109_3501.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0113", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6795_1383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0114", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7004_214.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0115", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3926_314.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0116", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2094_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0117", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3201_3053.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0118", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 11", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12347_3008.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0119", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 8", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6502_1801.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0120", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1507_2889.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0121", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9751_3618.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0122", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2253_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0123", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2063_3702.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0124", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2888_3606.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0125", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11914_1279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0126", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 7", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10674_1059.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0127", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7147_1799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0128", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 5", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5102_664.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0129", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12909_1830.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0130", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/435_2765.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0131", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7523_3125.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0132", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2358_1921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0133", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3183_638.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0134", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1315_615.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0135", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 13", + "(B) 17", + "(C) 8", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10484_2578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0136", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10755_1082.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0137", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/280_2519.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0138", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 9", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10919_3457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0139", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10386_3670.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0140", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 4", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5294_3954.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0141", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 11", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12087_2293.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0142", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/122_298.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0143", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2977_3804.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0144", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 2", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1048_865.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0145", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3192_1119.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0146", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1411_3795.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0147", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10368_1325.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0148", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10981_3440.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0149", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 7", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4249_276.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0150", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7356_1623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0151", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12878_3088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0152", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13922_1665.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0153", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2282_2438.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0154", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/906_1116.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0155", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5582_604.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0156", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12813_691.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0157", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 10", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12342_1605.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0158", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2810_1155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0159", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 5", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3930_2695.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0160", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13768_1164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0161", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7842_3347.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0162", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1486_2144.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0163", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9653_317.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0164", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1142_84.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0165", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/106_3904.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0166", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 10", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/163_1.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0167", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13675_3566.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0168", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7701_1666.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0169", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5875_3793.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0170", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 6", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2096_3495.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0171", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11418_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0172", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4633_799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0173", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11977_473.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0174", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5982_2537.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0175", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13047_3711.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0176", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 12", + "(B) 5", + "(C) 11", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10746_2118.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0177", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 5", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10093_728.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0178", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2174_913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0179", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 7", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8546_977.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0180", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12774_3409.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0181", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13811_3185.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0182", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10020_1783.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0183", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13391_1604.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0184", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8352_576.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0185", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8729_707.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0186", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8833_930.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0187", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/609_1303.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0188", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7630_1500.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0189", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6062_2304.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0190", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 8", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4081_2753.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0191", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1969_2794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0192", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 10", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11016_3656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0193", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 10", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13434_2840.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0194", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7986_138.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0195", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 5", + "(C) 7", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4247_2263.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0196", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2226_1880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0197", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 10", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7970_2189.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0198", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13564_1724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0199", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1508_198.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0200", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11623_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0201", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 9", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6925_1496.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0202", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3534_2121.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0203", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 10", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12770_2866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0204", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 4", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7180_1542.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0205", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2614_291.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0206", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1249_1059.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0207", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6280_2025.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0208", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4005_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0209", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6845_1578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0210", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12160_2076.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0211", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7038_32.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0212", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12250_851.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0213", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7053_1543.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0214", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/594_588.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0215", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/252_2448.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0216", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12076_3765.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0217", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 6", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3689_1917.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0218", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1917_3883.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0219", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2100_1985.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0220", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2255_839.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0221", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11904_614.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0222", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 4", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10643_3119.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0223", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11548_623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0224", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 9", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/75_1931.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0225", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3_1003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0226", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3431_3084.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0227", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4634_1003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0228", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 5", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8813_134.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0229", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13224_1649.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0230", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4027_733.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0231", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2506_2257.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0232", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 6", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12081_291.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0233", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13557_2299.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0234", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7531_3202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0235", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7963_1668.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0236", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 10", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13587_1249.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0237", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7082_2990.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0238", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8690_177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0239", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10933_140.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0240", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3564_289.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0241", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 4", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5372_3939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0242", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5688_2350.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0243", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5089_288.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0244", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9716_656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0245", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 12", + "(C) 8", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10481_2294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0246", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 4", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3181_2582.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0247", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10949_72.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0248", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4616_620.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0249", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6757_1520.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0250", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11513_2472.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0251", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11898_422.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0252", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10725_1067.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0253", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13098_3497.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0254", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12332_1770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0255", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5797_1997.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0256", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2768_3662.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0257", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2558_3470.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0258", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10896_553.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0259", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1636_618.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0260", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/174_3667.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0261", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10532_170.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0262", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11997_44.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0263", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2163_1411.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0264", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7182_101.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0265", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13788_1467.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0266", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2903_2878.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0267", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3392_3283.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0268", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4855_1396.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0269", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3079_3141.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0270", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 8", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9791_2644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0271", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7556_3466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0272", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3878_1145.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0273", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1277_3797.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0274", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11530_1913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0275", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10253_666.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0276", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 5", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1267_3234.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0277", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7743_867.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0278", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4703_1046.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0279", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3366_3939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0280", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 13", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10501_3029.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0281", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/936_622.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0282", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13048_363.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0283", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8209_2854.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0284", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3378_1373.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0285", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12768_149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0286", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5371_1481.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0287", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12638_1156.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0288", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9828_2941.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0289", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1807_1528.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0290", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 5", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10272_2888.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0291", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/192_2944.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0292", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11919_547.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0293", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3986_813.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0294", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 2", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4720_395.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0295", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3728_75.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0296", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5561_1678.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0297", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10741_849.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0298", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2211_187.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0299", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4298_369.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0300", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8491_994.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0301", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12981_1494.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0302", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2255_3421.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0303", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 3", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4049_2236.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0304", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 7", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5422_432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0305", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 3", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3894_2872.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0306", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 2", + "(C) 10", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9939_2960.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0307", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3689_231.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0308", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8376_647.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0309", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 1", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4230_1950.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0310", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/561_143.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0311", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6671_2753.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0312", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 7", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10150_396.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0313", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2357_424.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0314", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/114_3235.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0315", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/821_2538.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0316", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3046_2973.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0317", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 7", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3816_2687.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0318", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12550_852.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0319", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1554_1717.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0320", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6201_2673.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0321", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13506_3308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0322", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3912_654.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0323", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10233_3744.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0324", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/262_1963.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0325", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11486_3.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0326", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7563_3028.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0327", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9876_1989.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0328", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 13", + "(C) 3", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3938_2391.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0329", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 4", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4262_3003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0330", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1307_239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0331", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6621_2106.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0332", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 12", + "(B) 4", + "(C) 5", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12196_2140.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0333", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/752_3095.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0334", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11590_1921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0335", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5918_1306.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0336", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7190_2706.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0337", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 5", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9609_362.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0338", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10356_3644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0339", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2027_1369.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0340", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/892_685.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0341", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7980_2660.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0342", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3751_934.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0343", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13769_219.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0344", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6233_1857.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0345", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1224_2226.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0346", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1615_3381.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0347", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 5", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4131_3581.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0348", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12014_624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0349", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4162_307.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0350", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12979_3691.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0351", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2778_3308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0352", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10629_3845.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0353", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3309_1103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0354", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10916_2139.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0355", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4217_82.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0356", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9737_1339.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0357", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 3", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8197_262.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0358", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 10", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10075_3524.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0359", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11818_3305.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0360", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7947_389.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0361", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 4", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3075_2427.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0362", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 9", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9775_613.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0363", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13713_2199.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0364", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11582_2983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0365", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13049_3488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0366", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 11", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4690_2543.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0367", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10589_894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0368", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/196_1334.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0369", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 9", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4076_2781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0370", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 8", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12039_2355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0371", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6384_2549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0372", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6154_914.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0373", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 10", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13286_1207.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0374", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11482_2007.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0375", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13142_3279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0376", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 10", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8558_838.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0377", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 2", + "(C) 4", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9972_2963.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0378", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2877_50.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0379", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2462_716.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0380", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8842_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0381", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4935_164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0382", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9740_3256.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0383", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13852_3465.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0384", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12246_1022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0385", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/428_1326.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0386", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13452_2937.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0387", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3601_1023.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0388", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5068_2839.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0389", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7753_1653.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0390", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11402_48.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0391", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13841_2201.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0392", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/588_2955.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0393", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1593_1117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0394", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 4", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3627_2274.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0395", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2767_939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0396", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5774_2781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0397", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 2", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/894_763.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0398", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6486_271.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0399", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4578_187.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0400", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 9", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5328_656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0401", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/97_718.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0402", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13144_2880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0403", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 4", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3832_1205.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0404", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/991_874.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0405", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 14", + "(C) 9", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10153_2321.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0406", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 12", + "(C) 8", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12458_2633.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0407", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2165_3709.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0408", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 10", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12237_2956.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0409", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/78_1231.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0410", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12607_794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0411", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5774_2432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0412", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5221_2601.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0413", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8727_323.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0414", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1027_2572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0415", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2242_239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0416", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12932_584.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0417", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10087_1288.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0418", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1913_2147.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0419", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13184_1460.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0420", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/180_2624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0421", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1738_2399.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0422", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 4", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2569_3293.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0423", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4002_2718.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0424", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 7", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10913_2173.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0425", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/821_2178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0426", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2568_1206.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0427", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12366_225.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0428", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 7", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2061_1630.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0429", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5499_1780.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0430", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 5", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11612_2036.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0431", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1756_414.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0432", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5726_3103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0433", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3537_278.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0434", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8192_558.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0435", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/33_1025.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0436", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1701_1433.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0437", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 5", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9238_634.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0438", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4289_3921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0439", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3061_1435.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0440", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/714_1472.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0441", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 6", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/420_3598.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0442", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7790_1658.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0443", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2128_3536.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0444", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9248_1103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0445", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 8", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12195_2419.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0446", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2127_443.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0447", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5352_1000.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0448", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13657_3021.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0449", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6207_2455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0450", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1602_2756.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0451", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11313_2324.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0452", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5440_1380.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0453", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10354_1324.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0454", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2515_1177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0455", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11134_3806.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0456", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 9", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7734_3056.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0457", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11442_3188.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0458", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8332_596.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0459", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/993_355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0460", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9637_1361.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0461", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8066_2953.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0462", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5159_1333.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0463", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 10", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4492_2037.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0464", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1953_1017.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0465", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13112_3465.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0466", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5620_2370.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0467", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5530_3591.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0468", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/246_138.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0469", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2582_3841.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0470", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/301_3263.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0471", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3447_2866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0472", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 7", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5073_879.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0473", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4969_2475.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0474", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4397_912.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0475", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/403_2637.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0476", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 5", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3766_2707.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0477", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 12", + "(C) 2", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4826_3071.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0478", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6337_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0479", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6826_2455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0480", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1080_1062.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0481", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 7", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9223_1098.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0482", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3607_795.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0483", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9922_3736.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0484", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 9", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7518_1645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0485", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10445_3340.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0486", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2073_1673.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0487", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 2", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/636_1164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0488", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 3", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4614_2127.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0489", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 5", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11824_2770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0490", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4978_1366.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0491", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7105_2215.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0492", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/342_2269.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0493", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2606_2895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0494", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1070_2498.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0495", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6393_65.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0496", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2573_3457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0497", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9518_73.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0498", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12479_1705.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0499", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11492_2519.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0500", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12910_2295.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0501", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10411_3320.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0502", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 3", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4309_1633.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0503", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1262_724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0504", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4263_296.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0505", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6764_1379.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0506", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1757_126.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0507", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1856_26.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0508", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/985_394.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0509", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9100_1589.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0510", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3135_1608.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0511", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 10", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2741_1402.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0512", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2706_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0513", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3480_3359.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0514", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 8", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9717_454.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0515", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 3", + "(C) 1", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4459_2107.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0516", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9361_1052.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0517", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9345_712.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0518", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12785_155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0519", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3205_2675.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0520", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5660_2754.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0521", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1080_3529.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0522", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7834_1740.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0523", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 9", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3773_0.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0524", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7528_1063.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0525", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10085_3640.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0526", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13100_2466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0527", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 10", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/606_3474.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0528", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5959_3242.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0529", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1535_2905.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0530", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5555_1725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0531", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6741_416.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0532", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10505_3857.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0533", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 15", + "(C) 13", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10837_2177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0534", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7291_2681.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0535", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11704_3836.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0536", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4512_870.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0537", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1743_1013.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0538", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/190_3626.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0539", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3455_1062.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0540", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 8", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7134_63.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0541", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5967_2488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0542", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6329_2739.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0543", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1088_555.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0544", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7916_643.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0545", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13937_2466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0546", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12766_3004.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0547", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/188_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0548", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9929_1723.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0549", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12184_3757.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0550", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2498_329.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0551", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3319_2282.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0552", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/418_3183.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0553", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6677_1274.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0554", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10671_3832.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0555", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12103_913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0556", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1974_1312.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0557", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 4", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/888_3645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0558", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6195_1866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0559", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12104_564.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0560", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12734_2936.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0561", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 6", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/313_2762.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0562", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4341_1210.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0563", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8113_2659.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0564", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9145_512.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0565", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2197_624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0566", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13873_3044.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0567", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10089_3815.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0568", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7824_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0569", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2047_289.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0570", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1120_3022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0571", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6413_1394.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0572", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 5", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1667_1052.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0573", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10374_3091.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0574", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 9", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4350_3891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0575", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7348_404.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0576", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 8", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12656_1652.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0577", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2188_827.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0578", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7314_584.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0579", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11939_512.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0580", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9708_930.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0581", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6457_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0582", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6540_2189.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0583", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 2", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11037_2859.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0584", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1234_1895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0585", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3976_312.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0586", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8920_863.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0587", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12789_3959.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0588", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1815_3443.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0589", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 8", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9770_3639.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0590", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11725_285.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0591", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12173_3086.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0592", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7063_2763.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0593", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8123_1920.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0594", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5647_502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0595", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11908_908.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0596", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7858_2303.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0597", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11415_2456.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0598", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 3", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9124_564.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0599", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12694_2200.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0600", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 9", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12568_2711.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0601", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5280_2100.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0602", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9986_329.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0603", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 3", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9989_383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0604", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9444_1441.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0605", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 11", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11741_2919.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0606", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5384_77.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0607", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 3", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10548_3936.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0608", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2728_725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0609", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1253_640.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0610", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3712_708.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0611", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2292_842.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0612", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9437_1247.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0613", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 7", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4298_2322.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0614", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 13", + "(B) 4", + "(C) 7", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10070_2063.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0615", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 11", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10210_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0616", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 11", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10766_3123.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0617", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7503_2616.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0618", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7133_1751.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0619", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2136_3680.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0620", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3084_953.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0621", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/689_3929.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0622", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12942_3517.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0623", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11940_3812.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0624", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3924_877.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0625", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7548_1194.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0626", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3733_915.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0627", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 8", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4193_864.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0628", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12062_136.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0629", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2345_3698.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0630", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9675_149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0631", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2864_1322.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0632", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10614_1238.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0633", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4562_1432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0634", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 4", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1168_3522.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0635", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11936_3148.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0636", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9407_736.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0637", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7335_3115.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0638", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12354_3912.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0639", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/219_657.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0640", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 3", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13191_1038.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0641", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 3", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6275_2597.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0642", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5522_3929.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0643", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5677_432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0644", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 4", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2172_1348.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0645", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10067_117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0646", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/448_3781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0647", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7251_2593.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0648", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5038_2390.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0649", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9689_1532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0650", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/195_2073.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0651", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 15", + "(C) 1", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10590_2261.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0652", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 10", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5666_1628.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0653", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6110_1328.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0654", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2016_2102.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0655", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5069_3541.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0656", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2954_1149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0657", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 9", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13329_3060.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0658", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9933_1983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0659", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13127_3131.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0660", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 6", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2633_177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0661", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2927_2823.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0662", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5687_2606.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0663", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4783_3965.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0664", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/312_1211.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0665", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5705_1624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0666", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11325_109.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0667", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 6", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13837_1794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0668", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/924_3088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0669", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 4", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/19_918.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0670", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5865_1972.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0671", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 4", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1312_59.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0672", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 9", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8158_2464.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0673", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7330_2457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0674", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6707_1659.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0675", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/584_1294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0676", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/613_2880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0677", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13707_3215.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0678", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9769_3157.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0679", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/358_3896.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0680", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/871_880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0681", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3116_3572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0682", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12213_3117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0683", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4580_3775.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0684", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/521_1304.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0685", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11643_2408.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0686", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7446_1844.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0687", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 8", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13766_3566.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0688", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5119_2117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0689", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 0", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/164_675.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0690", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 3", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5277_180.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0691", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13922_3285.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0692", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7130_2265.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0693", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2259_3498.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0694", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9702_3865.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0695", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9771_1221.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0696", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6262_1894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0697", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 4", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13410_1226.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0698", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/331_3275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0699", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7902_3124.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0700", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12363_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0701", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12725_3891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0702", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5223_181.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0703", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 12", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3813_2283.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0704", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1112_532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0705", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2081_1237.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0706", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 10", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3497_1717.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0707", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8370_267.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0708", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 10", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13959_3171.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0709", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3223_516.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0710", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1018_3550.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0711", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/760_576.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0712", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 10", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1333_2277.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0713", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12021_3532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0714", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 9", + "(C) 0", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2406_275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0715", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11689_3150.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0716", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5382_3423.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0717", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 8", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13310_1097.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0718", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9599_279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0719", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 0", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10349_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0720", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13658_891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0721", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/284_2045.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0722", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12573_3557.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0723", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7827_243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0724", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 0", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3298_2919.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0725", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 3", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7891_1040.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0726", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 10", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4601_1833.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0727", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9915_1725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0728", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2245_1110.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0729", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 7", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9776_516.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0730", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13712_3549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0731", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/51_18.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0732", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10499_3949.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0733", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13365_928.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0734", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 11", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3298_2077.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0735", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 3", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3024_2272.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0736", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 7", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/874_770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0737", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 10", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12020_2164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0738", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2976_3122.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0739", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1683_478.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0740", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 2", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1102_792.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0741", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6283_1424.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0742", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 15", + "(B) 10", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10183_2899.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0743", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 7", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7881_309.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0744", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7892_3239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0745", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12886_754.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0746", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12597_1244.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0747", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/348_142.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0748", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1992_2241.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0749", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 6", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4122_2450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0750", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10969_2233.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0751", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5686_2583.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0752", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11988_38.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0753", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2038_2650.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0754", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7306_2723.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0755", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12954_2127.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0756", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9185_1661.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0757", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1697_3245.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0758", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12914_1355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0759", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5206_3552.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0760", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 16", + "(B) 6", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10380_2108.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0761", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12460_1377.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0762", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 8", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11609_722.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0763", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 1", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5849_2965.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0764", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 8", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9728_2979.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0765", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3218_2356.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0766", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10908_3395.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0767", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 11", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10188_644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0768", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 5", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9894_212.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0769", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9753_3383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0770", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1262_2652.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0771", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 9", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13122_3234.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0772", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 15", + "(C) 14", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10389_2489.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0773", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12273_1870.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0774", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 0", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/20_3482.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0775", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4515_337.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0776", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 9", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12947_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0777", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1857_3873.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0778", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2898_761.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0779", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 2", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9854_3647.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0780", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1987_3747.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0781", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4467_3726.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0782", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 9", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10982_3161.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0783", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 8", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6673_202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0784", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6756_1811.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0785", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 8", + "(C) 1", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10565_2321.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0786", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6228_1134.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0787", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 0", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1152_3168.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0788", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 4", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7368_1179.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0789", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2267_3727.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0790", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 4", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13375_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0791", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 0", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1920_3184.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0792", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3701_1039.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0793", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5188_2470.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0794", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9488_1455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0795", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/409_3180.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0796", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2795_1227.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0797", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 4", + "(B) 2", + "(C) 0", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3292_1617.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0798", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10763_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0799", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 4", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4762_2733.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0800", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 5", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3733_2744.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0801", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5771_1888.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0802", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6191_1851.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0803", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 7", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11898_2932.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0804", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11368_3780.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0805", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 4", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2506_1587.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0806", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 3", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1655_2602.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0807", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 10", + "(B) 0", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4951_1696.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0808", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 5", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1387_1088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0809", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2219_3450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0810", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11768_225.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0811", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1244_3924.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0812", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1964_3531.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0813", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3195_578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0814", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3152_2895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0815", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 3", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9233_1073.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0816", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 6", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3108_3645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0817", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3281_3756.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0818", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 10", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10845_3561.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0819", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 6", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7615_1900.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0820", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/302_3894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0821", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/196_1202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0822", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 7", + "(D) 0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2132_72.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0823", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 7", + "(B) 0", + "(C) 1", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13205_1239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0824", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4349_807.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0825", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 3", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12126_197.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0826", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3707_1793.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0827", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. How many dead trees are in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm counting", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4302_2512.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_identification.json b/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_identification.json new file mode 100644 index 0000000000000000000000000000000000000000..3566b6348c91109670ca5fda42794cfe0a135e0f --- /dev/null +++ b/jsons/Biosphere/Crop_growth_monitoring/Perception/Dead_Oil_Palm_identification.json @@ -0,0 +1,15734 @@ +[ + { + "Question_id": "Dead Oil Palm identification/0000", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1341_257.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0001", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4373_3549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0002", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3295_3885.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0003", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10747_2371.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0004", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13606_3450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0005", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2030_2309.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0006", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7084_1243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0007", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7516_1178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0008", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5852_1836.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0009", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/432_3336.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0010", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10172_1970.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0011", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10465_340.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0012", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12503_3842.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0013", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12763_3276.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0014", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5435_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0015", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13188_3817.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0016", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4501_623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0017", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7246_198.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0018", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8233_2875.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0019", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9776_561.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0020", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2693_3950.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0021", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6048_1881.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0022", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/750_2656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0023", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8540_505.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0024", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6410_1244.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0025", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/999_1174.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0026", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1235_3022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0027", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1132_2848.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0028", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1406_2471.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0029", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3989_1900.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0030", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12985_2885.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0031", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4921_2502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0032", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6971_2427.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0033", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11736_1091.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0034", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7781_2136.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0035", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10093_275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0036", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10179_2308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0037", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3780_983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0038", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7880_1167.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0039", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11878_3438.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0040", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9960_3046.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0041", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12862_1693.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0042", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1354_3681.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0043", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5162_1696.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0044", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5590_3365.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0045", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7838_1110.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0046", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13470_3421.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0047", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4387_1123.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0048", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12755_2449.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0049", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13973_2202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0050", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4047_572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0051", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12470_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0052", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8253_117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0053", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2548_827.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0054", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3344_1960.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0055", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/837_1368.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0056", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9184_62.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0057", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7842_926.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0058", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4033_3844.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0059", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2045_821.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0060", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9392_490.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0061", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11080_2359.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0062", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8102_4.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0063", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/224_2436.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0064", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1437_2853.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0065", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1971_2626.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0066", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11006_294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0067", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12159_2154.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0068", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/258_3667.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0069", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10425_2415.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0070", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9418_526.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0071", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10681_2799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0072", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12813_261.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0073", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7473_338.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0074", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/681_2527.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0075", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7424_3117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0076", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9144_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0077", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5888_2583.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0078", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2203_1178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0079", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9168_537.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0080", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3213_2658.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0081", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12367_3724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0082", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8045_1880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0083", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/89_835.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0084", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13464_2251.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0085", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1180_279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0086", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3565_1720.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0087", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2538_3391.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0088", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1039_954.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0089", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12451_3578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0090", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1359_2155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0091", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7326_1350.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0092", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2371_502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0093", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10136_3488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0094", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7666_2830.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0095", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1093_3474.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0096", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6622_348.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0097", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9677_3243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0098", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3071_892.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0099", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6186_2598.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0100", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12531_315.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0101", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12403_731.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0102", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5643_1030.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0103", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7781_2601.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0104", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9806_160.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0105", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4223_762.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0106", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6919_1889.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0107", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4932_3550.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0108", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10752_3.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0109", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5694_2272.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0110", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11954_986.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0111", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4378_2436.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0112", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1109_3501.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0113", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6795_1383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0114", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7004_214.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0115", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3926_314.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0116", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2094_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0117", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3201_3053.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0118", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12347_3008.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0119", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6502_1801.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0120", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1507_2889.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0121", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9751_3618.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0122", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2253_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0123", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2063_3702.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0124", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2888_3606.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0125", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11914_1279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0126", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10674_1059.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0127", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7147_1799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0128", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5102_664.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0129", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12909_1830.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0130", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/435_2765.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0131", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7523_3125.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0132", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2358_1921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0133", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3183_638.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0134", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1315_615.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0135", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10484_2578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0136", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10755_1082.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0137", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/280_2519.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0138", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10919_3457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0139", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10386_3670.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0140", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5294_3954.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0141", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12087_2293.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0142", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/122_298.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0143", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2977_3804.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0144", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1048_865.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0145", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3192_1119.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0146", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1411_3795.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0147", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10368_1325.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0148", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10981_3440.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0149", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4249_276.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0150", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7356_1623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0151", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12878_3088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0152", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13922_1665.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0153", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2282_2438.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0154", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/906_1116.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0155", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5582_604.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0156", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12813_691.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0157", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12342_1605.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0158", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2810_1155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0159", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3930_2695.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0160", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13768_1164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0161", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7842_3347.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0162", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1486_2144.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0163", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9653_317.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0164", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1142_84.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0165", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/106_3904.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0166", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/163_1.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0167", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13675_3566.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0168", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7701_1666.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0169", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5875_3793.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0170", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2096_3495.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0171", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11418_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0172", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4633_799.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0173", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11977_473.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0174", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5982_2537.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0175", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13047_3711.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0176", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10746_2118.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0177", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10093_728.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0178", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2174_913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0179", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8546_977.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0180", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12774_3409.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0181", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13811_3185.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0182", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10020_1783.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0183", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13391_1604.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0184", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8352_576.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0185", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8729_707.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0186", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8833_930.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0187", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/609_1303.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0188", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7630_1500.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0189", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6062_2304.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0190", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4081_2753.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0191", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1969_2794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0192", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11016_3656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0193", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13434_2840.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0194", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7986_138.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0195", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4247_2263.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0196", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2226_1880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0197", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7970_2189.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0198", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13564_1724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0199", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1508_198.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0200", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11623_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0201", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6925_1496.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0202", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3534_2121.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0203", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12770_2866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0204", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7180_1542.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0205", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2614_291.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0206", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1249_1059.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0207", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6280_2025.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0208", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4005_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0209", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6845_1578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0210", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12160_2076.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0211", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7038_32.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0212", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12250_851.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0213", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7053_1543.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0214", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/594_588.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0215", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/252_2448.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0216", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12076_3765.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0217", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3689_1917.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0218", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1917_3883.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0219", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2100_1985.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0220", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2255_839.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0221", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11904_614.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0222", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10643_3119.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0223", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11548_623.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0224", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/75_1931.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0225", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3_1003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0226", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3431_3084.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0227", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4634_1003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0228", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8813_134.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0229", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13224_1649.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0230", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4027_733.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0231", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2506_2257.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0232", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12081_291.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0233", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13557_2299.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0234", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7531_3202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0235", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7963_1668.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0236", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13587_1249.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0237", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7082_2990.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0238", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8690_177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0239", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10933_140.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0240", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3564_289.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0241", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5372_3939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0242", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5688_2350.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0243", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5089_288.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0244", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9716_656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0245", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10481_2294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0246", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3181_2582.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0247", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10949_72.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0248", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4616_620.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0249", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6757_1520.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0250", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11513_2472.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0251", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11898_422.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0252", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10725_1067.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0253", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13098_3497.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0254", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12332_1770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0255", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5797_1997.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0256", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2768_3662.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0257", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2558_3470.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0258", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10896_553.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0259", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1636_618.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0260", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/174_3667.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0261", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10532_170.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0262", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11997_44.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0263", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2163_1411.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0264", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7182_101.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0265", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13788_1467.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0266", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2903_2878.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0267", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3392_3283.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0268", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4855_1396.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0269", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3079_3141.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0270", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9791_2644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0271", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7556_3466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0272", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3878_1145.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0273", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1277_3797.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0274", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11530_1913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0275", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10253_666.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0276", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1267_3234.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0277", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7743_867.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0278", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4703_1046.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0279", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3366_3939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0280", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10501_3029.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0281", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/936_622.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0282", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13048_363.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0283", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8209_2854.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0284", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3378_1373.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0285", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12768_149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0286", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5371_1481.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0287", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12638_1156.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0288", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9828_2941.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0289", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1807_1528.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0290", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10272_2888.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0291", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/192_2944.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0292", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11919_547.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0293", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3986_813.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0294", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4720_395.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0295", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3728_75.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0296", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5561_1678.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0297", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10741_849.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0298", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2211_187.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0299", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4298_369.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0300", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8491_994.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0301", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12981_1494.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0302", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2255_3421.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0303", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4049_2236.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0304", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5422_432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0305", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3894_2872.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0306", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9939_2960.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0307", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3689_231.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0308", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8376_647.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0309", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4230_1950.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0310", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/561_143.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0311", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6671_2753.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0312", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10150_396.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0313", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2357_424.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0314", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/114_3235.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0315", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/821_2538.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0316", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3046_2973.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0317", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3816_2687.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0318", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12550_852.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0319", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1554_1717.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0320", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6201_2673.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0321", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13506_3308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0322", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3912_654.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0323", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10233_3744.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0324", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/262_1963.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0325", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11486_3.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0326", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7563_3028.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0327", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9876_1989.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0328", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3938_2391.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0329", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4262_3003.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0330", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1307_239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0331", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6621_2106.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0332", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12196_2140.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0333", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/752_3095.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0334", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11590_1921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0335", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5918_1306.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0336", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7190_2706.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0337", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9609_362.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0338", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10356_3644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0339", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2027_1369.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0340", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/892_685.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0341", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7980_2660.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0342", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3751_934.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0343", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13769_219.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0344", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6233_1857.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0345", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1224_2226.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0346", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1615_3381.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0347", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4131_3581.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0348", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12014_624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0349", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4162_307.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0350", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12979_3691.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0351", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2778_3308.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0352", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10629_3845.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0353", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3309_1103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0354", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10916_2139.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0355", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4217_82.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0356", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9737_1339.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0357", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8197_262.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0358", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10075_3524.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0359", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11818_3305.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0360", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7947_389.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0361", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3075_2427.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0362", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9775_613.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0363", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13713_2199.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0364", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11582_2983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0365", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13049_3488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0366", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4690_2543.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0367", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10589_894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0368", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/196_1334.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0369", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4076_2781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0370", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12039_2355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0371", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6384_2549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0372", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6154_914.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0373", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13286_1207.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0374", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11482_2007.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0375", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13142_3279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0376", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8558_838.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0377", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9972_2963.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0378", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2877_50.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0379", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2462_716.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0380", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8842_451.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0381", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4935_164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0382", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9740_3256.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0383", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13852_3465.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0384", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12246_1022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0385", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/428_1326.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0386", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13452_2937.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0387", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3601_1023.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0388", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5068_2839.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0389", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7753_1653.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0390", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11402_48.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0391", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13841_2201.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0392", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/588_2955.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0393", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1593_1117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0394", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3627_2274.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0395", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2767_939.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0396", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5774_2781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0397", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/894_763.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0398", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6486_271.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0399", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4578_187.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0400", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5328_656.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0401", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/97_718.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0402", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13144_2880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0403", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3832_1205.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0404", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/991_874.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0405", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10153_2321.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0406", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12458_2633.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0407", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2165_3709.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0408", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12237_2956.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0409", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/78_1231.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0410", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12607_794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0411", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5774_2432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0412", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5221_2601.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0413", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8727_323.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0414", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1027_2572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0415", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2242_239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0416", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12932_584.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0417", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10087_1288.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0418", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1913_2147.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0419", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13184_1460.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0420", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/180_2624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0421", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1738_2399.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0422", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2569_3293.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0423", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4002_2718.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0424", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10913_2173.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0425", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/821_2178.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0426", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2568_1206.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0427", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12366_225.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0428", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2061_1630.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0429", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5499_1780.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0430", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11612_2036.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0431", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1756_414.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0432", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5726_3103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0433", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3537_278.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0434", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8192_558.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0435", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/33_1025.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0436", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1701_1433.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0437", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9238_634.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0438", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4289_3921.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0439", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3061_1435.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0440", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/714_1472.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0441", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/420_3598.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0442", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7790_1658.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0443", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2128_3536.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0444", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9248_1103.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0445", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12195_2419.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0446", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2127_443.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0447", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5352_1000.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0448", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13657_3021.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0449", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6207_2455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0450", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1602_2756.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0451", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11313_2324.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0452", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5440_1380.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0453", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10354_1324.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0454", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2515_1177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0455", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11134_3806.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0456", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7734_3056.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0457", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11442_3188.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0458", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8332_596.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0459", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/993_355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0460", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9637_1361.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0461", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8066_2953.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0462", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5159_1333.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0463", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4492_2037.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0464", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1953_1017.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0465", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13112_3465.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0466", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5620_2370.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0467", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5530_3591.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0468", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/246_138.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0469", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2582_3841.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0470", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/301_3263.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0471", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3447_2866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0472", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5073_879.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0473", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4969_2475.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0474", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4397_912.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0475", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/403_2637.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0476", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3766_2707.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0477", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4826_3071.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0478", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6337_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0479", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6826_2455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0480", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1080_1062.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0481", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9223_1098.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0482", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3607_795.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0483", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9922_3736.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0484", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7518_1645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0485", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10445_3340.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0486", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2073_1673.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0487", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/636_1164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0488", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4614_2127.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0489", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11824_2770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0490", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4978_1366.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0491", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7105_2215.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0492", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/342_2269.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0493", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2606_2895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0494", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1070_2498.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0495", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6393_65.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0496", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2573_3457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0497", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9518_73.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0498", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12479_1705.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0499", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11492_2519.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0500", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12910_2295.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0501", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10411_3320.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0502", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4309_1633.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0503", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1262_724.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0504", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4263_296.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0505", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6764_1379.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0506", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1757_126.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0507", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1856_26.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0508", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/985_394.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0509", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9100_1589.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0510", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3135_1608.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0511", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2741_1402.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0512", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2706_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0513", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3480_3359.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0514", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9717_454.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0515", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4459_2107.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0516", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9361_1052.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0517", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9345_712.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0518", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12785_155.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0519", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3205_2675.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0520", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5660_2754.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0521", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1080_3529.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0522", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7834_1740.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0523", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3773_0.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0524", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7528_1063.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0525", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10085_3640.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0526", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13100_2466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0527", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/606_3474.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0528", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5959_3242.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0529", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1535_2905.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0530", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5555_1725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0531", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6741_416.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0532", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10505_3857.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0533", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10837_2177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0534", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7291_2681.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0535", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11704_3836.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0536", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4512_870.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0537", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1743_1013.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0538", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/190_3626.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0539", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3455_1062.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0540", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7134_63.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0541", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5967_2488.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0542", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6329_2739.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0543", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1088_555.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0544", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7916_643.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0545", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13937_2466.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0546", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12766_3004.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0547", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/188_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0548", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9929_1723.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0549", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12184_3757.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0550", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2498_329.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0551", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3319_2282.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0552", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/418_3183.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0553", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6677_1274.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0554", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10671_3832.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0555", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12103_913.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0556", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1974_1312.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0557", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/888_3645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0558", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6195_1866.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0559", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12104_564.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0560", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12734_2936.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0561", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/313_2762.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0562", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4341_1210.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0563", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8113_2659.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0564", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9145_512.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0565", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2197_624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0566", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13873_3044.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0567", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10089_3815.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0568", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7824_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0569", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2047_289.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0570", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1120_3022.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0571", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6413_1394.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0572", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1667_1052.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0573", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10374_3091.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0574", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4350_3891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0575", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7348_404.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0576", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12656_1652.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0577", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2188_827.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0578", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7314_584.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0579", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11939_512.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0580", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9708_930.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0581", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6457_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0582", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6540_2189.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0583", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11037_2859.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0584", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1234_1895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0585", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3976_312.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0586", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8920_863.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0587", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12789_3959.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0588", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1815_3443.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0589", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9770_3639.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0590", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11725_285.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0591", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12173_3086.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0592", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7063_2763.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0593", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8123_1920.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0594", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5647_502.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0595", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11908_908.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0596", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7858_2303.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0597", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11415_2456.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0598", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9124_564.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0599", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12694_2200.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0600", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12568_2711.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0601", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5280_2100.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0602", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9986_329.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0603", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9989_383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0604", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9444_1441.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0605", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11741_2919.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0606", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5384_77.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0607", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10548_3936.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0608", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2728_725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0609", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1253_640.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0610", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3712_708.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0611", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2292_842.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0612", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9437_1247.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0613", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4298_2322.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0614", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10070_2063.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0615", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10210_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0616", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10766_3123.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0617", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7503_2616.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0618", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7133_1751.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0619", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2136_3680.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0620", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3084_953.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0621", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/689_3929.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0622", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12942_3517.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0623", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11940_3812.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0624", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3924_877.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0625", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7548_1194.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0626", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3733_915.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0627", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4193_864.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0628", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12062_136.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0629", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2345_3698.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0630", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9675_149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0631", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2864_1322.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0632", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10614_1238.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0633", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4562_1432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0634", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1168_3522.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0635", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11936_3148.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0636", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9407_736.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0637", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7335_3115.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0638", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12354_3912.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0639", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/219_657.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0640", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13191_1038.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0641", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6275_2597.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0642", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5522_3929.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0643", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5677_432.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0644", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2172_1348.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0645", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10067_117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0646", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/448_3781.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0647", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7251_2593.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0648", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5038_2390.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0649", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9689_1532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0650", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/195_2073.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0651", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10590_2261.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0652", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5666_1628.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0653", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6110_1328.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0654", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2016_2102.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0655", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5069_3541.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0656", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2954_1149.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0657", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13329_3060.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0658", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9933_1983.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0659", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13127_3131.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0660", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2633_177.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0661", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2927_2823.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0662", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5687_2606.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0663", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4783_3965.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0664", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/312_1211.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0665", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5705_1624.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0666", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11325_109.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0667", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13837_1794.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0668", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/924_3088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0669", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/19_918.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0670", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5865_1972.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0671", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1312_59.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0672", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8158_2464.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0673", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7330_2457.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0674", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6707_1659.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0675", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/584_1294.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0676", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/613_2880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0677", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13707_3215.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0678", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9769_3157.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0679", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/358_3896.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0680", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/871_880.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0681", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3116_3572.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0682", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12213_3117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0683", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4580_3775.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0684", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/521_1304.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0685", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11643_2408.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0686", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7446_1844.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0687", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13766_3566.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0688", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5119_2117.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0689", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/164_675.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0690", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5277_180.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0691", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13922_3285.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0692", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7130_2265.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0693", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2259_3498.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0694", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9702_3865.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0695", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9771_1221.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0696", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6262_1894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0697", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13410_1226.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0698", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/331_3275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0699", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7902_3124.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0700", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12363_1533.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0701", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12725_3891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0702", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5223_181.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0703", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3813_2283.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0704", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1112_532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0705", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2081_1237.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0706", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3497_1717.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0707", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/8370_267.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0708", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13959_3171.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0709", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3223_516.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0710", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1018_3550.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0711", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/760_576.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0712", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1333_2277.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0713", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12021_3532.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0714", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2406_275.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0715", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11689_3150.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0716", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5382_3423.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0717", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13310_1097.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0718", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9599_279.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0719", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10349_1316.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0720", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13658_891.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0721", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/284_2045.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0722", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12573_3557.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0723", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7827_243.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0724", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3298_2919.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0725", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7891_1040.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0726", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4601_1833.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0727", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9915_1725.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0728", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2245_1110.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0729", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9776_516.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0730", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13712_3549.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0731", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/51_18.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0732", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10499_3949.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0733", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13365_928.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0734", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3298_2077.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0735", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3024_2272.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0736", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/874_770.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0737", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12020_2164.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0738", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2976_3122.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0739", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1683_478.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0740", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1102_792.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0741", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6283_1424.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0742", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10183_2899.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0743", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7881_309.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0744", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7892_3239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0745", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12886_754.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0746", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12597_1244.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0747", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/348_142.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0748", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1992_2241.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0749", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4122_2450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0750", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10969_2233.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0751", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5686_2583.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0752", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11988_38.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0753", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2038_2650.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0754", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7306_2723.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0755", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12954_2127.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0756", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9185_1661.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0757", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1697_3245.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0758", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12914_1355.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0759", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5206_3552.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0760", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10380_2108.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0761", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12460_1377.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0762", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11609_722.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0763", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5849_2965.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0764", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9728_2979.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0765", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3218_2356.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0766", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10908_3395.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0767", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10188_644.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0768", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9894_212.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0769", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9753_3383.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0770", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1262_2652.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0771", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13122_3234.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0772", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10389_2489.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0773", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12273_1870.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0774", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/20_3482.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0775", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4515_337.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0776", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12947_2995.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0777", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1857_3873.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0778", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2898_761.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0779", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9854_3647.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0780", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1987_3747.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0781", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4467_3726.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0782", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10982_3161.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0783", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6673_202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0784", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6756_1811.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0785", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10565_2321.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0786", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6228_1134.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0787", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1152_3168.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0788", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7368_1179.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0789", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2267_3727.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0790", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13375_1014.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0791", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1920_3184.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0792", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3701_1039.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0793", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5188_2470.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0794", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9488_1455.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0795", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/409_3180.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0796", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2795_1227.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0797", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3292_1617.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0798", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10763_768.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0799", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4762_2733.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0800", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3733_2744.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0801", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/5771_1888.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0802", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/6191_1851.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0803", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11898_2932.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0804", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11368_3780.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0805", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2506_1587.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0806", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1655_2602.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0807", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4951_1696.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0808", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1387_1088.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0809", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2219_3450.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0810", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/11768_225.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0811", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1244_3924.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0812", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/1964_3531.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0813", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3195_578.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0814", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3152_2895.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0815", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/9233_1073.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0816", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3108_3645.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0817", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3281_3756.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0818", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/10845_3561.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0819", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/7615_1900.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0820", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/302_3894.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0821", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/196_1202.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0822", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/2132_72.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0823", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/13205_1239.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0824", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4349_807.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0825", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/12126_197.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0826", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/3707_1793.jpg" + ] + }, + { + "Question_id": "Dead Oil Palm identification/0827", + "Question Type": "Single Choice", + "Text": "This is an unmanned aerial vehicle (UAV) image capturing oil palm trees. Is there any dead tree in this image?", + "L1-task": "Biosphere", + "L2-task": "Crop growth monitoring", + "L3-task": "Perception", + "L4-task": "Dead Oil Palm identification", + "Dataset": "MOPAD", + "Answer Choices": [ + "(A) Yes", + "(B) No", + "(C) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Crop growth monitoring/images/4302_2512.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_area_calculation.json b/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_area_calculation.json new file mode 100644 index 0000000000000000000000000000000000000000..61a5700fe6f4d8a53d686f8078f6528fb10eeca5 --- /dev/null +++ b/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_area_calculation.json @@ -0,0 +1,2585 @@ +[ + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0000", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 10", + "(C) 4", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130404.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0001", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 11", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130603.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0002", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 8", + "(C) 10", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130721.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0003", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 15", + "(C) 16", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130907.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0004", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20131025.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0005", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 6", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20131110.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0006", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 2", + "(C) 6", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140214.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0007", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 4", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140318.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0008", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 11", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140419.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0009", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140521.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0010", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 12", + "(B) 4", + "(C) 5", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140606.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0011", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 9", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140622.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0012", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 4", + "(C) 10", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140724.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0013", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 3", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140809.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0014", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 10", + "(C) 12", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140910.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0015", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 3", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141012.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0016", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 7", + "(C) 12", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141028.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0017", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 9", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141129.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0018", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 11", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150116.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0019", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 9", + "(C) 3", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150524.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0020", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 4", + "(C) 10", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150609.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0021", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 2", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150625.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0022", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 12", + "(B) 10", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150711.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0023", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 13", + "(B) 10", + "(C) 8", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150727.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0024", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 7", + "(C) 9", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150812.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0025", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 7", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150828.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0026", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 7", + "(C) 4", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150929.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0027", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 10", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160119.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0028", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160408.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0029", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160424.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0030", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 9", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160510.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0031", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 10", + "(B) 5", + "(C) 9", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160611.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0032", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 6", + "(C) 9", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160713.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0033", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 4", + "(C) 9", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160729.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0034", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 1", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160814.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0035", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 10", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160830.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0036", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 8", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170121.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0037", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 6", + "(C) 3", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170206.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0038", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 6", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170222.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0039", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 6", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170310.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0040", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 10", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170427.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0041", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 7", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170630.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0042", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 3", + "(C) 4", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170716.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0043", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 11", + "(C) 3", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170817.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0044", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 9", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170902.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0045", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 12", + "(B) 3", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170918.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0046", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20171121.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0047", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 6", + "(C) 8", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190620.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0048", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 11", + "(C) 5", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190908.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0049", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 10", + "(C) 8", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190924.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0050", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 7", + "(C) 12", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191010.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0051", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 10", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191026.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0052", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 9", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191111.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0053", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 8", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191127.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0054", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 9", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200521.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0055", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 8", + "(C) 3", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200825.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0056", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 9", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200926.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0057", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 11", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201012.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0058", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 11", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201028.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0059", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 2", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201215.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0060", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 11", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201231.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0061", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 4", + "(C) 2", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210201.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0062", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 11", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210305.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0063", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 9", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210321.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0064", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 11", + "(C) 6", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210406.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0065", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 6", + "(C) 2", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210422.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0066", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 8", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210508.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0067", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 10", + "(B) 7", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210524.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0068", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 8", + "(C) 10", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210609.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0069", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 11", + "(C) 8", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210625.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0070", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210711.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0071", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 5", + "(C) 9", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210812.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0072", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 5", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210828.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0073", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 10", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210913.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0074", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 3", + "(C) 10", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20211015.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0075", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20211031.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0076", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 6", + "(C) 1", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220220.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0077", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 7", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220612.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0078", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220628.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0079", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 4", + "(C) 9", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220714.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0080", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220730.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0081", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 4", + "(C) 8", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220815.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0082", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220831.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0083", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220916.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0084", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 9", + "(C) 8", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20221119.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0085", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 4", + "(C) 1", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20221205.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0086", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230122.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0087", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 7", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230428.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0088", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 9", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230802.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0089", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 8", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230903.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0090", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 8", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20231208.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0091", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220127.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0092", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220212.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0093", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 8", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220401.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0094", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 7", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220519.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0095", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 5", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220604.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0096", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 3", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220620.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0097", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 8", + "(C) 4", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220722.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0098", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 7", + "(C) 6", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220823.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0099", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 2", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220924.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0100", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20221111.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0101", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 6", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20221213.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0102", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 7", + "(C) 1", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230130.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0103", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 6", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230319.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0104", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 3", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230420.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0105", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 7", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230623.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0106", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 4", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230810.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0107", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 6", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230927.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0108", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 3", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20231013.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0109", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 6", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20231029.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0110", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 13", + "(B) 8", + "(C) 10", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060531.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0111", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 13", + "(B) 16", + "(C) 11", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060718.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0112", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 13", + "(C) 10", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060819.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0113", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 10", + "(B) 5", + "(C) 12", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060904.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0114", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 5", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060920.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0115", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 12", + "(B) 5", + "(C) 7", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20061006.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0116", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 3", + "(B) 6", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070518.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0117", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 12", + "(C) 17", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070806.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0118", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 12", + "(B) 7", + "(C) 17", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070822.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0119", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 6", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070923.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0120", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 15", + "(C) 10", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080520.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0121", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 5", + "(B) 11", + "(C) 10", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080707.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill area calculation/0122", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. What is the oil spill area in the image in square kilometers?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill area calculation", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 11", + "(B) 9", + "(C) 14", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080723.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_counting.json b/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_counting.json new file mode 100644 index 0000000000000000000000000000000000000000..9f22a0af6ef3cd8062b29dd60d0b469e25c0ceeb --- /dev/null +++ b/jsons/Biosphere/Environmental_pollution_monitoring/Perception/Terrestrial_oil_spill_counting.json @@ -0,0 +1,2585 @@ +[ + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0000", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 31", + "(B) 46", + "(C) 61", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130404.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0001", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 45", + "(B) 46", + "(C) 36", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130603.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0002", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 48", + "(B) 37", + "(C) 47", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130721.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0003", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 41", + "(C) 29", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20130907.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0004", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 39", + "(C) 24", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20131025.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0005", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 39", + "(B) 51", + "(C) 48", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20131110.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0006", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 36", + "(B) 50", + "(C) 44", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140214.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0007", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 56", + "(B) 53", + "(C) 40", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140318.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0008", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 50", + "(B) 46", + "(C) 37", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140419.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0009", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 27", + "(B) 25", + "(C) 24", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140521.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0010", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 31", + "(B) 28", + "(C) 29", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140606.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0011", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 32", + "(C) 29", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140622.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0012", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 48", + "(B) 32", + "(C) 39", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140724.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0013", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 28", + "(C) 58", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140809.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0014", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 52", + "(B) 27", + "(C) 39", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20140910.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0015", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 40", + "(B) 52", + "(C) 56", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141012.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0016", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 52", + "(B) 54", + "(C) 48", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141028.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0017", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 27", + "(B) 26", + "(C) 43", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20141129.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0018", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 24", + "(B) 41", + "(C) 42", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150116.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0019", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 51", + "(B) 52", + "(C) 39", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150524.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0020", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 47", + "(C) 35", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150609.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0021", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 24", + "(B) 50", + "(C) 48", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150625.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0022", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 23", + "(B) 44", + "(C) 21", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150711.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0023", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 36", + "(B) 47", + "(C) 49", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150727.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0024", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 29", + "(B) 26", + "(C) 46", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150812.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0025", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 52", + "(B) 53", + "(C) 38", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150828.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0026", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 38", + "(B) 27", + "(C) 47", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20150929.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0027", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 41", + "(B) 30", + "(C) 20", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160119.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0028", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 24", + "(B) 32", + "(C) 26", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160408.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0029", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 50", + "(B) 39", + "(C) 46", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160424.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0030", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 40", + "(B) 27", + "(C) 30", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160510.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0031", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 20", + "(B) 39", + "(C) 18", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160611.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0032", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 36", + "(B) 50", + "(C) 32", + "(D) 66", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160713.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0033", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 34", + "(B) 32", + "(C) 42", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160729.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0034", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 38", + "(B) 30", + "(C) 29", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160814.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0035", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 50", + "(B) 41", + "(C) 28", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20160830.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0036", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 19", + "(B) 24", + "(C) 17", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170121.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0037", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 44", + "(B) 30", + "(C) 37", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170206.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0038", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 44", + "(C) 59", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170222.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0039", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 41", + "(B) 26", + "(C) 54", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170310.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0040", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 20", + "(B) 30", + "(C) 42", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170427.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0041", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 23", + "(B) 44", + "(C) 48", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170630.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0042", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 34", + "(B) 27", + "(C) 46", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170716.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0043", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 31", + "(B) 41", + "(C) 19", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170817.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0044", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 35", + "(B) 43", + "(C) 21", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170902.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0045", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 48", + "(B) 26", + "(C) 36", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20170918.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0046", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 25", + "(B) 45", + "(C) 33", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20171121.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0047", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 38", + "(C) 20", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190620.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0048", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 28", + "(B) 55", + "(C) 49", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190908.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0049", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 25", + "(B) 49", + "(C) 48", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20190924.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0050", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 47", + "(B) 46", + "(C) 26", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191010.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0051", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 25", + "(B) 32", + "(C) 26", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191026.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0052", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 34", + "(B) 43", + "(C) 45", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191111.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0053", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 53", + "(C) 26", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20191127.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0054", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 41", + "(B) 49", + "(C) 31", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200521.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0055", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 39", + "(B) 50", + "(C) 46", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200825.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0056", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 36", + "(B) 30", + "(C) 37", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20200926.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0057", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 38", + "(B) 25", + "(C) 30", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201012.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0058", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 36", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201028.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0059", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 25", + "(B) 32", + "(C) 21", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201215.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0060", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 20", + "(B) 24", + "(C) 18", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20201231.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0061", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 33", + "(B) 20", + "(C) 22", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210201.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0062", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 33", + "(B) 25", + "(C) 22", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210305.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0063", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 31", + "(B) 23", + "(C) 39", + "(D) 38", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210321.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0064", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 23", + "(B) 19", + "(C) 32", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210406.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0065", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 47", + "(B) 43", + "(C) 35", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210422.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0066", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 41", + "(B) 32", + "(C) 24", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210508.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0067", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 40", + "(B) 20", + "(C) 29", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210524.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0068", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 37", + "(B) 25", + "(C) 26", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210609.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0069", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 23", + "(B) 37", + "(C) 31", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210625.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0070", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 26", + "(B) 39", + "(C) 54", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210711.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0071", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 29", + "(C) 37", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210812.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0072", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 41", + "(B) 54", + "(C) 30", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210828.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0073", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 43", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20210913.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0074", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 37", + "(B) 45", + "(C) 24", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20211015.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0075", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 54", + "(B) 40", + "(C) 26", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20211031.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0076", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 33", + "(B) 41", + "(C) 22", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220220.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0077", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 21", + "(B) 35", + "(C) 47", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220612.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0078", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 29", + "(B) 38", + "(C) 49", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220628.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0079", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 43", + "(B) 38", + "(C) 32", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220714.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0080", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 24", + "(B) 36", + "(C) 45", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220730.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0081", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 41", + "(C) 51", + "(D) 56", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220815.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0082", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 53", + "(B) 39", + "(C) 46", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220831.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0083", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 56", + "(B) 26", + "(C) 53", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20220916.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0084", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 48", + "(B) 60", + "(C) 59", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20221119.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0085", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 63", + "(B) 61", + "(C) 35", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20221205.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0086", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 26", + "(B) 33", + "(C) 19", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230122.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0087", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 59", + "(B) 32", + "(C) 44", + "(D) 57", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230428.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0088", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 65", + "(B) 64", + "(C) 47", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230802.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0089", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 28", + "(B) 26", + "(C) 25", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20230903.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0090", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 34", + "(B) 36", + "(C) 26", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC08_165030_20231208.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0091", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 43", + "(B) 33", + "(C) 23", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220127.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0092", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 30", + "(B) 18", + "(C) 23", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220212.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0093", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 39", + "(C) 43", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220401.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0094", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 38", + "(B) 23", + "(C) 35", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220519.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0095", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 33", + "(B) 28", + "(C) 23", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220604.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0096", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 31", + "(B) 38", + "(C) 47", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220620.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0097", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 53", + "(B) 50", + "(C) 41", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220722.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0098", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 47", + "(B) 49", + "(C) 38", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220823.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0099", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 53", + "(B) 55", + "(C) 41", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20220924.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0100", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 38", + "(B) 48", + "(C) 24", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20221111.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0101", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 45", + "(B) 36", + "(C) 50", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20221213.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0102", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 32", + "(B) 41", + "(C) 40", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230130.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0103", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 24", + "(B) 32", + "(C) 44", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230319.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0104", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 28", + "(B) 39", + "(C) 35", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230420.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0105", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 45", + "(B) 24", + "(C) 37", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230623.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0106", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 32", + "(B) 27", + "(C) 55", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230810.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0107", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 23", + "(B) 36", + "(C) 28", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20230927.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0108", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 42", + "(B) 34", + "(C) 25", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20231013.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0109", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 34", + "(B) 24", + "(C) 28", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LC09_165030_20231029.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0110", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 166", + "(B) 222", + "(C) 225", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060531.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0111", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 139", + "(B) 173", + "(C) 175", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060718.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0112", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 171", + "(B) 125", + "(C) 95", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060819.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0113", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 173", + "(B) 97", + "(C) 187", + "(D) 140", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060904.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0114", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 96", + "(B) 83", + "(C) 69", + "(D) 88", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20060920.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0115", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 104", + "(B) 140", + "(C) 138", + "(D) 130", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20061006.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0116", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 97", + "(B) 71", + "(C) 59", + "(D) 128", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070518.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0117", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 124", + "(B) 215", + "(C) 172", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070806.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0118", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 195", + "(B) 203", + "(C) 161", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070822.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0119", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 92", + "(B) 79", + "(C) 145", + "(D) 121", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20070923.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0120", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 40", + "(B) 50", + "(C) 28", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080520.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0121", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 20", + "(B) 40", + "(C) 37", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080707.png" + ] + }, + { + "Question_id": "Biosphere/Environmental pollution monitoring/Perception/Terrestrial oil spill counting/0122", + "Question Type": "Single Choice", + "Text": "This image is a natural color image from the Landsat satellite with a spatial resolution of 30 m. How many oil spills are there in the image?", + "L1-task": "Biosphere", + "L2-task": "Environmental pollution monitoring", + "L3-task": "Perception", + "L4-task": "Terrestrial oil spill counting", + "Dataset": "ROSID", + "Answer Choices": [ + "(A) 167", + "(B) 97", + "(C) 128", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Ecological_spherev1/Environmental pollution monitoring/images/LT05_165030_20080723.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_assessment.json b/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..84939f01fb40a0ab81e052e8441abd889a5ad357 --- /dev/null +++ b/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_assessment.json @@ -0,0 +1,7802 @@ +[ + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0000", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0001", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0002", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0003", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0004", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0005", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0006", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0007", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0008", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0009", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0010", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0011", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0012", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0013", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0014", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0015", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0016", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0017", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0018", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0019", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0020", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0021", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0022", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0023", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0024", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0025", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0026", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0027", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0028", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0029", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0030", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0031", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0032", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0033", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0034", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0035", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0036", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0037", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0038", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0039", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0040", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0041", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0042", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0043", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0044", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0045", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0046", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0047", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0048", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0049", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0050", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0051", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0052", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0053", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0054", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0055", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0056", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0057", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0058", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0059", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0060", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0061", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0062", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0063", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0064", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0065", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0066", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0067", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0068", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0069", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0070", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0071", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0072", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0073", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0074", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0075", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0076", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0077", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0078", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0079", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0080", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0081", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0082", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0083", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0084", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0085", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0086", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0087", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0088", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0089", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0090", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0091", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0092", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0093", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0094", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0095", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0096", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0097", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0098", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0099", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0100", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0101", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0102", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0103", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0104", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0105", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0106", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0107", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0108", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0109", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0110", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0111", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0112", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0113", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0114", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0115", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0116", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0117", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0118", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0119", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0120", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0121", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0122", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0123", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0124", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0125", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0126", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0127", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0128", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0129", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0130", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0131", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0132", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0133", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0134", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0135", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0136", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0137", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0138", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0139", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0140", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0141", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0142", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0143", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0144", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0145", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0146", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0147", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0148", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0149", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0150", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0151", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0152", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0153", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0154", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0155", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0156", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0157", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0158", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0159", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0160", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0161", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0162", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0163", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0164", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0165", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0166", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0167", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0168", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0169", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0170", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0171", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0172", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0173", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0174", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0175", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0176", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0177", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0178", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0179", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0180", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0181", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0182", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0183", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0184", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0185", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0186", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0187", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0188", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0189", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0190", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0191", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0192", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0193", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0194", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0195", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0196", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0197", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0198", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0199", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0200", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0201", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0202", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0203", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0204", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0205", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0206", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0207", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0208", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0209", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0210", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0211", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0212", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0213", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0214", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0215", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0216", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0217", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0218", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0219", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0220", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0221", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0222", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0223", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0224", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0225", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0226", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0227", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0228", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0229", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0230", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0231", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0232", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0233", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0234", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0235", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0236", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0237", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0238", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0239", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0240", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0241", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0242", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0243", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0244", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0245", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0246", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0247", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0248", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0249", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0250", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0251", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0252", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0253", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0254", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0255", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0256", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0257", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0258", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0259", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0260", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0261", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0262", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0263", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0264", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0265", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0266", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0267", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0268", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0269", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0270", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0271", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0272", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0273", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0274", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0275", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0276", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0277", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0278", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0279", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0280", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0281", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0282", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0283", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0284", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0285", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0286", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0287", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0288", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0289", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0290", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0291", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0292", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0293", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0294", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0295", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0296", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0297", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0298", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint assessment/0299", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is this area influenced by human activities?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint assessment", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) Wilderness: have not been influenced by human activities", + "(B) Intact: slightly influenced by human activities", + "(C) Modified: greatly influenced by human activities", + "(D) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band07.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_index_estimation.json b/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_index_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..4768f94451565b4583c9deedeb885c03fc237431 --- /dev/null +++ b/jsons/Biosphere/Human_footprint_assessment/Reasoning/Human_footprint_index_estimation.json @@ -0,0 +1,8102 @@ +[ + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0000", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_98_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0001", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_99_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0002", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_97_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0003", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_93_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0004", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_94_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0005", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_95_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0006", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_96_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0007", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_90_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0008", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_91_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0009", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_92_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0010", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_9_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0011", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_87_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0012", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_88_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0013", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_89_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0014", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_84_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0015", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_85_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0016", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_86_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0017", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_80_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0018", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_81_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0019", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_82_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0020", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_83_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0021", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_8_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0022", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_77_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0023", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_78_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0024", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_79_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0025", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_74_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0026", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_75_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0027", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_76_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0028", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_70_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0029", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_71_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0030", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_72_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0031", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_73_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0032", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_7_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0033", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_67_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0034", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_68_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0035", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_69_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0036", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_63_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0037", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_64_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0038", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_65_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0039", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_66_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0040", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_6_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0041", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_60_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0042", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_61_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0043", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_62_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0044", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_56_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0045", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_57_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0046", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_58_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0047", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_59_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0048", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_52_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0049", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_53_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0050", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_54_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0051", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_55_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0052", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_5_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0053", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_49_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0054", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_50_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0055", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_51_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0056", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_43_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0057", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_44_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0058", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_45_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0059", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_46_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0060", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_47_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0061", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_48_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0062", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_42_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0063", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_4_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0064", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_39_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0065", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_40_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0066", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_41_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0067", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_35_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0068", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_36_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0069", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_37_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0070", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_38_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0071", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_32_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0072", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_33_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0073", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_34_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0074", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_30_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0075", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_31_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0076", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_300_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0077", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_3_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0078", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_297_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0079", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_298_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0080", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_299_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0081", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_293_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0082", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_294_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0083", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_295_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0084", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_296_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0085", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_29_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0086", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_290_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0087", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_291_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0088", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_292_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0089", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_287_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0090", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_288_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0091", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_289_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0092", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_283_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0093", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_284_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0094", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_285_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0095", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_286_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0096", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_28_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0097", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_280_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0098", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_281_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0099", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_282_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0100", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_275_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0101", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_276_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0102", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_277_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0103", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_278_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0104", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_279_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0105", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_272_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0106", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_273_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0107", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_274_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0108", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_27_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0109", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_269_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0110", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_270_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0111", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_271_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0112", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_264_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0113", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_265_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0114", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_266_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0115", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_267_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0116", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_268_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0117", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_260_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0118", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_261_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0119", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_262_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0120", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_263_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0121", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_26_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0122", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_257_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0123", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_258_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0124", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_259_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0125", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_254_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0126", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_255_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0127", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_256_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0128", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_250_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0129", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_251_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0130", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_252_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0131", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_253_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0132", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_25_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0133", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_249_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0134", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_244_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0135", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_245_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0136", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_246_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0137", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_247_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0138", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_248_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0139", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_240_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0140", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_241_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0141", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_242_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0142", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_243_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0143", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_24_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0144", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_238_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0145", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_239_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0146", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_234_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0147", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_235_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0148", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_236_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0149", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_237_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0150", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_23_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0151", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_230_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0152", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_231_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0153", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_232_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0154", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_233_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0155", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_227_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0156", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_228_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0157", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_229_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0158", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_222_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0159", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_223_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0160", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_224_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0161", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_225_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0162", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_226_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0163", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_22_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0164", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_218_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0165", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_219_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0166", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_220_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0167", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_221_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0168", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_215_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0169", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_216_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0170", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_217_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0171", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_211_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0172", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_212_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0173", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_213_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0174", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_214_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0175", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_21_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0176", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_208_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0177", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_209_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0178", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_210_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0179", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_204_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0180", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_205_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0181", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_206_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0182", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_207_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0183", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_200_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0184", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_201_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0185", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_202_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0186", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_203_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0187", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_2_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0188", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_20_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0189", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_198_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0190", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_199_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0191", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_194_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0192", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_195_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0193", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_196_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0194", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_197_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0195", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_191_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0196", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_192_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0197", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_193_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0198", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_19_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0199", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_190_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0200", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_186_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0201", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_187_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0202", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_188_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0203", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_189_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0204", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_182_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0205", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_183_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0206", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_184_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0207", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_185_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0208", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_18_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0209", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_179_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0210", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_180_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0211", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_181_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0212", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_175_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0213", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_176_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0214", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_177_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0215", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_178_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0216", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_171_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0217", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_172_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0218", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_173_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0219", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_174_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0220", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_17_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0221", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_167_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0222", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_168_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0223", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_169_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0224", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_170_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0225", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_165_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0226", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_166_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0227", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_160_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0228", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_161_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0229", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_162_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0230", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_163_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0231", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_164_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0232", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_16_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0233", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_157_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0234", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_158_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0235", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_159_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0236", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_153_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0237", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_154_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0238", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_155_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0239", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_156_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0240", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_15_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0241", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_149_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0242", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_150_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0243", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_151_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0244", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_152_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0245", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_145_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0246", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_146_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0247", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_147_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0248", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_148_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0249", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_140_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0250", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_141_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0251", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_142_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0252", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_143_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0253", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_144_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0254", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_14_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0255", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_136_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0256", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_137_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0257", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_138_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0258", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_139_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0259", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_132_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0260", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_133_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0261", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_134_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0262", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_135_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0263", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_13_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0264", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_129_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0265", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_130_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0266", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_131_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0267", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_124_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0268", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_125_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0269", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_126_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0270", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_127_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0271", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_128_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0272", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_120_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0273", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_121_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0274", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_122_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0275", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_123_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0276", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_12_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0277", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_116_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0278", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_117_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0279", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_118_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0280", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_119_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0281", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_112_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0282", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_113_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0283", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_114_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0284", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_115_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0285", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_11_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0286", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_109_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0287", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_110_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0288", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_111_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0289", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_104_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0290", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_105_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0291", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_106_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0292", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_107_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0293", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_108_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0294", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_10_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0295", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_100_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0296", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_101_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0297", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_102_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0298", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_103_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Human footprint assessment/Reasoning/Human footprint index estimation/0299", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Human footprint index in this area?", + "L1-task": "Biosphere", + "L2-task": "Human footprint assessment", + "L3-task": "Reasoning", + "L4-task": "Human footprint index estimation", + "Dataset": "HFP2018", + "Answer Choices": [ + "(A) 0-1", + "(B) 1-4", + "(C) 4-8", + "(D) 8-50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band01.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band02.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band03.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band04.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band05.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band06.jpg", + "raw/Biosphere/Human footprint assessment/MODIS/GEE_patches_1_band07.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Prediction.json b/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..f27644bc43000ea0472f600ab7ef48c6811e0b3b --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Prediction.json @@ -0,0 +1,10502 @@ +[ + { + "Question_id": "Tree Species Prediction/0000", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_7_154068_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.1221627706823° N, and the longitude is 10.304251685155798° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Pinus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0001", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_89992_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.516970308466874° N, and the longitude is 10.901631567743864° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Acer", + "(C) Quercus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0002", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48023_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.978165727787° N, and the longitude is 9.693921858207887° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pinus", + "(C) Picea", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0003", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82589_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.30790641871843° N, and the longitude is 7.602770603355055° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Quercus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0004", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_274536_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.03848250669075° N, and the longitude is 8.28781002360708° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Quercus", + "(C) Betula", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0005", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_162012_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.1810169625914° N, and the longitude is 9.572037228655574° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Tilia", + "(C) Larix", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0006", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_90397_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.49570205857832° N, and the longitude is 7.689647397495493° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Prunus", + "(C) Abies", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0007", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45267_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.73064018150782° N, and the longitude is 9.718902543564948° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Picea", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0008", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_275352_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.04287750712594° N, and the longitude is 8.137146309090165° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Prunus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0009", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_173091_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.271444201996346° N, and the longitude is 9.442820265508761° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Fraxinus", + "(C) Quercus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0010", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_9053_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.5178644418671° N, and the longitude is 10.066478379676042° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Betula", + "(C) Populus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0011", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_31603_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.512777749540206° N, and the longitude is 10.325476399517768° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pinus", + "(C) Fraxinus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0012", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_39966_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.571211295609416° N, and the longitude is 9.331286587123293° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Larix", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0013", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_35826_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.359497276524195° N, and the longitude is 10.83302791688661° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Larix", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0014", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_283852_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.085085207646664° N, and the longitude is 10.3481168821147° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Cleared", + "(C) Tilia", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0015", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_282403_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.07081318167543° N, and the longitude is 10.871395804686163° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Fraxinus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0016", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_11_86949_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.597082597509406° N, and the longitude is 10.600453231389617° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Quercus", + "(C) Tilia", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0017", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20897_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.71656180013929° N, and the longitude is 8.793542592976323° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Cleared", + "(C) Alnus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0018", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_142703_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.979790581447254° N, and the longitude is 10.413640230256846° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Quercus", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0019", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79271_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.517664274926325° N, and the longitude is 9.143951858751919° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Pseudotsuga", + "(C) Alnus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0020", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_46150_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.91714621262265° N, and the longitude is 10.263115602953803° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fagus", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0021", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_61167_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.94961906577159° N, and the longitude is 10.170170879982605° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fraxinus", + "(C) Prunus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0022", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_1_93020_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.61194904860429° N, and the longitude is 10.07652424459483° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Alnus", + "(C) Quercus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0023", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_39407_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.569390256799096° N, and the longitude is 9.355186683090894° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Picea", + "(C) Pinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0024", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9062_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.90061512866202° N, and the longitude is 10.611264193577995° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Alnus", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0025", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_26021_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.00416728475919° N, and the longitude is 9.362061549623531° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pseudotsuga", + "(C) Populus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0026", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_86446_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.283111188385604° N, and the longitude is 10.268674473757828° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Betula", + "(C) Fraxinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0027", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_272469_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.02484141747214° N, and the longitude is 8.261207770926156° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Larix", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0028", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22812_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.674034134579436° N, and the longitude is 10.153426154955014° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Cleared", + "(C) Acer", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0029", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_27636_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.72535520370859° N, and the longitude is 9.699162809762962° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Pseudotsuga", + "(C) Fagus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0030", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38002_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.09357304307297° N, and the longitude is 10.85980377526747° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Pseudotsuga", + "(C) Fagus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0031", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_9057_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.51781188592313° N, and the longitude is 10.072239946852005° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Fraxinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0032", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_172167_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.26519694623962° N, and the longitude is 9.431039921429882° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Pseudotsuga", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0033", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_78816_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.74917690563981° N, and the longitude is 9.685256662419189° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Tilia", + "(C) Prunus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0034", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_151829_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.11418652652993° N, and the longitude is 9.635411973394477° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Fagus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0035", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_58436_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.24587674809184° N, and the longitude is 8.65503127308732° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Tilia", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0036", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_174583_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.281209956501684° N, and the longitude is 9.473688642288918° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Prunus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0037", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_153203_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.12468926732267° N, and the longitude is 9.216501109964431° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Prunus", + "(C) Fraxinus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0038", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_1_33799_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.42895479173804° N, and the longitude is 9.758409734677318° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Abies", + "(C) Pseudotsuga", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0039", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_307840_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.21566244049672° N, and the longitude is 10.861237796178871° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pinus", + "(C) Betula", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0040", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_61129_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.29643305335315° N, and the longitude is 10.246532585146346° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Abies", + "(C) Pinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0041", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_305708_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.198525118082074° N, and the longitude is 10.619549574538192° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Acer", + "(C) Populus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0042", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_164452_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.19919917419688° N, and the longitude is 9.257816101558573° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0043", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_46672_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.70168494761239° N, and the longitude is 10.640212532828384° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Fraxinus", + "(C) Picea", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0044", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34611_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.00811211738383° N, and the longitude is 9.397218586446064° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Alnus", + "(C) Fraxinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0045", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47317_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.25195972235547° N, and the longitude is 9.222781688991569° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Betula", + "(C) Picea", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0046", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_28277_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.27628255290758° N, and the longitude is 9.467900743515935° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fagus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0047", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_27849_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.24951681353919° N, and the longitude is 10.82208661594616° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Larix", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0048", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5243_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.94898687211247° N, and the longitude is 9.439582343169414° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Betula", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0049", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_83786_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.516768078557384° N, and the longitude is 9.63679608171355° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Tilia", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0050", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47268_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.16174172341492° N, and the longitude is 8.095812306729° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Tilia", + "(C) Populus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0051", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_254830_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.90707577095974° N, and the longitude is 8.122009102508665° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Acer", + "(C) Prunus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0052", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_10_188751_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.39955019953548° N, and the longitude is 10.48432823901685° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Pinus", + "(C) Quercus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0053", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62056_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.085671319500555° N, and the longitude is 10.327624963750015° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Populus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0054", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_78849_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.114846061145684° N, and the longitude is 9.612178505995692° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pseudotsuga", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0055", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_64091_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.09819406516794° N, and the longitude is 10.784540395225212° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Larix", + "(C) Abies", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0056", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48395_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.10127413068777° N, and the longitude is 9.52821786020756° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Pinus", + "(C) Cleared", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0057", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_299431_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.15708458490244° N, and the longitude is 10.416154645898768° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Abies", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0058", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_326976_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.363897621549384° N, and the longitude is 9.829625404710905° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Prunus", + "(C) Populus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0059", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48005_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.7275332155693° N, and the longitude is 9.606821911322369° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0060", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_62480_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.145244392203935° N, and the longitude is 10.696093307741943° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Tilia", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0061", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_1_87948_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.68066193139437° N, and the longitude is 9.774792200257398° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Quercus", + "(C) Alnus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0062", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_2_38185_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.955948767949586° N, and the longitude is 9.768143607684623° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Larix", + "(C) Pinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0063", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24313_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.722859430797925° N, and the longitude is 7.128101794499755° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Cleared", + "(C) Picea", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0064", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_76432_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.64640205208199° N, and the longitude is 9.590585737059977° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pseudotsuga", + "(C) Picea", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0065", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_59331_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.04413605724699° N, and the longitude is 9.554293059624571° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pinus", + "(C) Cleared", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0066", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23705_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.9557442936629° N, and the longitude is 10.177919031102665° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Cleared", + "(C) Acer", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0067", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_33018_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.589300784978036° N, and the longitude is 9.992539636110786° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Quercus", + "(C) Betula", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0068", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_7_31849_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.01308082297524° N, and the longitude is 8.484646920586341° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Quercus", + "(C) Prunus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0069", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27712_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.478710138850694° N, and the longitude is 7.550389479086471° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Populus", + "(C) Fagus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0070", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_293428_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.137255273949634° N, and the longitude is 9.858122984097502° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Cleared", + "(C) Populus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0071", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_55815_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.15107113876204° N, and the longitude is 9.371521485515537° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Prunus", + "(C) Abies", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0072", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_15479_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.60935398473624° N, and the longitude is 10.087389058221884° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Acer", + "(C) Pseudotsuga", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0073", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34135_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.884452702032° N, and the longitude is 9.480018261762698° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0074", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_170170_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.24783816763414° N, and the longitude is 9.50261631762981° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Betula", + "(C) Picea", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0075", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20983_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.60966391994097° N, and the longitude is 10.329421085380524° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Fagus", + "(C) Populus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0076", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_83893_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.52568465721538° N, and the longitude is 9.278291974701943° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Acer", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0077", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_30086_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.414915254272124° N, and the longitude is 7.494882678997019° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fraxinus", + "(C) Populus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0078", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_9_75955_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.9809842918188° N, and the longitude is 10.21196094470904° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Betula", + "(C) Pseudotsuga", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0079", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_43173_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.93268750106956° N, and the longitude is 7.8635304576021285° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Populus", + "(C) Larix", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0080", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75850_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.55327209468532° N, and the longitude is 7.757651857479169° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Fagus", + "(C) Pseudotsuga", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0081", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_3_55141_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.26457139343298° N, and the longitude is 9.555983577695551° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Acer", + "(C) Pseudotsuga", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0082", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_23208_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.642127333195624° N, and the longitude is 10.31064965593528° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pinus", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0083", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63297_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.57592216579583° N, and the longitude is 9.919983969942773° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pseudotsuga", + "(C) Populus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0084", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23253_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.208205500610816° N, and the longitude is 9.194958336019258° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Cleared", + "(C) Pinus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0085", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_1_93708_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.550493991020524° N, and the longitude is 6.873963995445862° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Alnus", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0086", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_47583_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.689668975096424° N, and the longitude is 10.466226543038653° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Betula", + "(C) Prunus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0087", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_61565_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.61164969365055° N, and the longitude is 10.19876152515492° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Populus", + "(C) Pinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0088", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_32672_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.19272941344908° N, and the longitude is 9.550244057460107° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Picea", + "(C) Larix", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0089", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47630_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.78532079691594° N, and the longitude is 9.58416924133913° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Acer", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0090", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22748_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.72659991853633° N, and the longitude is 8.66576099495503° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Abies", + "(C) Fagus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0091", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9674_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.974555989589° N, and the longitude is 10.50491822255429° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Acer", + "(C) Tilia", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0092", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_1_38162_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.49789250606025° N, and the longitude is 9.638680432982227° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Populus", + "(C) Acer", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0093", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_86063_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.398534139115796° N, and the longitude is 7.445550569057634° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Quercus", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0094", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48629_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.42810167794995° N, and the longitude is 10.087242396402274° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Alnus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0095", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48947_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.706676660652384° N, and the longitude is 10.612954154967024° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Picea", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0096", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_2_43286_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.4493156116104° N, and the longitude is 10.093144453856748° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Betula", + "(C) Larix", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0097", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_85315_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92165042322153° N, and the longitude is 8.475997068003451° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Quercus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0098", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_7559_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.11629065966881° N, and the longitude is 8.131827152881877° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Quercus", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0099", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23968_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.15311566023169° N, and the longitude is 9.970220790931469° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Cleared", + "(C) Pseudotsuga", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0100", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24643_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.84709614849539° N, and the longitude is 8.70123570535786° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Acer", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0101", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_1_81712_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.66514122832721° N, and the longitude is 9.515457631458569° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Betula", + "(C) Cleared", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0102", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_28674_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.1966373618365° N, and the longitude is 9.333040715942209° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Acer", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0103", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_45305_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.162853722808435° N, and the longitude is 9.56034132241493° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Tilia", + "(C) Picea", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0104", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_39847_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.20291986089261° N, and the longitude is 9.327888857405485° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Quercus", + "(C) Alnus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0105", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_154443_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.131392427718055° N, and the longitude is 9.610830675623852° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Picea", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0106", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62990_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.33306238466814° N, and the longitude is 10.734836887623063° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Acer", + "(C) Betula", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0107", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_4749_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.44281114052496° N, and the longitude is 10.015824708399824° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Alnus", + "(C) Quercus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0108", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87789_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.00622171714647° N, and the longitude is 8.473864029462726° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pseudotsuga", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0109", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_33632_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.51630781559136° N, and the longitude is 10.096235441402609° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Tilia", + "(C) Fagus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0110", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_41290_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.72332964046176° N, and the longitude is 9.586031821144712° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Picea", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0111", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_35948_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.289695035248876° N, and the longitude is 10.47248371406571° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Populus", + "(C) Larix", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0112", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_60212_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.10292093807317° N, and the longitude is 10.808323298749922° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Betula", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0113", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_49279_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.6231824986112° N, and the longitude is 8.693263438359784° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Cleared", + "(C) Fraxinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0114", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87150_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.060100971539214° N, and the longitude is 8.453709045816531° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Quercus", + "(C) Abies", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0115", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_86565_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.06528762505407° N, and the longitude is 10.222022863391018° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Quercus", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0116", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22901_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87347348667696° N, and the longitude is 9.520097014348178° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Alnus", + "(C) Cleared", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0117", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_93542_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.59540685446803° N, and the longitude is 8.949934558279734° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Betula", + "(C) Quercus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0118", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_88351_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.133327522302736° N, and the longitude is 9.19447203689239° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Prunus", + "(C) Alnus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0119", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_27239_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.38325394087896° N, and the longitude is 10.777921848832692° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Betula", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0120", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_77615_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.74397966992071° N, and the longitude is 7.832913162381881° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Pseudotsuga", + "(C) Abies", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0121", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_258727_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92756155503578° N, and the longitude is 8.584060084725781° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Prunus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0122", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_340186_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.538843613357756° N, and the longitude is 7.911400478046818° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Prunus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0123", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_165749_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.20709214818314° N, and the longitude is 9.335392127038581° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Abies", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0124", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_265005_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.95887038786064° N, and the longitude is 10.219178736336241° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Pinus", + "(C) Quercus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0125", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_80685_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.637932826691575° N, and the longitude is 7.723097297860711° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fraxinus", + "(C) Quercus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0126", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_86654_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.29495427275282° N, and the longitude is 9.468192225676631° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Quercus", + "(C) Alnus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0127", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63380_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.09874252421572° N, and the longitude is 10.881104782447322° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fraxinus", + "(C) Tilia", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0128", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_40861_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.24832149313668° N, and the longitude is 10.717223892521984° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fagus", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0129", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27150_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.79838337757051° N, and the longitude is 9.57989779994808° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fraxinus", + "(C) Fagus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0130", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_62193_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.30518355788509° N, and the longitude is 10.230293495251491° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Populus", + "(C) Pinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0131", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_5047_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.44835160193098° N, and the longitude is 9.99868567807092° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fagus", + "(C) Fagus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0132", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_62747_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.11046910258498° N, and the longitude is 10.743391464312225° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Abies", + "(C) Pinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0133", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_62072_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.08652498925151° N, and the longitude is 10.814203270711694° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Larix", + "(C) Fraxinus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0134", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63447_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.75747879182265° N, and the longitude is 9.80397297152733° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Pinus", + "(C) Larix", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0135", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_30524_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.202719051329794° N, and the longitude is 9.733517688830819° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fraxinus", + "(C) Tilia", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0136", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_7_85495_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.42543320142073° N, and the longitude is 9.49229393236899° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Picea", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0137", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_64729_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.75707875630125° N, and the longitude is 7.8785186330947825° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Fraxinus", + "(C) Pseudotsuga", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0138", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_84935_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.81726896982256° N, and the longitude is 9.07286756210247° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Acer", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0139", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_5207_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.94279788723844° N, and the longitude is 10.231748040189848° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Picea", + "(C) Acer", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0140", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_86491_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.340421789018656° N, and the longitude is 10.708166337490514° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Acer", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0141", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_289194_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.103144422080405° N, and the longitude is 10.87279972829357° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Betula", + "(C) Pinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0142", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_25200_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.751772377632875° N, and the longitude is 9.429383679838793° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Quercus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0143", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24204_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.363529730954376° N, and the longitude is 8.886966942913405° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Tilia", + "(C) Alnus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0144", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_26628_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.88897857612464° N, and the longitude is 8.796633569165996° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Tilia", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0145", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_304881_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.19702799036548° N, and the longitude is 9.916178776163058° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Pinus", + "(C) Tilia", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0146", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22358_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.883506066324365° N, and the longitude is 10.255035126134802° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Picea", + "(C) Pinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0147", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_42355_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.947352310241826° N, and the longitude is 7.865502486927044° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Fraxinus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0148", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24694_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.918803481392914° N, and the longitude is 8.152324023018993° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Cleared", + "(C) Larix", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0149", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_34701_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.21913836000899° N, and the longitude is 8.087058376408711° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Abies", + "(C) Fraxinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0150", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_87345_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.414814699606325° N, and the longitude is 9.995822623253584° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Quercus", + "(C) Fagus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0151", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_76814_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.502585320706764° N, and the longitude is 7.530570951146302° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Betula", + "(C) Pseudotsuga", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0152", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_7_148508_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.058555601170575° N, and the longitude is 10.200333151382033° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Acer", + "(C) Betula", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0153", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_25716_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.9204845035896° N, and the longitude is 8.479513480629251° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0154", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_8087_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87568967511805° N, and the longitude is 10.233052360084294° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Populus", + "(C) Prunus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0155", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_29711_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.1960815246603° N, and the longitude is 9.275110922055225° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Alnus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0156", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_64134_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.19104201427402° N, and the longitude is 10.605958491543912° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Tilia", + "(C) Pinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0157", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_2_36676_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.934395657080046° N, and the longitude is 9.583214393754654° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Betula", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0158", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_40893_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.88081920706119° N, and the longitude is 8.304516492193022° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Pseudotsuga", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0159", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_9459_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.208674466346125° N, and the longitude is 9.187663939684974° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fagus", + "(C) Populus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0160", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_4_84541_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.543756574559474° N, and the longitude is 9.666411020264386° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Quercus", + "(C) Fraxinus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0161", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_30885_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.97447914157415° N, and the longitude is 10.513396573281621° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fraxinus", + "(C) Pseudotsuga", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0162", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_293161_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.12368260064851° N, and the longitude is 10.881162884248683° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0163", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38087_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.42481935730722° N, and the longitude is 10.090228790778252° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Fraxinus", + "(C) Alnus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0164", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_43214_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.201043047250614° N, and the longitude is 9.855187764830067° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Tilia", + "(C) Larix", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0165", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_90346_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.51588380703019° N, and the longitude is 9.646129958797303° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Abies", + "(C) Betula", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0166", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_32070_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.574524253917126° N, and the longitude is 10.05239858062986° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0167", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_1_37900_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.519913456134745° N, and the longitude is 9.608415173478486° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Populus", + "(C) Prunus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0168", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22900_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.517276275136965° N, and the longitude is 7.871189277436735° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Pinus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0169", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_11377_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.569099910889356° N, and the longitude is 9.962388668521479° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Alnus", + "(C) Betula", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0170", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60003_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.749584495736876° N, and the longitude is 9.25250170163854° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Abies", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0171", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48006_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.658373075594405° N, and the longitude is 10.547056381683854° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Cleared", + "(C) Alnus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0172", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_8527_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.811465297267105° N, and the longitude is 9.065108791025546° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Alnus", + "(C) Betula", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0173", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_33313_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.82264432124509° N, and the longitude is 10.166122546187848° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Larix", + "(C) Acer", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0174", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_60556_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92902222264383° N, and the longitude is 10.175702971292912° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Pinus", + "(C) Fraxinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0175", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22508_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.72873158774577° N, and the longitude is 9.529294932197175° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Quercus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0176", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21506_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.83276947031268° N, and the longitude is 10.396604583354236° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Abies", + "(C) Prunus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0177", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_1_36658_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.61997176447665° N, and the longitude is 9.761716748998492° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Larix", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0178", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24878_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.99550356549902° N, and the longitude is 9.691715088972723° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Cleared", + "(C) Pinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0179", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22336_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.51911887930076° N, and the longitude is 9.511198591525257° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Larix", + "(C) Picea", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0180", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63073_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.56853246618675° N, and the longitude is 9.916724816654662° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Abies", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0181", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_62468_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.61705445377615° N, and the longitude is 9.999635170995909° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fraxinus", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0182", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_89737_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.76448358736854° N, and the longitude is 9.40401739879524° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Betula", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0183", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38877_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.41333529419936° N, and the longitude is 10.016387147740087° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Betula", + "(C) Abies", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0184", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_87072_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.03256843694627° N, and the longitude is 9.585583689803798° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Quercus", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0185", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6770_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.08326720331898° N, and the longitude is 9.94972418192811° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Pseudotsuga", + "(C) Picea", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0186", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78282_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.8040222627971° N, and the longitude is 9.248819851261533° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Alnus", + "(C) Acer", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0187", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_85946_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.80686670914224° N, and the longitude is 8.716073367927077° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Quercus", + "(C) Acer", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0188", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_49704_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.83229812488713° N, and the longitude is 10.273745871334551° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fraxinus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0189", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21139_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.9976235950086° N, and the longitude is 10.297146709747992° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Quercus", + "(C) Cleared", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0190", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_60674_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.79470173079413° N, and the longitude is 9.545343547651738° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pinus", + "(C) Pseudotsuga", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0191", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_37625_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.0670032544554° N, and the longitude is 10.35913350008129° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pinus", + "(C) Betula", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0192", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_26347_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.9874477528885° N, and the longitude is 9.413477349880592° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Alnus", + "(C) Cleared", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0193", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_26704_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.477295983985584° N, and the longitude is 9.198724323236183° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Prunus", + "(C) Pseudotsuga", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0194", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_43961_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.13733743081328° N, and the longitude is 9.959436130785381° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Fagus", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0195", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_214417_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.58141963439917° N, and the longitude is 9.000412513207387° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Cleared", + "(C) Tilia", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0196", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_89382_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.30076119964834° N, and the longitude is 7.61734636811727° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Quercus", + "(C) Pseudotsuga", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0197", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62442_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.590911759651256° N, and the longitude is 8.53932601084801° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Tilia", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0198", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82831_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.91308602249821° N, and the longitude is 8.16270741988521° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fraxinus", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0199", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_36781_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.280606248758176° N, and the longitude is 10.497593030039736° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Alnus", + "(C) Fraxinus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0200", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_34282_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.513899742794884° N, and the longitude is 10.101032250915289° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Quercus", + "(C) Tilia", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0201", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45014_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.275387374908604° N, and the longitude is 9.484805012889193° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Pinus", + "(C) Picea", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0202", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_1_32358_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.64326831084554° N, and the longitude is 10.420164331301185° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Populus", + "(C) Fraxinus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0203", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_272375_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.02468446042534° N, and the longitude is 8.392362609638834° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Betula", + "(C) Prunus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0204", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22402_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.82350137664212° N, and the longitude is 10.485098560350162° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Prunus", + "(C) Larix", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0205", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_79345_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.51617163577436° N, and the longitude is 9.21734093607899° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Pseudotsuga", + "(C) Prunus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0206", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_75102_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.13472906797373° N, and the longitude is 9.605302697695828° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pseudotsuga", + "(C) Fraxinus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0207", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_30128_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.57063538910101° N, and the longitude is 10.03462327342459° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fraxinus", + "(C) Fagus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0208", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_56168_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.63964529450387° N, and the longitude is 8.866839036869088° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pinus", + "(C) Acer", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0209", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20063_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.675337203232694° N, and the longitude is 10.468586397801891° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pinus", + "(C) Cleared", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0210", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_45010_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.77462228764106° N, and the longitude is 10.355359366440833° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Populus", + "(C) Picea", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0211", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_3_58060_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.247619134476764° N, and the longitude is 8.653825656968625° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Abies", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0212", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_46896_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.80228305742966° N, and the longitude is 10.283826708139165° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Picea", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0213", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21030_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.27414946353804° N, and the longitude is 10.256037587734692° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Cleared", + "(C) Fagus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0214", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_8_87315_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.13406145839795° N, and the longitude is 9.382586506023065° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Cleared", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0215", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27608_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.27384564835849° N, and the longitude is 9.442872140790008° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Abies", + "(C) Picea", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0216", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_2646_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92525828839708° N, and the longitude is 8.84208183517165° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Abies", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0217", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_46939_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.77778077675064° N, and the longitude is 9.607456039603937° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Cleared", + "(C) Picea", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0218", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_25148_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.216763097946036° N, and the longitude is 9.151512790928372° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fagus", + "(C) Acer", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0219", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_144875_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.00841007084754° N, and the longitude is 9.357203545018113° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Picea", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0220", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_8936_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.08467221693819° N, and the longitude is 9.921730685583775° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Tilia", + "(C) Larix", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0221", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60889_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.12988012869349° N, and the longitude is 9.946061057707489° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Pinus", + "(C) Pinus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0222", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_4_51144_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.71331360191555° N, and the longitude is 8.669820275938141° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0223", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_8_81365_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.64930769814196° N, and the longitude is 9.269739190766145° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Betula", + "(C) Prunus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0224", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_245641_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.83087260060532° N, and the longitude is 8.889141339236138° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Cleared", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0225", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_27667_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.00111912728008° N, and the longitude is 9.401736922894429° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fagus", + "(C) Quercus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0226", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_42032_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.710630922935394° N, and the longitude is 9.630630940815843° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Tilia", + "(C) Larix", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0227", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_30237_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.51125133324856° N, and the longitude is 10.910308732377693° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Cleared", + "(C) Fraxinus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0228", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_46851_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.81954507783653° N, and the longitude is 10.44307494387239° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fraxinus", + "(C) Alnus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0229", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_29928_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.67692817960365° N, and the longitude is 10.476899998734417° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Fagus", + "(C) Larix", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0230", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_64837_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.9920271644762° N, and the longitude is 9.337309856659292° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Picea", + "(C) Pseudotsuga", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0231", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_79326_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.223858822234384° N, and the longitude is 9.21208401471631° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pseudotsuga", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0232", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_26245_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.963290174089394° N, and the longitude is 9.629019814602517° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Picea", + "(C) Fagus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0233", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_48867_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.76975436192031° N, and the longitude is 9.583882706965195° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Prunus", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0234", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21179_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.52334470209945° N, and the longitude is 9.237702627998068° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Alnus", + "(C) Pinus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0235", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21318_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.273142444020166° N, and the longitude is 10.245124206944611° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Cleared", + "(C) Pinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0236", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_62086_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.04721723229168° N, and the longitude is 11.256859285527353° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Acer", + "(C) Pinus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0237", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_85812_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.74460994192842° N, and the longitude is 9.63964645248975° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Pinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0238", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_304920_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.19012503740277° N, and the longitude is 10.575842127629677° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Larix", + "(C) Pseudotsuga", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0239", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_8_82525_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.31726939264292° N, and the longitude is 10.965315333190953° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Quercus", + "(C) Acer", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0240", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_6_159955_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.168512586154904° N, and the longitude is 9.555799273089615° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pinus", + "(C) Tilia", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0241", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75376_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.14121139751593° N, and the longitude is 10.85385945670369° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Picea", + "(C) Pseudotsuga", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0242", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_30835_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.03318931310348° N, and the longitude is 9.580735978860972° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Larix", + "(C) Populus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0243", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_9_278096_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.062959715253626° N, and the longitude is 8.508175476400794° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Fraxinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0244", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_34424_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.66914145224921° N, and the longitude is 10.364967258465185° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fraxinus", + "(C) Larix", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0245", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_321_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92241302582678° N, and the longitude is 8.844595189019147° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fraxinus", + "(C) Abies", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0246", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47785_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.14059172536001° N, and the longitude is 10.671736426183507° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Picea", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0247", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_49853_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.71665376556968° N, and the longitude is 10.63475460185225° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Betula", + "(C) Picea", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0248", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_8_85587_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.44354576410072° N, and the longitude is 9.488460517711342° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Prunus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0249", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_85083_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.49331354356396° N, and the longitude is 9.645460787228119° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Prunus", + "(C) Quercus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0250", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_64510_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.40914502536674° N, and the longitude is 10.445295032935642° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Prunus", + "(C) Populus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0251", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_46409_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.46545014856239° N, and the longitude is 7.585777046740972° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Fraxinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0252", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_40045_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.043489102700164° N, and the longitude is 9.549675899654709° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Larix", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0253", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_168277_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.22437729111207° N, and the longitude is 9.524302223266925° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Abies", + "(C) Tilia", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0254", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_41758_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.50482443668141° N, and the longitude is 7.700388918768536° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Quercus", + "(C) Larix", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0255", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_6925_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.07005407155895° N, and the longitude is 10.49999250949038° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Pseudotsuga", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0256", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6945_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.726391340240816° N, and the longitude is 10.469373440975863° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pseudotsuga", + "(C) Picea", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0257", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_153911_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.12389226347042° N, and the longitude is 10.040009758719108° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Larix", + "(C) Prunus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0258", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_48500_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.6728979076946° N, and the longitude is 10.645060379681837° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Populus", + "(C) Cleared", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0259", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_4_50744_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.71292978334831° N, and the longitude is 8.672192004935097° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Tilia", + "(C) Fraxinus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0260", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_46575_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.15489446518014° N, and the longitude is 9.017752451144494° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Prunus", + "(C) Picea", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0261", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_87556_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.36372042961969° N, and the longitude is 9.413306343040212° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Alnus", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0262", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44555_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.50491196706264° N, and the longitude is 8.996636298099453° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pseudotsuga", + "(C) Pinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0263", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_34203_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.32265337509435° N, and the longitude is 10.326209934500328° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Cleared", + "(C) Alnus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0264", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_159522_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.165781891634985° N, and the longitude is 9.563072669559855° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Quercus", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0265", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_298399_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.14630328461328° N, and the longitude is 10.81339285510234° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Alnus", + "(C) Cleared", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0266", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_33087_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.32217845727239° N, and the longitude is 10.719648754914138° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fagus", + "(C) Fraxinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0267", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_2_41382_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.605555433118845° N, and the longitude is 8.757688967475938° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Prunus", + "(C) Larix", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0268", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_49844_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.82284472205649° N, and the longitude is 9.538093395096443° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pinus", + "(C) Abies", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0269", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_28169_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.84442981045413° N, and the longitude is 10.216824101030687° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Prunus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0270", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48113_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.85582046710136° N, and the longitude is 10.538489536432373° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Picea", + "(C) Cleared", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0271", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_165279_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.20449081385164° N, and the longitude is 9.300266508779353° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Larix", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0272", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_63997_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.99822075283259° N, and the longitude is 10.300847751209014° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Tilia", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0273", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_64706_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.45062880295658° N, and the longitude is 10.644130301699358° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Tilia", + "(C) Larix", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0274", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47513_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.67292931443841° N, and the longitude is 10.581616743631464° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Abies", + "(C) Picea", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0275", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_38256_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.444693529943045° N, and the longitude is 9.214454708096648° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Larix", + "(C) Larix", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0276", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_6_54437_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.586803531405224° N, and the longitude is 9.831478513416247° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Fagus", + "(C) Cleared", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0277", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_215863_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.59470946536771° N, and the longitude is 9.211438807825965° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Prunus", + "(C) Picea", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0278", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_29243_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.07001534116105° N, and the longitude is 9.907909568938972° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Cleared", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0279", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_42086_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.54385067810349° N, and the longitude is 7.208950212086009° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Larix", + "(C) Larix", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0280", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_157277_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.15321446323501° N, and the longitude is 9.559991754965743° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Populus", + "(C) Fraxinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0281", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21912_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.650728430136894° N, and the longitude is 10.063975302890443° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Quercus", + "(C) Prunus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0282", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_77322_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.79087331920277° N, and the longitude is 10.384035897881295° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Acer", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0283", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_305123_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.198602727607074° N, and the longitude is 9.944644322544706° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Acer", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0284", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21402_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.509266074372434° N, and the longitude is 10.903374635279334° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pseudotsuga", + "(C) Fagus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0285", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_61906_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.17567375365386° N, and the longitude is 10.888605863277014° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Pinus", + "(C) Populus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0286", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27626_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.950003663151044° N, and the longitude is 9.707982206638286° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Picea", + "(C) Fagus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0287", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_152375_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.120231575201686° N, and the longitude is 9.196039633922613° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Picea", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0288", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_26352_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.26518737459628° N, and the longitude is 9.486753997821337° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Populus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0289", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_83192_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.902700479968225° N, and the longitude is 9.674427527925943° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Fraxinus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0290", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_28109_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.0661780226073° N, and the longitude is 9.628604750833171° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0291", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_82111_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.16669195467008° N, and the longitude is 10.960892864014227° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Alnus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0292", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_30291_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.49299600769118° N, and the longitude is 10.030010469318245° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Populus", + "(C) Alnus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0293", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63838_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.156565391479376° N, and the longitude is 10.437759921717577° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Picea", + "(C) Abies", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0294", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_29530_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.084200336708534° N, and the longitude is 10.531969938140062° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Fagus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0295", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_153645_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.11938632663418° N, and the longitude is 10.311470841740778° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pseudotsuga", + "(C) Alnus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0296", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_270227_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.00427974194862° N, and the longitude is 8.446276465878888° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Tilia", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0297", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_56442_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.93674968321892° N, and the longitude is 7.875270574568005° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pinus", + "(C) Tilia", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0298", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82565_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.97431529114347° N, and the longitude is 10.200029995734045° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Abies", + "(C) Tilia", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0299", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22403_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.331920653213466° N, and the longitude is 10.724356103322288° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Quercus", + "(C) Pseudotsuga", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0300", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_12240_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.5783202330541° N, and the longitude is 10.040484207290033° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Prunus", + "(C) Pseudotsuga", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0301", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_9_502_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.48786968877855° N, and the longitude is 7.520374081419455° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Cleared", + "(C) Fraxinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0302", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_84861_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.08744507124957° N, and the longitude is 8.15827033696703° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Tilia", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0303", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_27367_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.189042401152186° N, and the longitude is 10.585326906575979° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Betula", + "(C) Larix", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0304", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_31840_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.654795094224454° N, and the longitude is 10.05616993464479° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Populus", + "(C) Fraxinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0305", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_2_929_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.39693974904797° N, and the longitude is 9.830244427696844° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Abies", + "(C) Betula", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0306", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78427_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.89268789117311° N, and the longitude is 8.042750960717676° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pseudotsuga", + "(C) Abies", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0307", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20276_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.65120461729262° N, and the longitude is 9.695911365332329° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Pseudotsuga", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0308", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_33923_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.96767936857153° N, and the longitude is 9.429743925916318° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Populus", + "(C) Fraxinus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0309", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_27330_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.96885844312026° N, and the longitude is 9.728742365723702° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Prunus", + "(C) Acer", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0310", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_269309_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.99197583903777° N, and the longitude is 10.316916679852367° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Abies", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0311", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22397_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.64956772598246° N, and the longitude is 10.411938805321684° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Alnus", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0312", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47362_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.637935180581785° N, and the longitude is 9.722707366200158° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Picea", + "(C) Betula", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0313", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48419_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.85734618983276° N, and the longitude is 10.202788436186077° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Larix", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0314", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48447_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87196350946111° N, and the longitude is 10.247657953829677° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Pinus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0315", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_299217_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.158914929151855° N, and the longitude is 7.834318138382499° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Tilia", + "(C) Abies", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0316", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_11_25367_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.625857397695334° N, and the longitude is 9.702936964210215° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Alnus", + "(C) Fagus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0317", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21520_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.83911513354311° N, and the longitude is 10.371511510371954° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Alnus", + "(C) Cleared", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0318", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_2_35931_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.141993417375794° N, and the longitude is 10.683759310109714° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pseudotsuga", + "(C) Larix", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0319", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_26342_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.78768426274184° N, and the longitude is 9.591381685917831° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Picea", + "(C) Fagus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0320", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_150563_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.08867717380087° N, and the longitude is 9.953108787322154° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Populus", + "(C) Alnus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0321", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75741_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.78762482184222° N, and the longitude is 9.519331766458523° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Fagus", + "(C) Betula", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0322", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_25650_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.79482113484869° N, and the longitude is 10.458220317672543° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fagus", + "(C) Fagus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0323", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_310897_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.24286037755754° N, and the longitude is 10.726090073814598° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pinus", + "(C) Acer", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0324", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_285405_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.092051235516124° N, and the longitude is 10.28713101812864° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Pinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0325", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_46878_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.68557601656861° N, and the longitude is 10.628957801248417° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Picea", + "(C) Fraxinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0326", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_31080_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.501685396332384° N, and the longitude is 8.982129400238406° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Pseudotsuga", + "(C) Picea", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0327", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_88560_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.526823374211645° N, and the longitude is 10.107839004311467° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Betula", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0328", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49968_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.82700022106897° N, and the longitude is 9.531256729252323° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Picea", + "(C) Larix", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0329", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34294_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.35247099878693° N, and the longitude is 10.951867147466812° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Fraxinus", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0330", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_8_88376_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.9902076182418° N, and the longitude is 10.211411860785349° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Quercus", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0331", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_7056_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87592415417584° N, and the longitude is 9.36246275549621° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Fraxinus", + "(C) Pinus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0332", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45900_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.682451601219604° N, and the longitude is 9.722717093944677° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Tilia", + "(C) Fraxinus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0333", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_26480_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.49815046054392° N, and the longitude is 7.837783795588068° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Picea", + "(C) Larix", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0334", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38448_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.308579397070766° N, and the longitude is 10.927117724135083° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Quercus", + "(C) Larix", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0335", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27357_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.709959989622895° N, and the longitude is 9.679992108236695° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Pseudotsuga", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0336", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_63298_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.99004856977399° N, and the longitude is 10.229428599167562° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Abies", + "(C) Larix", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0337", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_287354_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.102321567041066° N, and the longitude is 10.333724742147515° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Populus", + "(C) Acer", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0338", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24351_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.146083284148645° N, and the longitude is 8.226854433163021° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Alnus", + "(C) Cleared", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0339", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44151_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.99088236255666° N, and the longitude is 8.224130018658986° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Fraxinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0340", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_264266_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.951819930705504° N, and the longitude is 10.205589032955388° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Acer", + "(C) Tilia", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0341", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_26104_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.203776949652216° N, and the longitude is 10.731256172408996° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Populus", + "(C) Pinus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0342", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_28986_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.21474675348683° N, and the longitude is 9.310266288054233° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fagus", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0343", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_260570_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.93444478694758° N, and the longitude is 8.1794595807806° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Larix", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0344", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_84770_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.680207638685125° N, and the longitude is 9.621802431937475° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Alnus", + "(C) Populus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0345", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_76802_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.39698177010482° N, and the longitude is 9.83316103433304° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Pseudotsuga", + "(C) Pseudotsuga", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0346", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_81854_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.76576101868431° N, and the longitude is 9.455955086474095° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Cleared", + "(C) Acer", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0347", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_89872_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.03668599413547° N, and the longitude is 11.177229072263968° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Cleared", + "(C) Quercus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0348", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48751_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.77250176638916° N, and the longitude is 10.389674439103846° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Fraxinus", + "(C) Picea", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0349", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21611_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.38159678336911° N, and the longitude is 10.774496392863622° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Betula", + "(C) Cleared", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0350", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_11_28446_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.65223700432778° N, and the longitude is 10.40932385725067° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0351", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27826_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.235248208317° N, and the longitude is 10.81700458178663° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fagus", + "(C) Pinus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0352", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_46855_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.20461790021378° N, and the longitude is 9.243762456190629° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Prunus", + "(C) Picea", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0353", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_81241_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.19336223251067° N, and the longitude is 10.566900342308715° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Alnus", + "(C) Prunus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0354", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_305358_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.19033330982011° N, and the longitude is 10.813754971315825° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Betula", + "(C) Alnus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0355", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86003_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.16739472711419° N, and the longitude is 8.090488451329374° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Acer", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0356", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_0_91324_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.626403752770386° N, and the longitude is 9.63270870318624° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fraxinus", + "(C) Tilia", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0357", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_267740_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.984177040435036° N, and the longitude is 10.205001222530612° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Pinus", + "(C) Tilia", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0358", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48525_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.84153931483716° N, and the longitude is 10.34988143988366° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Betula", + "(C) Picea", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0359", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_11_25057_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.01443013454144° N, and the longitude is 9.349821693361108° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Larix", + "(C) Fagus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0360", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62969_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.636681450994125° N, and the longitude is 10.025904782057923° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Abies", + "(C) Fagus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0361", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_62421_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.03185056454901° N, and the longitude is 11.18816348088869° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Populus", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0362", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79429_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.031909497717265° N, and the longitude is 10.432924254146466° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Fraxinus", + "(C) Pseudotsuga", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0363", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_162132_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.1819085207151° N, and the longitude is 9.573510702180162° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pseudotsuga", + "(C) Fraxinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0364", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_8562_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.65459931038545° N, and the longitude is 10.438005014007453° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Larix", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0365", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23428_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.52089769371789° N, and the longitude is 7.581668469598775° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Prunus", + "(C) Acer", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0366", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48052_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.77906553937919° N, and the longitude is 10.306533410278147° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fraxinus", + "(C) Populus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0367", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_82665_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.57780231201792° N, and the longitude is 9.334429102186322° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Quercus", + "(C) Betula", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0368", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_0_7755_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.14725959940593° N, and the longitude is 9.59007212863628° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Acer", + "(C) Fraxinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0369", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22300_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.83862863448188° N, and the longitude is 10.27161289513021° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Picea", + "(C) Picea", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0370", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87655_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.9996933261803° N, and the longitude is 8.459848943648863° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Alnus", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0371", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_93551_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.01640200027846° N, and the longitude is 8.294467439908567° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Quercus", + "(C) Cleared", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0372", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_13748_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.58903160557152° N, and the longitude is 10.316335118067027° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Quercus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0373", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_0_48371_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.700790155188876° N, and the longitude is 9.471481873979835° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Prunus", + "(C) Picea", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0374", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_301625_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.171400494562675° N, and the longitude is 10.564686533953063° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pseudotsuga", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0375", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_36218_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.00103778712137° N, and the longitude is 9.334674551080157° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Fagus", + "(C) Larix", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0376", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_26826_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.874514673113104° N, and the longitude is 9.377186638629095° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Fagus", + "(C) Tilia", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0377", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62600_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.49037156685775° N, and the longitude is 7.355717520919466° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pinus", + "(C) Larix", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0378", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_5_33707_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.365454374601626° N, and the longitude is 10.81563137693407° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Quercus", + "(C) Pinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0379", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_27373_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.38250960416358° N, and the longitude is 9.686338857121735° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Fagus", + "(C) Fagus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0380", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_1_32399_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.8852772029498° N, and the longitude is 9.540458028444963° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Acer", + "(C) Fraxinus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0381", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_78416_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.39576719333699° N, and the longitude is 7.888962292710352° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0382", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_302817_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.18478660113829° N, and the longitude is 9.871039684842708° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Abies", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0383", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_28026_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.256240847002495° N, and the longitude is 11.037245853918408° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Picea", + "(C) Acer", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0384", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_305308_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.201013222397684° N, and the longitude is 9.863886416758607° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Prunus", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0385", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85697_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.362852904897494° N, and the longitude is 10.502654901778131° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Larix", + "(C) Fraxinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0386", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21648_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.15237563415675° N, and the longitude is 9.364905243737535° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Cleared", + "(C) Betula", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0387", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_27449_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.27854563732951° N, and the longitude is 9.492800478744348° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fagus", + "(C) Fraxinus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0388", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_267003_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.97855821033782° N, and the longitude is 10.227177415116616° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Prunus", + "(C) Abies", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0389", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_88081_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.318557338268846° N, and the longitude is 10.71763762499961° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Tilia", + "(C) Pseudotsuga", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0390", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_211871_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.56572317808365° N, and the longitude is 9.314530509719061° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pinus", + "(C) Fagus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0391", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27267_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.24128811673771° N, and the longitude is 9.52572358344713° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Betula", + "(C) Fagus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0392", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_28939_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.63372622999352° N, and the longitude is 9.715537593438768° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Fraxinus", + "(C) Picea", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0393", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_5405_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.80651438863833° N, and the longitude is 10.45481764402053° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Alnus", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0394", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_49329_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.8234498012312° N, and the longitude is 10.448938662371365° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Cleared", + "(C) Fraxinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0395", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_84191_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.50511366225963° N, and the longitude is 9.648091327773784° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Populus", + "(C) Pseudotsuga", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0396", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_85653_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.866903570318364° N, and the longitude is 8.99175270017622° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fagus", + "(C) Quercus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0397", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5723_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.43378779546415° N, and the longitude is 10.080414212650242° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Larix", + "(C) Fagus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0398", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_7_88292_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.117647895666714° N, and the longitude is 10.863781584723675° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Picea", + "(C) Acer", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0399", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_1_322789_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.31550275850219° N, and the longitude is 10.2308247073163° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Fraxinus", + "(C) Cleared", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0400", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_302636_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.18393177342607° N, and the longitude is 9.865038750736645° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Pseudotsuga", + "(C) Pinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0401", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_64472_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.06563571227534° N, and the longitude is 8.239006292991728° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pseudotsuga", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0402", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_5_144434_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.99580483136559° N, and the longitude is 10.427249245953362° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fagus", + "(C) Betula", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0403", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_27859_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.13450921800246° N, and the longitude is 9.60291294350379° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Fraxinus", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0404", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44891_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.40628241843052° N, and the longitude is 7.905546059268219° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Betula", + "(C) Prunus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0405", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27151_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.90685317929044° N, and the longitude is 8.781316514641746° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Betula", + "(C) Alnus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0406", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_27917_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.31962273560345° N, and the longitude is 9.506499240616645° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Acer", + "(C) Abies", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0407", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_45718_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.8439147815587° N, and the longitude is 10.361412395089415° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Pinus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0408", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_9_7786_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.38945300051681° N, and the longitude is 9.39527886275428° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Acer", + "(C) Fraxinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0409", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_92132_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.14438990115158° N, and the longitude is 9.344757131377731° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Acer", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0410", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_26302_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.10951317945324° N, and the longitude is 10.326064832800292° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Populus", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0411", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_25279_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87738112691727° N, and the longitude is 10.27308035907905° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Tilia", + "(C) Acer", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0412", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_7_277199_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.057549914332846° N, and the longitude is 8.503762546369002° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Quercus", + "(C) Tilia", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0413", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_149143_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.07012977074627° N, and the longitude is 9.911878422215151° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Picea", + "(C) Fraxinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0414", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_277284_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.03809590053139° N, and the longitude is 11.206957652534578° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Acer", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0415", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_264460_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.953870705820385° N, and the longitude is 10.180350274507104° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Quercus", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0416", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23838_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.56703533106747° N, and the longitude is 8.137219281777222° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Abies", + "(C) Betula", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0417", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20443_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.17616716148155° N, and the longitude is 9.882917428862793° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Populus", + "(C) Cleared", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0418", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_49483_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.75310477318789° N, and the longitude is 9.564978674621283° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Picea", + "(C) Picea", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0419", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_61449_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.10719387923711° N, and the longitude is 9.363948842707135° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Prunus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0420", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85444_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.15461073386571° N, and the longitude is 11.011239121754231° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Quercus", + "(C) Tilia", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0421", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_286140_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.08845807420629° N, and the longitude is 10.834842753226088° E.", + "Answer Choices": [ + "(A) Acer", + "(B) Pinus", + "(C) Alnus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0422", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24087_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.15431950645135° N, and the longitude is 9.11674395685083° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0423", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_149773_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.07970297890635° N, and the longitude is 9.95145877754291° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Quercus", + "(C) Fagus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0424", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49201_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.771386996852° N, and the longitude is 10.268198433515177° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Alnus", + "(C) Betula", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0425", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_47921_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87549035154108° N, and the longitude is 9.729497023117045° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Pseudotsuga", + "(C) Tilia", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0426", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_60552_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.435899462415094° N, and the longitude is 9.832290422815765° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Pinus", + "(C) Cleared", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0427", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_83276_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.650796079209094° N, and the longitude is 9.124044113348235° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Cleared", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0428", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23155_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.87596709924941° N, and the longitude is 8.209295625046238° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Populus", + "(C) Pseudotsuga", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0429", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_28373_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.205177015978066° N, and the longitude is 9.325943947802605° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Acer", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0430", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_64636_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.031961337919576° N, and the longitude is 11.166401229193692° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pseudotsuga", + "(C) Cleared", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0431", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49949_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.73695667548091° N, and the longitude is 9.629748236703845° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Picea", + "(C) Quercus", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0432", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48650_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.6280125220891° N, and the longitude is 9.770147233400184° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Picea", + "(C) Abies", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0433", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63752_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.73954502758468° N, and the longitude is 9.512799499291° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Fraxinus", + "(C) Pinus", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0434", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_5_94403_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.76507199631237° N, and the longitude is 9.424401866295176° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fraxinus", + "(C) Quercus", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0435", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_41212_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.02882765201145° N, and the longitude is 8.18556677440448° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Prunus", + "(C) Larix", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0436", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_25304_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.355818394294275° N, and the longitude is 10.987033660874093° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Fraxinus", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0437", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_16196_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.613617140277405° N, and the longitude is 10.112034473941513° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Quercus", + "(C) Abies", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0438", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_28212_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.314919789096294° N, and the longitude is 10.46163821508695° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Pinus", + "(C) Fagus", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0439", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_31895_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.94700904972573° N, and the longitude is 9.44069546519134° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Fraxinus", + "(C) Cleared", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0440", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_29542_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.23408674309699° N, and the longitude is 9.5203240339447° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Pseudotsuga", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0441", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_45800_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.37878998918272° N, and the longitude is 9.821616349376617° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Betula", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0442", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_26665_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.8975227707043° N, and the longitude is 10.332379873085396° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Acer", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0443", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20175_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.884334748289405° N, and the longitude is 10.250152648699796° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Fraxinus", + "(C) Cleared", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0444", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_7_88908_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.364260913297116° N, and the longitude is 10.814961159007122° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Populus", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0445", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23002_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.48684533936328° N, and the longitude is 7.8479186695118575° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0446", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_32585_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.63125030064082° N, and the longitude is 10.415627031821094° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Quercus", + "(C) Larix", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0447", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20396_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.96358784858676° N, and the longitude is 10.142454168267784° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Cleared", + "(C) Prunus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0448", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45206_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.387116096307224° N, and the longitude is 9.412417833271022° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Quercus", + "(C) Picea", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0449", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27346_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87629082040253° N, and the longitude is 9.49647910629111° E.", + "Answer Choices": [ + "(A) Prunus", + "(B) Fagus", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0450", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_262493_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.946799015885624° N, and the longitude is 8.707352201952418° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Acer", + "(C) Abies", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0451", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_28984_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.645198878081544° N, and the longitude is 10.48436431494018° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Populus", + "(C) Picea", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0452", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_63833_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.13931903531276° N, and the longitude is 10.922792037590298° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fagus", + "(C) Prunus", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0453", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_63367_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.18781048348135° N, and the longitude is 10.614826239739477° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Prunus", + "(C) Pinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0454", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_208691_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.545424351548434° N, and the longitude is 8.891331805566402° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Alnus", + "(C) Pinus", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0455", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23786_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.08380405910419° N, and the longitude is 9.542617831156091° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Cleared", + "(C) Pinus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0456", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_205375_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.52382783860893° N, and the longitude is 8.863391532426682° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Abies", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0457", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_61199_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.81776513350663° N, and the longitude is 9.240703732580345° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Prunus", + "(C) Pinus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0458", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23307_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.719222398270766° N, and the longitude is 10.44160433859661° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Larix", + "(C) Cleared", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0459", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_46070_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.93986390339934° N, and the longitude is 9.701071112568801° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Fraxinus", + "(C) Picea", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0460", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_84292_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.076555967762566° N, and the longitude is 9.549899977041292° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Pinus", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0461", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_29825_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.26772168885707° N, and the longitude is 10.668005086572538° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Populus", + "(C) Prunus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0462", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_87522_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.97040668941655° N, and the longitude is 9.709565988236848° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fraxinus", + "(C) Quercus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0463", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_9844_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.96413127756714° N, and the longitude is 10.203916744507254° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Abies", + "(C) Quercus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0464", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_92108_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.972568735393516° N, and the longitude is 9.593637062175553° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Quercus", + "(C) Quercus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0465", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_80918_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.69155258359847° N, and the longitude is 9.477715019361575° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Betula", + "(C) Quercus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0466", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_61684_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.45335207436846° N, and the longitude is 10.066176173332774° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Betula", + "(C) Tilia", + "(D) Alnus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0467", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23256_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.31199723549312° N, and the longitude is 9.76016283253899° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Cleared", + "(C) Cleared", + "(D) Prunus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0468", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_88461_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.68648597491384° N, and the longitude is 7.150516282480258° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Alnus", + "(C) Tilia", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0469", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_2_51120_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.45994983170879° N, and the longitude is 7.192251101038997° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Acer", + "(C) Pinus", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0470", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_46361_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.8499752014446° N, and the longitude is 10.416541517847625° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Picea", + "(C) Prunus", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0471", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_76669_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.27425045581816° N, and the longitude is 9.136607781112978° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fagus", + "(C) Acer", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0472", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22591_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92282126739726° N, and the longitude is 8.4734735273413° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Cleared", + "(C) Quercus", + "(D) Pseudotsuga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0473", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78350_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.92547928243764° N, and the longitude is 8.623318161285837° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Pseudotsuga", + "(C) Fraxinus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0474", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_41821_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.53404597272401° N, and the longitude is 7.733798201907176° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fraxinus", + "(C) Tilia", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0475", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_79032_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.09164834412562° N, and the longitude is 10.83947235557687° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pseudotsuga", + "(C) Pseudotsuga", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0476", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_47561_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.87877187935501° N, and the longitude is 10.485865210386226° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fagus", + "(C) Quercus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0477", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_85726_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.5143692450805° N, and the longitude is 7.4152316851338504° E.", + "Answer Choices": [ + "(A) Quercus", + "(B) Acer", + "(C) Fagus", + "(D) Betula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0478", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_41065_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.27329162474171° N, and the longitude is 9.114149764210518° E.", + "Answer Choices": [ + "(A) Cleared", + "(B) Larix", + "(C) Abies", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0479", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75688_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.341128436683306° N, and the longitude is 8.092872225424122° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Quercus", + "(C) Pseudotsuga", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0480", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_63927_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.57656497129544° N, and the longitude is 10.16790694457029° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Alnus", + "(C) Cleared", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0481", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5006_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.40448200453935° N, and the longitude is 9.850405281883686° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Populus", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0482", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_153859_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.12703243929524° N, and the longitude is 9.584486923134339° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Prunus", + "(C) Acer", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0483", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79494_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.68708304007614° N, and the longitude is 10.313748556282714° E.", + "Answer Choices": [ + "(A) Populus", + "(B) Prunus", + "(C) Pseudotsuga", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0484", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_28687_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.6599330864801° N, and the longitude is 10.404955185891977° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Fraxinus", + "(C) Fagus", + "(D) Abies", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0485", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_26323_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.618829635520946° N, and the longitude is 10.610591674186763° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Populus", + "(C) Picea", + "(D) Cleared", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0486", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_289136_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.10447555403698° N, and the longitude is 10.78624584910497° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Pinus", + "(C) Pinus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0487", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_0_37088_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.514598733073626° N, and the longitude is 9.645997941637013° E.", + "Answer Choices": [ + "(A) Betula", + "(B) Fraxinus", + "(C) Larix", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0488", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_0_78184_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.876398523094984° N, and the longitude is 10.523628879236973° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Populus", + "(C) Acer", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0489", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_25132_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.72725389823446° N, and the longitude is 9.740775964708298° E.", + "Answer Choices": [ + "(A) Larix", + "(B) Fagus", + "(C) Alnus", + "(D) Picea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0490", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78346_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.89570269296198° N, and the longitude is 7.945626305617428° E.", + "Answer Choices": [ + "(A) Pseudotsuga", + "(B) Cleared", + "(C) Pinus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0491", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63663_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.25051544527442° N, and the longitude is 11.047162649392055° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Prunus", + "(C) Abies", + "(D) Tilia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0492", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_86134_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.46529105882626° N, and the longitude is 9.869682951473838° E.", + "Answer Choices": [ + "(A) Fraxinus", + "(B) Pseudotsuga", + "(C) Quercus", + "(D) Acer", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0493", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_157267_BI_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.153282998869784° N, and the longitude is 9.545381795367692° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Alnus", + "(C) Fagus", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0494", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_1_62844_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.65012940897781° N, and the longitude is 8.508592013197871° E.", + "Answer Choices": [ + "(A) Pinus", + "(B) Pinus", + "(C) Abies", + "(D) Populus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0495", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_45187_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.82962312073296° N, and the longitude is 9.585018720882175° E.", + "Answer Choices": [ + "(A) Alnus", + "(B) Quercus", + "(C) Picea", + "(D) Fraxinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0496", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_29910_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 52.49952221293466° N, and the longitude is 7.450471171508248° E.", + "Answer Choices": [ + "(A) Picea", + "(B) Fagus", + "(C) Pseudotsuga", + "(D) Pinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0497", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47505_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.63283467657181° N, and the longitude is 10.540575968936492° E.", + "Answer Choices": [ + "(A) Abies", + "(B) Picea", + "(C) Picea", + "(D) Larix", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0498", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_27410_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 51.76547498448629° N, and the longitude is 10.408456213585074° E.", + "Answer Choices": [ + "(A) Fagus", + "(B) Abies", + "(C) Quercus", + "(D) Fagus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Prediction/0499", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_82611_WEFL_NLF.tif" + ], + "Text": "Which type of tree occupies the largest proportion in the picture? The latitude is 53.087635373490514° N, and the longitude is 10.853909698814935° E.", + "Answer Choices": [ + "(A) Tilia", + "(B) Fagus", + "(C) Larix", + "(D) Quercus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Proportion_Prediction.json b/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Proportion_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..a50a66a7bedc615e297819cbbef8d5a247803b6f --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Perception/Tree_Species_Proportion_Prediction.json @@ -0,0 +1,10502 @@ +[ + { + "Question_id": "Tree Species Proportion Prediction/0000", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_25262_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.826762234166° N, and the longitude is 9.605097589329871° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 10.0% - 20.0%", + "(C) 40% - 90%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0001", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_61851_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.037135986245644° N, and the longitude is 11.215870045990759° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 90.0% - 100.0%", + "(C) 50% - 60%", + "(D) 20% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0002", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_32676_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 52.373085328040325° N, and the longitude is 9.412392056206222° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 30% - 60%", + "(C) 0% - 90%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0003", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_48819_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.84599001032344° N, and the longitude is 10.345650882723278° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 90.0% - 100.0%", + "(C) 10% - 80%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0004", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82785_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.64716220205865° N, and the longitude is 9.066767397218298° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 80% - 90%", + "(C) 20% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0005", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9188_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.09141799337251° N, and the longitude is 9.531733815360642° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 70%", + "(C) 30% - 60%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0006", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20262_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.30269648834555° N, and the longitude is 7.626119081048176° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 20% - 50%", + "(C) 80% - 100%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0007", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_30501_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.35548743131606° N, and the longitude is 9.575915168132527° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 0% - 90%", + "(C) 30.0% - 40.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0008", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_61943_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.631394888352226° N, and the longitude is 9.347881970918865° E.", + "Answer Choices": [ + "(A) 30% - 50%", + "(B) 90.0% - 100.0%", + "(C) 50% - 70%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0009", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_235622_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.76914743663834° N, and the longitude is 8.856109503502209° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 40%", + "(C) 60% - 90%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0010", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_64753_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.61196360712106° N, and the longitude is 9.77643514456313° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 0% - 80%", + "(C) 90% - 100%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0011", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_11_26263_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.26446894454474° N, and the longitude is 9.523362153845214° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 30% - 50%", + "(C) 30% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0012", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_315917_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.27679036588925° N, and the longitude is 9.821939789238428° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 80.0% - 90.0%", + "(C) 40% - 50%", + "(D) 70% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0013", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_60737_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.27803166923233° N, and the longitude is 9.828055732041078° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 40% - 80%", + "(C) 90.0% - 100.0%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0014", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_4_2975_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.47200919225321° N, and the longitude is 7.541840238168063° E.", + "Answer Choices": [ + "(A) 20% - 60%", + "(B) 40% - 60%", + "(C) 0% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0015", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86840_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.39579732516471° N, and the longitude is 10.788125536693126° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 10.0% - 20.0%", + "(C) 0% - 30%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0016", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_85341_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.94108763916575° N, and the longitude is 7.964686187687586° E.", + "Answer Choices": [ + "(A) 30% - 100%", + "(B) 80.0% - 90.0%", + "(C) 10% - 80%", + "(D) 0% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0017", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_29457_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.878440465336205° N, and the longitude is 9.706485528127878° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 10% - 60%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0018", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_26245_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.963290174089394° N, and the longitude is 9.629019814602517° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 0% - 80%", + "(C) 90.0% - 100.0%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0019", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_28632_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.90705175526105° N, and the longitude is 9.753409529181694° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 70% - 100%", + "(C) 60.0% - 70.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0020", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_31841_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 51.84537602866559° N, and the longitude is 9.534032327545845° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 90% - 100%", + "(C) 60% - 90%", + "(D) 20% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0021", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_32557_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.25348944819377° N, and the longitude is 11.042428720995579° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 20% - 50%", + "(C) 90.0% - 100.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0022", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_9_90587_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.10009993413149° N, and the longitude is 10.854583175594847° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 20% - 30%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0023", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_83873_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.50906094202785° N, and the longitude is 9.01486801363327° E.", + "Answer Choices": [ + "(A) 20.0% - 30.0%", + "(B) 70% - 90%", + "(C) 0% - 100%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0024", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9320_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.09138657829495° N, and the longitude is 10.34881281131578° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 40% - 60%", + "(C) 40% - 50%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0025", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_25643_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.69399619796209° N, and the longitude is 9.645959620834917° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 60% - 70%", + "(C) 30% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0026", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38565_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.214678559208714° N, and the longitude is 9.144174029216105° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 90.0% - 100.0%", + "(C) 0% - 10%", + "(D) 30% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0027", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78197_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.159363641139805° N, and the longitude is 10.581063755849812° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 40% - 70%", + "(C) 10.0% - 20.0%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0028", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_234336_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.75282292881532° N, and the longitude is 8.480568842822338° E.", + "Answer Choices": [ + "(A) 0% - 40%", + "(B) 30% - 60%", + "(C) 70% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0029", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6127_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Betula? The latitude is 52.16667710659181° N, and the longitude is 8.0985200866915° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 70% - 80%", + "(C) 80% - 100%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0030", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_63722_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.44756491896035° N, and the longitude is 10.694767913523664° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 40% - 70%", + "(C) 40% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0031", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_25856_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.87286255138768° N, and the longitude is 9.702069116466532° E.", + "Answer Choices": [ + "(A) 40.0% - 50.0%", + "(B) 50% - 100%", + "(C) 70% - 80%", + "(D) 60% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0032", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_86775_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.41866090730419° N, and the longitude is 10.900057686970833° E.", + "Answer Choices": [ + "(A) 20% - 40%", + "(B) 0% - 90%", + "(C) 70% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0033", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22294_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 53.19766805437717° N, and the longitude is 9.883862016674575° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 90.0% - 100.0%", + "(C) 10% - 50%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0034", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_56613_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.12697062049221° N, and the longitude is 8.119383915901059° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 60% - 90%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0035", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_82813_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.760248953851374° N, and the longitude is 9.741879697333978° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 90.0% - 100.0%", + "(C) 70% - 80%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0036", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_213854_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.57770713595041° N, and the longitude is 8.832247053282945° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 40% - 50%", + "(C) 70% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0037", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_86413_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.43163298217955° N, and the longitude is 10.930799304539354° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 30% - 40%", + "(C) 40% - 80%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0038", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_3082_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.638946662681114° N, and the longitude is 8.849283956770229° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 20% - 70%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0039", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_13763_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.58860475306192° N, and the longitude is 10.353839980634255° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 10% - 30%", + "(C) 90.0% - 100.0%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0040", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_2_39392_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 52.295540450256574° N, and the longitude is 8.347208544091798° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 30% - 80%", + "(C) 10.0% - 20.0%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0041", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45910_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.68195236035524° N, and the longitude is 10.441804243986187° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 10% - 50%", + "(D) 10% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0042", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_325258_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.34356846209586° N, and the longitude is 8.092053404822513° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 40% - 80%", + "(C) 90.0% - 100.0%", + "(D) 10% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0043", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_31340_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.829394831870566° N, and the longitude is 10.20225119608294° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 50%", + "(C) 20% - 90%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0044", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_5_53969_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.84619099332191° N, and the longitude is 8.58324610881814° E.", + "Answer Choices": [ + "(A) 20% - 60%", + "(B) 90.0% - 100.0%", + "(C) 0% - 60%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0045", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_77162_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.96096814804406° N, and the longitude is 8.370446816923312° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 80% - 90%", + "(C) 90.0% - 100.0%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0046", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_209351_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.54991348675979° N, and the longitude is 8.886898173802829° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 40% - 80%", + "(C) 20.0% - 30.0%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0047", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27304_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.71023267488065° N, and the longitude is 9.719947876496352° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 40% - 50%", + "(C) 0% - 40%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0048", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_5368_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.234328307519135° N, and the longitude is 9.510937618289201° E.", + "Answer Choices": [ + "(A) 60% - 100%", + "(B) 80% - 100%", + "(C) 10.0% - 20.0%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0049", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86331_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.08599746673588° N, and the longitude is 10.273545390518064° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 10% - 40%", + "(C) 80.0% - 90.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0050", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_76287_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.911596570399254° N, and the longitude is 9.698802148944466° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 80.0% - 90.0%", + "(C) 20% - 80%", + "(D) 10% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0051", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_48975_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.96580641776387° N, and the longitude is 10.24043120082337° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 80.0% - 90.0%", + "(C) 10% - 50%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0052", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_28565_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.12558191889129° N, and the longitude is 9.839239773180495° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 30% - 50%", + "(C) 10% - 20%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0053", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_41143_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.45008811755363° N, and the longitude is 10.713112947648018° E.", + "Answer Choices": [ + "(A) 0% - 80%", + "(B) 80.0% - 90.0%", + "(C) 90% - 100%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0054", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_25875_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.61821644649117° N, and the longitude is 10.588925487088703° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 70%", + "(C) 20% - 40%", + "(D) 10% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0055", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45440_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.76983390951489° N, and the longitude is 10.294297487190878° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 90%", + "(C) 50% - 60%", + "(D) 30% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0056", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_90803_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.99369114020843° N, and the longitude is 9.332386105105106° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 80% - 90%", + "(C) 50.0% - 60.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0057", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_26957_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.16397153422656° N, and the longitude is 9.556411912838813° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 40% - 60%", + "(C) 10.0% - 20.0%", + "(D) 20% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0058", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48372_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.714173826348556° N, and the longitude is 10.5970807714912° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 0% - 30%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0059", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_36967_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.36578577238719° N, and the longitude is 8.133134891577003° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90% - 100%", + "(C) 60% - 100%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0060", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_28490_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.65849297267543° N, and the longitude is 9.48810931662032° E.", + "Answer Choices": [ + "(A) 10% - 20%", + "(B) 20.0% - 30.0%", + "(C) 90% - 100%", + "(D) 10% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0061", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_27822_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.22448766263148° N, and the longitude is 9.515293335921596° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 90.0% - 100.0%", + "(C) 0% - 40%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0062", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_27602_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.70852355158138° N, and the longitude is 9.480182245917808° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 80.0% - 90.0%", + "(C) 10% - 50%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0063", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_84636_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.42583857039646° N, and the longitude is 10.138729256441682° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 80.0% - 90.0%", + "(C) 90% - 100%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0064", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_26561_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.86777489816584° N, and the longitude is 10.570592072970985° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 90.0% - 100.0%", + "(C) 10% - 30%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0065", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79329_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.93773730679863° N, and the longitude is 7.912165429062659° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 20% - 90%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0066", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_56887_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.26314834745692° N, and the longitude is 9.55637451973128° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 10% - 100%", + "(C) 30% - 50%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0067", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85310_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.52124064890042° N, and the longitude is 7.488887650927938° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 50.0% - 60.0%", + "(C) 30% - 100%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0068", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_64906_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.338031132980305° N, and the longitude is 10.715975872592983° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 0% - 40%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0069", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78522_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.12673783714458° N, and the longitude is 8.103830467001687° E.", + "Answer Choices": [ + "(A) 10% - 70%", + "(B) 60% - 80%", + "(C) 40% - 60%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0070", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20594_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.67532304431254° N, and the longitude is 9.747061481134724° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 70%", + "(C) 0% - 40%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0071", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_84362_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.27326058634241° N, and the longitude is 9.500008775168064° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 40% - 90%", + "(C) 60% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0072", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_39227_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.426039077209886° N, and the longitude is 10.104454318714858° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 10% - 50%", + "(C) 40% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0073", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_216335_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.59841368462918° N, and the longitude is 8.51781511970885° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 90.0% - 100.0%", + "(C) 50% - 70%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0074", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_36143_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.633959848640465° N, and the longitude is 9.708260356925038° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 20% - 40%", + "(C) 10% - 70%", + "(D) 40% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0075", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_10_48711_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.64199511232374° N, and the longitude is 10.579189017979234° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 30% - 90%", + "(D) 10% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0076", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_92085_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.977445061324644° N, and the longitude is 10.465142682187867° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 50%", + "(C) 0% - 50%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0077", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_30385_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.14169919424169° N, and the longitude is 9.906112567685378° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 10%", + "(C) 0% - 90%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0078", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_26365_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.872200390964906° N, and the longitude is 9.749001813710946° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 50% - 70%", + "(C) 90.0% - 100.0%", + "(D) 30% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0079", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_29750_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.63308170267307° N, and the longitude is 10.556018689934074° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 90%", + "(C) 70% - 90%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0080", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21360_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.558766868596955° N, and the longitude is 7.740358174704612° E.", + "Answer Choices": [ + "(A) 10% - 90%", + "(B) 60.0% - 70.0%", + "(C) 50% - 60%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0081", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_25922_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 51.59265711098861° N, and the longitude is 10.578187917866575° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 10.0% - 20.0%", + "(C) 40% - 60%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0082", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_31384_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.120993561488525° N, and the longitude is 9.914129176313441° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 70%", + "(C) 20% - 80%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0083", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_28511_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.76471130988976° N, and the longitude is 9.56744640606508° E.", + "Answer Choices": [ + "(A) 0% - 10%", + "(B) 0% - 40%", + "(C) 90.0% - 100.0%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0084", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_27696_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.84916897078735° N, and the longitude is 9.938866376721657° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 40% - 50%", + "(C) 80% - 100%", + "(D) 60.0% - 70.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0085", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_45072_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.8240760300889° N, and the longitude is 10.47521308936255° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 50% - 90%", + "(C) 60% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0086", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_75755_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.13341880291927° N, and the longitude is 10.6880766915798° E.", + "Answer Choices": [ + "(A) 0% - 100%", + "(B) 20.0% - 30.0%", + "(C) 40% - 70%", + "(D) 40% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0087", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79893_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.91432994822462° N, and the longitude is 7.882130525178276° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 50%", + "(C) 70% - 80%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0088", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82220_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.686606561861915° N, and the longitude is 9.6142283276641° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 90.0% - 100.0%", + "(C) 60% - 70%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0089", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_25524_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.68095424174022° N, and the longitude is 9.4860054122512° E.", + "Answer Choices": [ + "(A) 20% - 60%", + "(B) 70% - 100%", + "(C) 20% - 70%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0090", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23759_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.69019315373295° N, and the longitude is 9.514830722688156° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 90% - 100%", + "(C) 30% - 100%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0091", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20041_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.111449440797486° N, and the longitude is 9.627263278526272° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 60.0% - 70.0%", + "(C) 40% - 90%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0092", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_75693_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.51577083167818° N, and the longitude is 9.217570548048366° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 30% - 40%", + "(C) 30% - 60%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0093", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_85037_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.38641749637553° N, and the longitude is 9.371502658511695° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 50%", + "(C) 70% - 80%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0094", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9535_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.57766230352456° N, and the longitude is 10.058566329940522° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 80% - 90%", + "(C) 70.0% - 80.0%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0095", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_139698_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.964688019389996° N, and the longitude is 10.14980743063918° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 90.0% - 100.0%", + "(C) 70% - 80%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0096", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_80689_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.96100355422828° N, and the longitude is 8.367114808605747° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 60% - 100%", + "(C) 0% - 100%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0097", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_81244_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.213813309619134° N, and the longitude is 9.228144556365853° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 80%", + "(C) 0% - 20%", + "(D) 40% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0098", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_88993_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.95908971980779° N, and the longitude is 7.882816372150204° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 50% - 80%", + "(C) 60% - 70%", + "(D) 40% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0099", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_63512_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.61792721549969° N, and the longitude is 10.025456060821737° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 0% - 80%", + "(D) 10% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0100", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_38608_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.60404543318975° N, and the longitude is 9.840285263509703° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 40% - 50%", + "(C) 40% - 80%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0101", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_46184_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.803503131372885° N, and the longitude is 10.276830046510854° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 70% - 90%", + "(C) 90.0% - 100.0%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0102", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_80637_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.09533616481881° N, and the longitude is 10.570090541623632° E.", + "Answer Choices": [ + "(A) 10% - 20%", + "(B) 40% - 70%", + "(C) 80.0% - 90.0%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0103", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_155044_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.137675494537184° N, and the longitude is 9.612377284665492° E.", + "Answer Choices": [ + "(A) 10% - 30%", + "(B) 30% - 80%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0104", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_46157_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.837043252939004° N, and the longitude is 10.487209071827879° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 50%", + "(C) 20% - 40%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0105", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_11637_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.57067244825999° N, and the longitude is 10.090792403954428° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 20% - 80%", + "(C) 20% - 40%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0106", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_32821_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.15690817354552° N, and the longitude is 8.084775161833267° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 60% - 80%", + "(C) 20.0% - 30.0%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0107", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_77212_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.950048020025996° N, and the longitude is 7.916599640545345° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 80% - 90%", + "(C) 90.0% - 100.0%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0108", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_47071_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.922904440842444° N, and the longitude is 10.317274664659395° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 60% - 100%", + "(C) 10.0% - 20.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0109", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_8579_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.74396780715622° N, and the longitude is 10.314518965825751° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 90.0% - 100.0%", + "(C) 30% - 40%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0110", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_83539_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.811391421412225° N, and the longitude is 9.054281642943739° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 60% - 70%", + "(C) 30% - 50%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0111", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24673_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.965461278194006° N, and the longitude is 10.144631614960554° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 60% - 80%", + "(C) 30.0% - 40.0%", + "(D) 80% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0112", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78753_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.930495932756735° N, and the longitude is 7.862369711045809° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 50% - 100%", + "(C) 10.0% - 20.0%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0113", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_63355_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.56243386133503° N, and the longitude is 9.318318083106337° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 40% - 50%", + "(C) 90.0% - 100.0%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0114", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49868_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.4999738418849° N, and the longitude is 7.461031607678836° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 70% - 100%", + "(C) 90% - 100%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0115", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_82091_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.78497579209411° N, and the longitude is 8.31440197224202° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 50% - 100%", + "(C) 80.0% - 90.0%", + "(D) 10% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0116", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_77090_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.26634845688829° N, and the longitude is 9.49138961370167° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 80% - 90%", + "(C) 40% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0117", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34206_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.99120342293835° N, and the longitude is 10.412549518853256° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 50%", + "(C) 70% - 90%", + "(D) 20% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0118", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_27867_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.63838203314631° N, and the longitude is 9.739204215052217° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 20% - 70%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0119", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_26795_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.88989643473594° N, and the longitude is 10.217036427649948° E.", + "Answer Choices": [ + "(A) 20% - 90%", + "(B) 60% - 70%", + "(C) 30.0% - 40.0%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0120", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44882_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.029058364077436° N, and the longitude is 8.30366263122463° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 50% - 60%", + "(C) 30% - 60%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0121", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_325311_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.343331373251935° N, and the longitude is 9.93733206993727° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 20% - 40%", + "(C) 30% - 80%", + "(D) 40% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0122", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_25208_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.84061060929416° N, and the longitude is 10.202761764402222° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 90.0% - 100.0%", + "(C) 10% - 70%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0123", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9874_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.25729616479471° N, and the longitude is 9.519359073165651° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 20% - 100%", + "(C) 80.0% - 90.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0124", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_64490_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.84615592418683° N, and the longitude is 9.602803671642564° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 40% - 50%", + "(C) 90.0% - 100.0%", + "(D) 10% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0125", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_7_33204_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.6621588897753° N, and the longitude is 9.253156000816302° E.", + "Answer Choices": [ + "(A) 10% - 60%", + "(B) 50% - 70%", + "(C) 80.0% - 90.0%", + "(D) 0% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0126", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_6_53032_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.136671642012836° N, and the longitude is 10.667012109021448° E.", + "Answer Choices": [ + "(A) 20% - 100%", + "(B) 60% - 70%", + "(C) 70.0% - 80.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0127", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_152234_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.119344811662664° N, and the longitude is 9.188735943963833° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 60%", + "(C) 0% - 30%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0128", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86746_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.099582780381525° N, and the longitude is 10.349253425791513° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 50% - 90%", + "(C) 10.0% - 20.0%", + "(D) 0% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0129", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_46361_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.8499752014446° N, and the longitude is 10.416541517847625° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 20%", + "(C) 40% - 50%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0130", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_5790_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.72368285576717° N, and the longitude is 10.619572323931907° E.", + "Answer Choices": [ + "(A) 0% - 40%", + "(B) 0% - 60%", + "(C) 0% - 100%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0131", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_61906_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.17567375365386° N, and the longitude is 10.888605863277014° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 90%", + "(C) 10% - 80%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0132", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_32019_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.48586803640398° N, and the longitude is 10.167964494943774° E.", + "Answer Choices": [ + "(A) 10% - 90%", + "(B) 70% - 90%", + "(C) 10% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0133", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_152394_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.118871075500884° N, and the longitude is 9.59897963646061° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 60%", + "(C) 0% - 70%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0134", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_29357_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.513408661991804° N, and the longitude is 9.610216031732614° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 70% - 80%", + "(C) 70% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0135", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_148010_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.04889359923118° N, and the longitude is 10.345848653932249° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 70.0% - 80.0%", + "(C) 60% - 70%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0136", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85303_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.17267371391779° N, and the longitude is 10.585785283745981° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 60%", + "(C) 80% - 90%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0137", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_91602_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.93515725535744° N, and the longitude is 8.15965285106976° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 10.0% - 20.0%", + "(C) 90% - 100%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0138", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_31071_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.6317050417674° N, and the longitude is 9.838554243533247° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 80%", + "(C) 40% - 50%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0139", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_32913_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.66976169712932° N, and the longitude is 10.249289297053537° E.", + "Answer Choices": [ + "(A) 50.0% - 60.0%", + "(B) 0% - 40%", + "(C) 90% - 100%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0140", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_46043_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.8179289807282° N, and the longitude is 10.410072156171141° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 60% - 70%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0141", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_170950_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.2549641331613° N, and the longitude is 9.517341149713694° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 20% - 70%", + "(C) 90.0% - 100.0%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0142", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23238_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 53.29817074422362° N, and the longitude is 10.252460328324897° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 0% - 80%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0143", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_26000_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.71273808249227° N, and the longitude is 10.308501323557069° E.", + "Answer Choices": [ + "(A) 20% - 90%", + "(B) 0% - 50%", + "(C) 90.0% - 100.0%", + "(D) 30% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0144", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_27057_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.263555924408536° N, and the longitude is 9.522582300014513° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 30% - 50%", + "(C) 90.0% - 100.0%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0145", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_44801_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.719419394004746° N, and the longitude is 10.323697912985315° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 90.0% - 100.0%", + "(C) 0% - 60%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0146", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_44265_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.30025480116204° N, and the longitude is 7.616790861764723° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 90.0% - 100.0%", + "(C) 40% - 90%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0147", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_5082_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.44675345519864° N, and the longitude is 10.17126631701665° E.", + "Answer Choices": [ + "(A) 30.0% - 40.0%", + "(B) 40% - 100%", + "(C) 50% - 80%", + "(D) 40% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0148", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_29260_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.74143888394342° N, and the longitude is 10.321104909759955° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 20% - 70%", + "(C) 30% - 40%", + "(D) 50.0% - 60.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0149", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49676_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.708416927776106° N, and the longitude is 9.610460102086012° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 40% - 100%", + "(C) 40% - 60%", + "(D) 70% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0150", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_25321_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.015785631910816° N, and the longitude is 9.355812633142216° E.", + "Answer Choices": [ + "(A) 40% - 100%", + "(B) 0% - 70%", + "(C) 70% - 80%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0151", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_25034_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.796111790290084° N, and the longitude is 9.479688586719838° E.", + "Answer Choices": [ + "(A) 10% - 20%", + "(B) 50% - 90%", + "(C) 40% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0152", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_76639_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.91028239970403° N, and the longitude is 7.933677443221465° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 10.0% - 20.0%", + "(C) 90% - 100%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0153", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_262362_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.94004994337091° N, and the longitude is 10.214186748337251° E.", + "Answer Choices": [ + "(A) 40.0% - 50.0%", + "(B) 20% - 100%", + "(C) 20% - 60%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0154", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34294_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.35247099878693° N, and the longitude is 10.951867147466812° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 50% - 90%", + "(C) 90.0% - 100.0%", + "(D) 40% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0155", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_26404_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.85630529882375° N, and the longitude is 8.671168177589081° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 20% - 80%", + "(C) 80.0% - 90.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0156", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_87943_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.32265187653029° N, and the longitude is 10.684155377512717° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 90.0% - 100.0%", + "(C) 70% - 80%", + "(D) 10% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0157", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_27015_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.20665203778557° N, and the longitude is 9.19221181723286° E.", + "Answer Choices": [ + "(A) 20% - 40%", + "(B) 0% - 70%", + "(C) 60% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0158", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22200_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.822870529534796° N, and the longitude is 10.455795708265196° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 90% - 100%", + "(C) 40% - 90%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0159", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_86540_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.25839217814515° N, and the longitude is 11.053282647688121° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 20% - 90%", + "(C) 0% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0160", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_4_525_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.29993570350262° N, and the longitude is 7.611278280350396° E.", + "Answer Choices": [ + "(A) 10% - 60%", + "(B) 40% - 60%", + "(C) 90.0% - 100.0%", + "(D) 0% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0161", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_91062_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.54922246640914° N, and the longitude is 9.452902718189092° E.", + "Answer Choices": [ + "(A) 30% - 40%", + "(B) 0% - 50%", + "(C) 40% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0162", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_2_44819_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.60732049099463° N, and the longitude is 10.224560383426262° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 60% - 90%", + "(C) 70% - 100%", + "(D) 40.0% - 50.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0163", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_25869_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.648509770531575° N, and the longitude is 10.426149584711794° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 90.0% - 100.0%", + "(C) 20% - 50%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0164", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86831_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.775331234644725° N, and the longitude is 9.538696010649973° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 80% - 90%", + "(C) 20% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0165", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_279168_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.059003829711514° N, and the longitude is 10.56955868698037° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 90%", + "(C) 80% - 90%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0166", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_146868_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.02642281342607° N, and the longitude is 10.422396202063823° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 30% - 80%", + "(C) 30% - 100%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0167", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_25779_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.714330352377345° N, and the longitude is 9.649179672836143° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90.0% - 100.0%", + "(C) 0% - 20%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0168", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_4_85798_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.073845689521384° N, and the longitude is 8.492975907920384° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 0% - 40%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0169", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_35283_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.28982210763198° N, and the longitude is 8.314928397163696° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 80% - 100%", + "(C) 40% - 50%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0170", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_30365_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.602190930445246° N, and the longitude is 9.969125538413236° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 40% - 90%", + "(C) 90.0% - 100.0%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0171", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_46464_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.925051082335294° N, and the longitude is 8.739949575565099° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 90.0% - 100.0%", + "(C) 10% - 60%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0172", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_33430_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.18613353224615° N, and the longitude is 9.5915520209538° E.", + "Answer Choices": [ + "(A) 30.0% - 40.0%", + "(B) 40% - 50%", + "(C) 90% - 100%", + "(D) 50% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0173", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_25061_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.58228836773416° N, and the longitude is 10.584818735323507° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 90% - 100%", + "(C) 70.0% - 80.0%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0174", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20617_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.671802679968444° N, and the longitude is 9.824278222044045° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 30% - 40%", + "(C) 90.0% - 100.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0175", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_46375_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.77137542164817° N, and the longitude is 9.610848135306156° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 30% - 40%", + "(C) 10% - 60%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0176", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_4_80921_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.54403027916583° N, and the longitude is 9.560859649573246° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 50% - 80%", + "(C) 90.0% - 100.0%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0177", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_92116_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.15707624827297° N, and the longitude is 9.577635278661294° E.", + "Answer Choices": [ + "(A) 40% - 60%", + "(B) 10% - 40%", + "(C) 90.0% - 100.0%", + "(D) 10% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0178", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34796_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.51231839712934° N, and the longitude is 10.320750785758861° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 50% - 100%", + "(C) 70.0% - 80.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0179", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_26024_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.84389285712171° N, and the longitude is 10.05135533449856° E.", + "Answer Choices": [ + "(A) 50% - 60%", + "(B) 80.0% - 90.0%", + "(C) 50% - 70%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0180", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_91156_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.02719133814627° N, and the longitude is 9.279045143626952° E.", + "Answer Choices": [ + "(A) 0% - 10%", + "(B) 40.0% - 50.0%", + "(C) 50% - 70%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0181", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_294074_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.139040849943° N, and the longitude is 9.976211892406717° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 30% - 40%", + "(C) 60% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0182", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_1_90339_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.90634735142518° N, and the longitude is 7.888803221475983° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 70.0% - 80.0%", + "(C) 10% - 70%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0183", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_27190_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.72420532100289° N, and the longitude is 9.624418604824493° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 40% - 100%", + "(C) 90% - 100%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0184", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22684_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.82597802414293° N, and the longitude is 10.369975952743536° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 10.0% - 20.0%", + "(C) 20% - 50%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0185", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_290021_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.10796197664154° N, and the longitude is 10.852101071966741° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 90.0% - 100.0%", + "(C) 0% - 90%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0186", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_81592_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.91465789827447° N, and the longitude is 8.138819448214496° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 20% - 50%", + "(C) 60% - 100%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0187", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23597_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.73025711918876° N, and the longitude is 9.775470329571798° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 30% - 80%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0188", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_258245_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.924970863224566° N, and the longitude is 8.61531020514659° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 20% - 70%", + "(D) 40% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0189", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_7_46722_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.71363245676821° N, and the longitude is 10.306953207590093° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 90.0% - 100.0%", + "(C) 30% - 90%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0190", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_62633_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.6138306175078° N, and the longitude is 10.006917853908893° E.", + "Answer Choices": [ + "(A) 50% - 70%", + "(B) 10% - 60%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0191", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87316_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.49349069807784° N, and the longitude is 9.656494477748456° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 70% - 90%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0192", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_47593_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.77650801527171° N, and the longitude is 9.610274626778915° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 90%", + "(C) 10% - 70%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0193", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_47380_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.515195239066855° N, and the longitude is 9.619673691874475° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 40% - 90%", + "(C) 30% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0194", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_5100_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.31498020994164° N, and the longitude is 9.693267920849449° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 90% - 100%", + "(C) 10% - 80%", + "(D) 60.0% - 70.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0195", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_7723_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.96331148888236° N, and the longitude is 9.43743992432467° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 30% - 70%", + "(C) 90.0% - 100.0%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0196", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_87670_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.021462527695576° N, and the longitude is 9.27680448624305° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 50% - 60%", + "(C) 70% - 80%", + "(D) 50% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0197", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_29320_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.058927957030456° N, and the longitude is 8.454882925059062° E.", + "Answer Choices": [ + "(A) 60.0% - 70.0%", + "(B) 50% - 100%", + "(C) 80% - 100%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0198", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_25990_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.31642771194477° N, and the longitude is 9.745948288112908° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 10% - 20%", + "(C) 20% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0199", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_55661_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.64185821766259° N, and the longitude is 8.874687642956168° E.", + "Answer Choices": [ + "(A) 20% - 90%", + "(B) 0% - 50%", + "(C) 30% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0200", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_7_63046_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.73995673232935° N, and the longitude is 7.983215203882675° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 70% - 90%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0201", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_46301_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.68686823402245° N, and the longitude is 10.605606300797357° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 40%", + "(C) 40% - 60%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0202", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24749_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.702987996800076° N, and the longitude is 10.444525619512648° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 20.0% - 30.0%", + "(C) 50% - 90%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0203", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_92991_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.938040436564904° N, and the longitude is 7.952204666632972° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 90% - 100%", + "(C) 80% - 90%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0204", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_27142_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.65140354132599° N, and the longitude is 10.564914250322701° E.", + "Answer Choices": [ + "(A) 0% - 40%", + "(B) 50% - 90%", + "(C) 70% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0205", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_26314_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.77830333634528° N, and the longitude is 9.61256356902201° E.", + "Answer Choices": [ + "(A) 20.0% - 30.0%", + "(B) 40% - 70%", + "(C) 50% - 80%", + "(D) 0% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0206", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_77774_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.89827395069004° N, and the longitude is 8.6113716549915° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 50%", + "(C) 20% - 80%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0207", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_34542_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.946305248238275° N, and the longitude is 9.749303392942° E.", + "Answer Choices": [ + "(A) 40% - 100%", + "(B) 80.0% - 90.0%", + "(C) 20% - 40%", + "(D) 60% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0208", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_8165_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.7685712001517° N, and the longitude is 9.470417526299084° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 20% - 50%", + "(C) 50.0% - 60.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0209", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_47597_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.828815023868216° N, and the longitude is 9.571766560994297° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 90%", + "(C) 10% - 80%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0210", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_296789_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.139970957293215° N, and the longitude is 10.816115052481932° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 90%", + "(C) 40% - 60%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0211", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_2_59536_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.25602723870682° N, and the longitude is 9.561117818633129° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0212", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_328032_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.380027445068826° N, and the longitude is 9.835950185628224° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 80%", + "(C) 10% - 80%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0213", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_8373_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.32004440080262° N, and the longitude is 9.394672824641724° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 70% - 80%", + "(C) 10% - 70%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0214", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_3_31657_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.88040322366139° N, and the longitude is 9.736455536648537° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 50% - 60%", + "(C) 90.0% - 100.0%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0215", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_8359_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.602044581464455° N, and the longitude is 9.833158177860138° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 90%", + "(C) 60% - 70%", + "(D) 0% - 10%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0216", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_1_85190_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.7948266212148° N, and the longitude is 9.547667744478897° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 20% - 70%", + "(C) 50% - 100%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0217", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_166217_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.209864086659756° N, and the longitude is 9.307617438430825° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 40% - 90%", + "(C) 90.0% - 100.0%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0218", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_0_37806_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.49991241844301° N, and the longitude is 9.668467998060175° E.", + "Answer Choices": [ + "(A) 0% - 10%", + "(B) 30% - 70%", + "(C) 80.0% - 90.0%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0219", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_86039_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.268659381929616° N, and the longitude is 11.040279888719887° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 70%", + "(C) 40% - 60%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0220", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79766_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.16983284496954° N, and the longitude is 10.944987999280002° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 90.0% - 100.0%", + "(C) 30% - 90%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0221", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48462_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.14344841087923° N, and the longitude is 8.238732773618297° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 80%", + "(C) 0% - 90%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0222", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60734_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.9387612963054° N, and the longitude is 11.425228577953531° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 80% - 90%", + "(C) 90.0% - 100.0%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0223", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_31049_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.13747139732063° N, and the longitude is 9.902884874066613° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 0% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0224", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_333192_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.42369027039324° N, and the longitude is 7.803021662585088° E.", + "Answer Choices": [ + "(A) 50% - 70%", + "(B) 40% - 60%", + "(C) 30.0% - 40.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0225", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_9_1793_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.1376844835362° N, and the longitude is 10.824764746675855° E.", + "Answer Choices": [ + "(A) 10% - 30%", + "(B) 90.0% - 100.0%", + "(C) 10% - 80%", + "(D) 20% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0226", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_26498_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.108079146653786° N, and the longitude is 9.380580445395704° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 0% - 50%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0227", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20189_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 53.39746325009043° N, and the longitude is 9.168194120228547° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 70% - 100%", + "(C) 30% - 50%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0228", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_93605_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.91195805468957° N, and the longitude is 7.902251344993832° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 70% - 90%", + "(C) 40% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0229", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75716_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.12861958096964° N, and the longitude is 10.8777368744095° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 10.0% - 20.0%", + "(C) 20% - 70%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0230", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5670_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.231583000014574° N, and the longitude is 9.518539860276745° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 80% - 90%", + "(C) 20% - 40%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0231", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60535_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.750351313914095° N, and the longitude is 9.253289373159195° E.", + "Answer Choices": [ + "(A) 0% - 10%", + "(B) 90.0% - 100.0%", + "(C) 40% - 90%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0232", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_5945_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.88411364122926° N, and the longitude is 9.477770260242654° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 90.0% - 100.0%", + "(C) 0% - 60%", + "(D) 10% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0233", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_230679_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.713518430163305° N, and the longitude is 9.0137330833582° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 40% - 80%", + "(C) 0% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0234", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_15698_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.6121407603085° N, and the longitude is 9.974848656547637° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 90.0% - 100.0%", + "(C) 20% - 60%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0235", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_0_75583_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.778239243875156° N, and the longitude is 10.27497876395751° E.", + "Answer Choices": [ + "(A) 40% - 60%", + "(B) 30% - 70%", + "(C) 10.0% - 20.0%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0236", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_149508_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.07612034980119° N, and the longitude is 9.949923959195846° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 50% - 60%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0237", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_2_42906_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.29819492080306° N, and the longitude is 7.62303317283502° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 40% - 70%", + "(C) 70.0% - 80.0%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0238", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_49402_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.82787511128302° N, and the longitude is 10.49478733699738° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 40% - 80%", + "(C) 0% - 60%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0239", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_6924_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.1491212958416° N, and the longitude is 9.135820880882585° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 60% - 90%", + "(C) 30% - 60%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0240", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48199_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.8589346665466° N, and the longitude is 8.63187378272194° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 10.0% - 20.0%", + "(C) 30% - 50%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0241", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_29583_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.243380811532845° N, and the longitude is 9.5017989017551° E.", + "Answer Choices": [ + "(A) 50% - 70%", + "(B) 90.0% - 100.0%", + "(C) 10% - 80%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0242", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_33072_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.19208965525048° N, and the longitude is 9.549035238225605° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 50%", + "(C) 0% - 90%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0243", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_29429_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.371697647250265° N, and the longitude is 9.703176866634136° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 80%", + "(C) 30% - 60%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0244", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_282500_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.080439196751826° N, and the longitude is 10.194258146660856° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 60% - 80%", + "(C) 90.0% - 100.0%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0245", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_305397_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.19713469781069° N, and the longitude is 10.372581996477427° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 90.0% - 100.0%", + "(C) 40% - 50%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0246", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_79303_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.238405675687034° N, and the longitude is 10.816228505354326° E.", + "Answer Choices": [ + "(A) 20% - 100%", + "(B) 10.0% - 20.0%", + "(C) 30% - 70%", + "(D) 80% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0247", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_28394_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.61922042277774° N, and the longitude is 9.76382335284054° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 90% - 100%", + "(C) 80.0% - 90.0%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0248", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_5_54060_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.84893785263581° N, and the longitude is 8.584078231338161° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 40%", + "(C) 50% - 60%", + "(D) 0% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0249", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_39667_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.86783691671232° N, and the longitude is 9.727631547616832° E.", + "Answer Choices": [ + "(A) 0% - 40%", + "(B) 60% - 80%", + "(C) 60% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0250", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87183_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.082800405740265° N, and the longitude is 8.154933569696126° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 0% - 80%", + "(C) 60% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0251", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_5_154352_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.13054631884633° N, and the longitude is 9.600596701717066° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 10% - 70%", + "(C) 90.0% - 100.0%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0252", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_39436_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.118017204689416° N, and the longitude is 10.78245495975683° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 80% - 90%", + "(C) 0% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0253", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_76325_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.005704718589335° N, and the longitude is 9.653065354273167° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 70% - 80%", + "(C) 60% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0254", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85562_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.435175149242724° N, and the longitude is 9.207126340010909° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 80% - 90%", + "(C) 40% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0255", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_5_53757_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.845196750182424° N, and the longitude is 8.583920180412218° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 10% - 80%", + "(C) 90.0% - 100.0%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0256", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_2_33542_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.028553427076965° N, and the longitude is 9.692930342943852° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 60%", + "(C) 60% - 80%", + "(D) 10% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0257", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_85848_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.32098432872476° N, and the longitude is 10.934859991001867° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 40% - 60%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0258", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_5207_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.94279788723844° N, and the longitude is 10.231748040189848° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 80%", + "(C) 30% - 50%", + "(D) 20% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0259", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_76969_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.90776961389545° N, and the longitude is 7.868431883635394° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 70% - 90%", + "(D) 20% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0260", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_64933_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.037459674385566° N, and the longitude is 8.185139427987846° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 60%", + "(C) 10% - 80%", + "(D) 40% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0261", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_231108_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 52.719617802293314° N, and the longitude is 8.94565888337126° E.", + "Answer Choices": [ + "(A) 60.0% - 70.0%", + "(B) 0% - 30%", + "(C) 0% - 60%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0262", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_14074_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.59567196815854° N, and the longitude is 10.009131471569443° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 40% - 60%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0263", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44692_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.04228758081317° N, and the longitude is 9.415689766621878° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 90% - 100%", + "(C) 60% - 100%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0264", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_7024_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.76121548590327° N, and the longitude is 10.39869559345877° E.", + "Answer Choices": [ + "(A) 30% - 40%", + "(B) 80% - 90%", + "(C) 0% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0265", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_64219_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 53.22311468970769° N, and the longitude is 8.113758735693091° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 20.0% - 30.0%", + "(C) 40% - 90%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0266", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_0_36915_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.37627651944521° N, and the longitude is 9.670503418837132° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 30% - 60%", + "(C) 20% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0267", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_37182_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.48786123085746° N, and the longitude is 9.209088698384035° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 0% - 60%", + "(C) 90.0% - 100.0%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0268", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_90809_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.30336424536311° N, and the longitude is 10.227186278236498° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 70% - 90%", + "(C) 60% - 100%", + "(D) 80% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0269", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_47213_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.79168621883827° N, and the longitude is 9.535265725467045° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 30% - 100%", + "(C) 10.0% - 20.0%", + "(D) 20% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0270", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_4777_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.44377194605062° N, and the longitude is 10.008654233324194° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 0% - 80%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0271", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_303829_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.18987492057538° N, and the longitude is 9.911537840413034° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 40% - 60%", + "(C) 90.0% - 100.0%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0272", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_92256_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.14060497698616° N, and the longitude is 9.346080581773814° E.", + "Answer Choices": [ + "(A) 30% - 50%", + "(B) 50% - 100%", + "(C) 40% - 60%", + "(D) 20.0% - 30.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0273", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_29443_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.69668014403455° N, and the longitude is 9.525381824258842° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 50% - 90%", + "(C) 40.0% - 50.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0274", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_9_80309_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.361087821779925° N, and the longitude is 10.066306111907181° E.", + "Answer Choices": [ + "(A) 30.0% - 40.0%", + "(B) 60% - 90%", + "(C) 60% - 70%", + "(D) 10% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0275", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_92885_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.10943576019991° N, and the longitude is 9.359529826035178° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 90.0% - 100.0%", + "(C) 60% - 90%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0276", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_27095_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.90335715391982° N, and the longitude is 10.625403114056253° E.", + "Answer Choices": [ + "(A) 50% - 70%", + "(B) 0% - 10%", + "(C) 90.0% - 100.0%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0277", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_46256_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.82814129339801° N, and the longitude is 10.482565587775822° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 80%", + "(C) 70% - 90%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0278", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48690_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.66589507810533° N, and the longitude is 10.601376409116636° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 70%", + "(C) 50% - 70%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0279", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_4_25023_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.38055791830115° N, and the longitude is 8.007475869084969° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 50% - 90%", + "(C) 40% - 80%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0280", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_9459_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.208674466346125° N, and the longitude is 9.187663939684974° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 60%", + "(C) 0% - 10%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0281", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_62595_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.056478743902424° N, and the longitude is 8.45380455099471° E.", + "Answer Choices": [ + "(A) 10% - 100%", + "(B) 60% - 100%", + "(C) 80.0% - 90.0%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0282", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_8_31249_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.88513869771882° N, and the longitude is 9.718991407732426° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 80.0% - 90.0%", + "(C) 30% - 70%", + "(D) 0% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0283", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_49980_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.16115470001665° N, and the longitude is 8.11407335279669° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90.0% - 100.0%", + "(C) 40% - 90%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0284", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_64283_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.632576041930214° N, and the longitude is 8.471510148729998° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 90%", + "(C) 40% - 60%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0285", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_5_408_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 52.75072027774377° N, and the longitude is 8.480557989100639° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 60% - 90%", + "(C) 70% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0286", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_86336_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.022954840280114° N, and the longitude is 8.253840216461393° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 60% - 80%", + "(C) 90.0% - 100.0%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0287", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_46459_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.26040334857236° N, and the longitude is 9.52579596527541° E.", + "Answer Choices": [ + "(A) 0% - 100%", + "(B) 80% - 100%", + "(C) 0% - 90%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0288", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_2_56738_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.25726098794132° N, and the longitude is 9.562251537861805° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0289", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_29793_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.894230387757204° N, and the longitude is 10.262745993526194° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 80.0% - 90.0%", + "(C) 60% - 80%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0290", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_34465_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.14894145968699° N, and the longitude is 9.040264662610287° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 10.0% - 20.0%", + "(C) 40% - 90%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0291", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_60244_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.14232701243784° N, and the longitude is 9.868559692499753° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 80.0% - 90.0%", + "(C) 30% - 50%", + "(D) 0% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0292", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6177_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.160486576780826° N, and the longitude is 10.373519539873543° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 60% - 70%", + "(C) 10% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0293", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_88987_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.09114952355492° N, and the longitude is 10.33478161427044° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 50% - 90%", + "(C) 10% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0294", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85645_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.42655334031539° N, and the longitude is 10.931770824634985° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 30% - 60%", + "(C) 90.0% - 100.0%", + "(D) 40% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0295", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_5_94132_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.76693410329778° N, and the longitude is 9.421991823225609° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 40%", + "(C) 10% - 60%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0296", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_77037_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.45318340205874° N, and the longitude is 9.545049765558106° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 80% - 90%", + "(C) 10% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0297", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_26595_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.81858046329219° N, and the longitude is 8.852586492749758° E.", + "Answer Choices": [ + "(A) 40% - 60%", + "(B) 20% - 60%", + "(C) 60.0% - 70.0%", + "(D) 30% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0298", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_27064_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.28113457385743° N, and the longitude is 9.479363195636324° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 50% - 100%", + "(C) 60% - 100%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0299", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_23573_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.291460419021064° N, and the longitude is 9.409739864529302° E.", + "Answer Choices": [ + "(A) 50.0% - 60.0%", + "(B) 30% - 80%", + "(C) 40% - 50%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0300", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_40444_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.421021895639974° N, and the longitude is 9.86703905348583° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 40% - 60%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0301", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_88623_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.5286272496227° N, and the longitude is 9.293067227260014° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 80% - 90%", + "(C) 30% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0302", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_75545_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.42346635373634° N, and the longitude is 9.844472027430562° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 60% - 100%", + "(C) 80.0% - 90.0%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0303", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_93774_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.9001782439139° N, and the longitude is 8.61326589601794° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 20% - 70%", + "(C) 10% - 40%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0304", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_61865_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.76796643096637° N, and the longitude is 9.650573090799508° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 90.0% - 100.0%", + "(C) 60% - 80%", + "(D) 10% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0305", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_29398_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.021929637914006° N, and the longitude is 9.26870285515279° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 20% - 80%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0306", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_28848_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.608289603765385° N, and the longitude is 9.959908371452444° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 90.0% - 100.0%", + "(C) 0% - 30%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0307", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_81211_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.51380685397766° N, and the longitude is 7.492073279521614° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 10% - 20%", + "(C) 10% - 100%", + "(D) 40% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0308", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48233_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.61475112795554° N, and the longitude is 9.734624775768646° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0309", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_94626_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.483142199277616° N, and the longitude is 9.664934051782554° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 10% - 90%", + "(C) 20.0% - 30.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0310", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_154027_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.1277443314538° N, and the longitude is 9.621002490839478° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 90.0% - 100.0%", + "(C) 70% - 80%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0311", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_83273_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.08645046992684° N, and the longitude is 9.539595351014512° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 90.0% - 100.0%", + "(C) 40% - 90%", + "(D) 0% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0312", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45216_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.73713768651488° N, and the longitude is 10.625182629179509° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 90.0% - 100.0%", + "(C) 20% - 30%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0313", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_63589_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.73136280779515° N, and the longitude is 9.51049122228792° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 20% - 60%", + "(C) 90.0% - 100.0%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0314", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_41526_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.355759021743786° N, and the longitude is 8.83367520296089° E.", + "Answer Choices": [ + "(A) 10% - 20%", + "(B) 20% - 80%", + "(C) 60% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0315", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_265760_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.965826275341556° N, and the longitude is 10.241700650539034° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 70% - 80%", + "(C) 90.0% - 100.0%", + "(D) 40% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0316", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_88998_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.03866857349274° N, and the longitude is 11.178552074829087° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 90% - 100%", + "(C) 80.0% - 90.0%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0317", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_4_42008_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.39844195973829° N, and the longitude is 7.982157952665083° E.", + "Answer Choices": [ + "(A) 50.0% - 60.0%", + "(B) 60% - 80%", + "(C) 10% - 40%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0318", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_9_75955_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.9809842918188° N, and the longitude is 10.21196094470904° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 20% - 40%", + "(C) 0% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0319", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_4_56168_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.63964529450387° N, and the longitude is 8.866839036869088° E.", + "Answer Choices": [ + "(A) 50% - 60%", + "(B) 30% - 40%", + "(C) 90.0% - 100.0%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0320", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_159706_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 52.16649286615361° N, and the longitude is 9.601081084501779° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 50% - 60%", + "(C) 30% - 90%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0321", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_75614_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.5030520899657° N, and the longitude is 7.550416531801707° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 40% - 80%", + "(C) 60% - 90%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0322", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_86801_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.60700112075966° N, and the longitude is 9.20772836921054° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 50% - 80%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0323", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_49905_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.290986703216404° N, and the longitude is 9.424627789589174° E.", + "Answer Choices": [ + "(A) 30% - 50%", + "(B) 40% - 60%", + "(C) 80.0% - 90.0%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0324", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_29390_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.65395210605331° N, and the longitude is 10.61558958788806° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 20% - 40%", + "(C) 70% - 90%", + "(D) 40.0% - 50.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0325", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_8_32436_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.627711107100176° N, and the longitude is 10.568119963047108° E.", + "Answer Choices": [ + "(A) 40% - 100%", + "(B) 80% - 90%", + "(C) 30% - 60%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0326", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21939_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.20425649524122° N, and the longitude is 10.706532922829838° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 80% - 90%", + "(C) 50.0% - 60.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0327", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_215838_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.593979688885604° N, and the longitude is 8.532620672787585° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 50%", + "(C) 50% - 80%", + "(D) 20% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0328", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_26292_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.61956685379739° N, and the longitude is 10.637695897149625° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 60%", + "(C) 30% - 70%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0329", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_154018_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.127812872935685° N, and the longitude is 9.607861170190894° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 0% - 90%", + "(C) 30% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0330", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_82335_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.68016155417058° N, and the longitude is 9.553806614513878° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 50%", + "(C) 0% - 80%", + "(D) 0% - 10%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0331", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_7866_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.7420951998414° N, and the longitude is 10.274807492418354° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 0% - 10%", + "(C) 60% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0332", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_3_55529_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.12471256346076° N, and the longitude is 8.114665350664175° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 90.0% - 100.0%", + "(C) 10% - 90%", + "(D) 10% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0333", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_2_87768_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.90861001315565° N, and the longitude is 9.720227166440106° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 60% - 100%", + "(C) 40% - 50%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0334", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_77584_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.59969308643924° N, and the longitude is 9.219952674844414° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 70.0% - 80.0%", + "(C) 0% - 30%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0335", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6630_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.88269234072796° N, and the longitude is 10.199639084014768° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 10% - 30%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0336", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_8_81835_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.62544210588806° N, and the longitude is 9.760563582225698° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 30% - 70%", + "(C) 90.0% - 100.0%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0337", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_146847_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.026822723827685° N, and the longitude is 10.388896821154152° E.", + "Answer Choices": [ + "(A) 20.0% - 30.0%", + "(B) 10% - 50%", + "(C) 50% - 60%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0338", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_80772_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.68955598104425° N, and the longitude is 9.670060802143066° E.", + "Answer Choices": [ + "(A) 40% - 60%", + "(B) 70% - 90%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0339", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_76748_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.301258540752904° N, and the longitude is 7.643522485674636° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 60% - 70%", + "(C) 60% - 100%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0340", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_86939_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.89295941747196° N, and the longitude is 9.557376744061607° E.", + "Answer Choices": [ + "(A) 50% - 60%", + "(B) 30% - 60%", + "(C) 0% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0341", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_164182_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.19721897217576° N, and the longitude is 9.330930130934798° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 40%", + "(C) 30% - 80%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0342", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20240_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.690345627822495° N, and the longitude is 10.50236878903355° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 30% - 50%", + "(C) 10.0% - 20.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0343", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45329_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.781171545080504° N, and the longitude is 10.397980527327148° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 30% - 50%", + "(C) 90.0% - 100.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0344", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48505_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.22206021374649° N, and the longitude is 10.800563287213441° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 40% - 50%", + "(C) 60% - 70%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0345", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_6_29325_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.21944474267555° N, and the longitude is 9.505037396535352° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 80.0% - 90.0%", + "(C) 10% - 100%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0346", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24417_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.86762426094783° N, and the longitude is 9.783718262510304° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 90.0% - 100.0%", + "(C) 10% - 40%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0347", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44087_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.62363273920607° N, and the longitude is 8.72215461196734° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 80.0% - 90.0%", + "(C) 10% - 50%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0348", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_2_1574_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.514741325148634° N, and the longitude is 7.8582759932142405° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 0% - 30%", + "(C) 90.0% - 100.0%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0349", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_4571_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 52.94256007011094° N, and the longitude is 8.734616275216423° E.", + "Answer Choices": [ + "(A) 20% - 80%", + "(B) 20% - 70%", + "(C) 40% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0350", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_64296_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.2393001818561° N, and the longitude is 10.721026452312515° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 30% - 60%", + "(C) 90.0% - 100.0%", + "(D) 0% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0351", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_7620_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.218132009825624° N, and the longitude is 9.092078228302713° E.", + "Answer Choices": [ + "(A) 10% - 60%", + "(B) 90.0% - 100.0%", + "(C) 60% - 70%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0352", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_7898_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.45302991861228° N, and the longitude is 9.554871324126989° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 10.0% - 20.0%", + "(C) 40% - 50%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0353", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_2_92984_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.94069842130798° N, and the longitude is 7.986087681342039° E.", + "Answer Choices": [ + "(A) 50% - 100%", + "(B) 10.0% - 20.0%", + "(C) 50% - 70%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0354", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_83547_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.63829096048595° N, and the longitude is 9.081622275854595° E.", + "Answer Choices": [ + "(A) 70% - 100%", + "(B) 40% - 50%", + "(C) 90% - 100%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0355", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_26673_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.02765458530276° N, and the longitude is 10.216105014215358° E.", + "Answer Choices": [ + "(A) 20% - 40%", + "(B) 0% - 60%", + "(C) 60% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0356", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27820_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.6733323339012° N, and the longitude is 9.754827144494351° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 20% - 90%", + "(C) 20% - 30%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0357", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_9302_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 53.420580091717596° N, and the longitude is 9.859418248938322° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 80% - 90%", + "(C) 70.0% - 80.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0358", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_8326_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.20390999678319° N, and the longitude is 9.311477467680424° E.", + "Answer Choices": [ + "(A) 50% - 80%", + "(B) 40.0% - 50.0%", + "(C) 0% - 20%", + "(D) 10% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0359", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_39992_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.48753426809041° N, and the longitude is 9.642712924022113° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 20% - 40%", + "(C) 20% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0360", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_63909_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.270317126513525° N, and the longitude is 11.034729193374403° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 40% - 70%", + "(C) 80.0% - 90.0%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0361", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_45382_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 51.895525387861326° N, and the longitude is 9.78023005364485° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 60% - 90%", + "(C) 30% - 60%", + "(D) 70% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0362", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_48533_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.99896521109545° N, and the longitude is 10.236763265757235° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 60% - 80%", + "(C) 20% - 90%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0363", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_27889_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.665297376834° N, and the longitude is 10.63695398067436° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 50% - 90%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0364", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_9_51132_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.85529567133953° N, and the longitude is 8.6020104766157° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 0% - 10%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0365", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_5_84248_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.505183606786325° N, and the longitude is 9.654411156213992° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 10% - 80%", + "(C) 80% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0366", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21212_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.065720624524054° N, and the longitude is 10.379222961724516° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 60% - 80%", + "(C) 70% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0367", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_224782_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.65419201090339° N, and the longitude is 9.063955672508717° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 40%", + "(C) 40% - 70%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0368", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_1_94142_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.56406479756343° N, and the longitude is 7.885397107438149° E.", + "Answer Choices": [ + "(A) 50% - 70%", + "(B) 10% - 80%", + "(C) 60% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0369", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_3_39568_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.50752013126691° N, and the longitude is 9.251549957973767° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 40% - 70%", + "(C) 70% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0370", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_8291_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.19331960066428° N, and the longitude is 9.281723829555036° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 90.0% - 100.0%", + "(C) 20% - 70%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0371", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_85345_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.49251726181045° N, and the longitude is 9.68040986117067° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 90.0% - 100.0%", + "(C) 10% - 20%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0372", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_9_28781_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.04239429839994° N, and the longitude is 9.573468819480048° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 60% - 70%", + "(C) 0% - 10%", + "(D) 60% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0373", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_28931_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.63300395334942° N, and the longitude is 9.63628432425523° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 0% - 80%", + "(C) 80.0% - 90.0%", + "(D) 60% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0374", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_208481_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.5436229314771° N, and the longitude is 8.886914251718038° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 10% - 50%", + "(C) 30% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0375", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_169269_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.237857234044974° N, and the longitude is 9.524461249670422° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 70% - 90%", + "(C) 90.0% - 100.0%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0376", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24088_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.57184705184533° N, and the longitude is 7.755774619050287° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 50.0% - 60.0%", + "(C) 70% - 80%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0377", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_176181_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.294001818947834° N, and the longitude is 9.418128592404043° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 10% - 50%", + "(C) 20.0% - 30.0%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0378", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_38234_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.067606371262336° N, and the longitude is 10.353349899510734° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 80.0% - 90.0%", + "(C) 0% - 60%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0379", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_8406_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.51078428639491° N, and the longitude is 10.149860855869598° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 60%", + "(C) 60% - 90%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0380", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21038_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 53.32994277396465° N, and the longitude is 10.266837701460654° E.", + "Answer Choices": [ + "(A) 0% - 80%", + "(B) 90.0% - 100.0%", + "(C) 40% - 70%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0381", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_42157_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.267902177244736° N, and the longitude is 9.11756555173948° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 60% - 70%", + "(C) 50% - 90%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0382", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_4_75064_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Betula? The latitude is 53.02687481609911° N, and the longitude is 8.285747557162008° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 10.0% - 20.0%", + "(C) 20% - 90%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0383", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_29775_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.65290294134707° N, and the longitude is 10.407943027853621° E.", + "Answer Choices": [ + "(A) 30% - 50%", + "(B) 80% - 90%", + "(C) 90.0% - 100.0%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0384", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_31118_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 51.51031489205413° N, and the longitude is 10.07075241152665° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 70% - 90%", + "(C) 0% - 90%", + "(D) 0% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0385", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60143_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.033016927053204° N, and the longitude is 10.965210133350224° E.", + "Answer Choices": [ + "(A) 0% - 50%", + "(B) 90.0% - 100.0%", + "(C) 30% - 70%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0386", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_5093_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.28767098799612° N, and the longitude is 10.777992459016206° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 90.0% - 100.0%", + "(C) 50% - 60%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0387", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85275_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.72730445009898° N, and the longitude is 9.449455231193182° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 60% - 90%", + "(C) 30% - 80%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0388", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_299298_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.155899425196914° N, and the longitude is 10.440035737825303° E.", + "Answer Choices": [ + "(A) 20% - 60%", + "(B) 50% - 60%", + "(C) 90.0% - 100.0%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0389", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_9_60572_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.457418280040436° N, and the longitude is 9.244284356063124° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 20% - 70%", + "(C) 90.0% - 100.0%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0390", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_2_75120_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.51652619355276° N, and the longitude is 7.8328625044819535° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 10% - 60%", + "(C) 90.0% - 100.0%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0391", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_4_30586_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.19751779048824° N, and the longitude is 9.315088619034743° E.", + "Answer Choices": [ + "(A) 10.0% - 20.0%", + "(B) 70% - 80%", + "(C) 80% - 90%", + "(D) 70% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0392", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_5_86611_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.096122511638484° N, and the longitude is 10.206897850016896° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90.0% - 100.0%", + "(C) 70% - 80%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0393", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_83915_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.567706270366855° N, and the longitude is 9.358238095919253° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 50%", + "(C) 0% - 70%", + "(D) 20% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0394", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_289554_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.10482289053612° N, and the longitude is 10.880339331180753° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 20% - 80%", + "(C) 90.0% - 100.0%", + "(D) 40% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0395", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_61134_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.741208245292256° N, and the longitude is 9.492071711466224° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 70%", + "(C) 10% - 40%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0396", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_87568_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.09455871694086° N, and the longitude is 10.341662925486089° E.", + "Answer Choices": [ + "(A) 10% - 30%", + "(B) 90.0% - 100.0%", + "(C) 30% - 90%", + "(D) 20% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0397", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_147400_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.03690146465276° N, and the longitude is 10.208496801659818° E.", + "Answer Choices": [ + "(A) 40.0% - 50.0%", + "(B) 70% - 80%", + "(C) 50% - 100%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0398", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_80181_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.080210631429104° N, and the longitude is 9.917122686725175° E.", + "Answer Choices": [ + "(A) 10% - 30%", + "(B) 80.0% - 90.0%", + "(C) 90% - 100%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0399", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_2_28354_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.78753058978405° N, and the longitude is 9.613133135777037° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 40% - 100%", + "(C) 60.0% - 70.0%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0400", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_26923_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.65696804699725° N, and the longitude is 10.56335320495351° E.", + "Answer Choices": [ + "(A) 20% - 30%", + "(B) 20% - 60%", + "(C) 20% - 40%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0401", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_75127_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.84702519086805° N, and the longitude is 9.587207042603° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 10% - 70%", + "(C) 10% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0402", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_8356_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.082126079628786° N, and the longitude is 9.950616004564589° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 10% - 60%", + "(C) 40% - 70%", + "(D) 30% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0403", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_2_41999_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.74384199091836° N, and the longitude is 9.51768232905286° E.", + "Answer Choices": [ + "(A) 80% - 100%", + "(B) 40.0% - 50.0%", + "(C) 90% - 100%", + "(D) 50% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0404", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_301652_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.16614511918415° N, and the longitude is 10.923398058488768° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 20% - 40%", + "(C) 90.0% - 100.0%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0405", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_4_37171_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.566606665378096° N, and the longitude is 9.321848051369201° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 30% - 80%", + "(C) 40.0% - 50.0%", + "(D) 70% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0406", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5518_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.92076729662314° N, and the longitude is 8.830271656811798° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 60% - 70%", + "(C) 10.0% - 20.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0407", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_46604_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.87994484414696° N, and the longitude is 10.340699030957644° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 50%", + "(C) 40% - 90%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0408", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_4_88332_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.267619098311634° N, and the longitude is 9.518671854062827° E.", + "Answer Choices": [ + "(A) 10% - 60%", + "(B) 90.0% - 100.0%", + "(C) 50% - 70%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0409", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_94398_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.755290482067906° N, and the longitude is 9.471060867775549° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 20% - 30%", + "(C) 80.0% - 90.0%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0410", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_1_76175_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 51.71024457942874° N, and the longitude is 10.298689417609879° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 50% - 80%", + "(C) 90.0% - 100.0%", + "(D) 10% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0411", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_85090_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.86896837930145° N, and the longitude is 9.380925467433018° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 10.0% - 20.0%", + "(C) 80% - 100%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0412", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_3_94688_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.93830044460352° N, and the longitude is 7.966410550545998° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 90% - 100%", + "(C) 20% - 50%", + "(D) 10.0% - 20.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0413", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_45098_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 53.170345886529105° N, and the longitude is 10.985058286415573° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 90.0% - 100.0%", + "(C) 50% - 80%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0414", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_3_57059_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.450958889611165° N, and the longitude is 7.194143281579879° E.", + "Answer Choices": [ + "(A) 40% - 70%", + "(B) 10% - 50%", + "(C) 10% - 70%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0415", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24447_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.70855995774889° N, and the longitude is 9.667462001981203° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 0% - 10%", + "(C) 70% - 100%", + "(D) 20.0% - 30.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0416", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_6359_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.98003468326007° N, and the longitude is 9.668963655765806° E.", + "Answer Choices": [ + "(A) 20% - 50%", + "(B) 90.0% - 100.0%", + "(C) 60% - 90%", + "(D) 0% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0417", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_3_5582_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.83344706899968° N, and the longitude is 10.193253494096247° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 90.0% - 100.0%", + "(C) 40% - 60%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0418", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_60706_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.18660371400776° N, and the longitude is 9.860478064167884° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 50% - 80%", + "(C) 90.0% - 100.0%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0419", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_49039_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.6841156727948° N, and the longitude is 10.439604858501601° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 80%", + "(C) 80% - 90%", + "(D) 50% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0420", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_5790_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.45918471268836° N, and the longitude is 9.99316688147228° E.", + "Answer Choices": [ + "(A) 30.0% - 40.0%", + "(B) 0% - 10%", + "(C) 40% - 80%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0421", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_3_80290_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.096637225994186° N, and the longitude is 10.836694547014647° E.", + "Answer Choices": [ + "(A) 0% - 90%", + "(B) 90.0% - 100.0%", + "(C) 0% - 80%", + "(D) 0% - 10%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0422", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_8922_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.91701747458129° N, and the longitude is 8.479584508634737° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 50% - 90%", + "(C) 10% - 20%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0423", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_6_50459_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.85544764211219° N, and the longitude is 8.599384647962333° E.", + "Answer Choices": [ + "(A) 10% - 100%", + "(B) 90% - 100%", + "(C) 80.0% - 90.0%", + "(D) 20% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0424", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_3_141113_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.976679240947306° N, and the longitude is 9.43844872061495° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 0% - 60%", + "(D) 0% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0425", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_4_80419_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.025300725301754° N, and the longitude is 10.409843120829663° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 90.0% - 100.0%", + "(C) 60% - 70%", + "(D) 20% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0426", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_5_224415_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.65060054144224° N, and the longitude is 9.058040034298394° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 80% - 90%", + "(C) 40% - 80%", + "(D) 0% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0427", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60056_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.645950899729556° N, and the longitude is 7.719480908791942° E.", + "Answer Choices": [ + "(A) 70% - 100%", + "(B) 30% - 60%", + "(C) 70% - 80%", + "(D) 60.0% - 70.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0428", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_45149_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.85483137907198° N, and the longitude is 10.264073679677406° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 60.0% - 70.0%", + "(C) 30% - 80%", + "(D) 10% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0429", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_0_35293_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.51752055546795° N, and the longitude is 9.676183394280098° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 80% - 90%", + "(C) 20% - 60%", + "(D) 60.0% - 70.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0430", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_47585_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.78635977300678° N, and the longitude is 10.270882327007541° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 20% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0431", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_9362_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.625824915177986° N, and the longitude is 10.432616003194532° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 30% - 60%", + "(C) 90.0% - 100.0%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0432", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_2_48110_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.788653462770064° N, and the longitude is 10.280898421078401° E.", + "Answer Choices": [ + "(A) 0% - 60%", + "(B) 20% - 30%", + "(C) 90.0% - 100.0%", + "(D) 10% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0433", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_9_47739_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.861223046170586° N, and the longitude is 10.282903857405815° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 90%", + "(C) 50% - 60%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0434", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_7_27826_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 53.235248208317° N, and the longitude is 10.81700458178663° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 60%", + "(C) 50% - 90%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0435", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_rubra_4_91621_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.18374424499942° N, and the longitude is 9.845964050665467° E.", + "Answer Choices": [ + "(A) 70% - 100%", + "(B) 30.0% - 40.0%", + "(C) 40% - 90%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0436", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_158130_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.15870193920303° N, and the longitude is 9.539603069376028° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 30% - 90%", + "(C) 30% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0437", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_10_81567_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.42918548927929° N, and the longitude is 10.090398641532582° E.", + "Answer Choices": [ + "(A) 50% - 60%", + "(B) 30% - 70%", + "(C) 10% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0438", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20623_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.69248122916619° N, and the longitude is 9.734481136584185° E.", + "Answer Choices": [ + "(A) 40% - 100%", + "(B) 80% - 90%", + "(C) 60% - 80%", + "(D) 20.0% - 30.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0439", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_10_25512_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.147430227388845° N, and the longitude is 9.154227158740436° E.", + "Answer Choices": [ + "(A) 40% - 50%", + "(B) 30% - 50%", + "(C) 90.0% - 100.0%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0440", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_28988_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.91784056752656° N, and the longitude is 10.22991664182267° E.", + "Answer Choices": [ + "(A) 0% - 100%", + "(B) 0% - 20%", + "(C) 60.0% - 70.0%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0441", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_77409_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 53.50300406663929° N, and the longitude is 9.01533007936118° E.", + "Answer Choices": [ + "(A) 50% - 90%", + "(B) 40% - 80%", + "(C) 40% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0442", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_1_145543_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.01468773234622° N, and the longitude is 9.36162328600096° E.", + "Answer Choices": [ + "(A) 50% - 100%", + "(B) 60.0% - 70.0%", + "(C) 90% - 100%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0443", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_7597_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.021728841241206° N, and the longitude is 9.708955702531922° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 10% - 30%", + "(C) 30% - 40%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0444", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_144550_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 52.00586525819098° N, and the longitude is 9.303301411886714° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 20% - 90%", + "(C) 70% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0445", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_28927_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.75896670729299° N, and the longitude is 10.39404058490764° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 50% - 60%", + "(C) 0% - 30%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0446", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24946_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.43869720154381° N, and the longitude is 10.643131221616162° E.", + "Answer Choices": [ + "(A) 0% - 20%", + "(B) 90% - 100%", + "(C) 80% - 90%", + "(D) 50.0% - 60.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0447", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_30459_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Alnus? The latitude is 52.374940488615124° N, and the longitude is 9.42271539896552° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 20.0% - 30.0%", + "(C) 50% - 70%", + "(D) 30% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0448", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_220556_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.62627061687822° N, and the longitude is 8.517509408467504° E.", + "Answer Choices": [ + "(A) 10% - 30%", + "(B) 70% - 90%", + "(C) 70% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0449", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_2_7695_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 52.122491706872545° N, and the longitude is 10.329958495662073° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 50.0% - 60.0%", + "(C) 80% - 100%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0450", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_6_82805_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.13725489606995° N, and the longitude is 10.68712076782035° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 20% - 90%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0451", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_62704_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.726527500639186° N, and the longitude is 7.726348762698521° E.", + "Answer Choices": [ + "(A) 50% - 60%", + "(B) 60% - 80%", + "(C) 90.0% - 100.0%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0452", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22980_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.368493559492265° N, and the longitude is 9.689968690863099° E.", + "Answer Choices": [ + "(A) 50% - 100%", + "(B) 10.0% - 20.0%", + "(C) 70% - 80%", + "(D) 60% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0453", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_139383_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.96276226449928° N, and the longitude is 10.162852527943649° E.", + "Answer Choices": [ + "(A) 30.0% - 40.0%", + "(B) 10% - 100%", + "(C) 40% - 90%", + "(D) 50% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0454", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_6_60813_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.62549476791422° N, and the longitude is 10.0185467273566° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 0% - 60%", + "(C) 40% - 90%", + "(D) 10% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0455", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_3_60452_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.10971633804602° N, and the longitude is 8.413816338818664° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 60%", + "(C) 40% - 90%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0456", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_22246_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.92440228626015° N, and the longitude is 10.195643333927558° E.", + "Answer Choices": [ + "(A) 70.0% - 80.0%", + "(B) 0% - 10%", + "(C) 0% - 20%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0457", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_1_27630_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.47033305639779° N, and the longitude is 9.651405997576862° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 30% - 60%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0458", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_8_85362_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.38930065587152° N, and the longitude is 8.12232133581922° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 80%", + "(C) 40% - 70%", + "(D) 70% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0459", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_9_463_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Abies? The latitude is 53.499222690097675° N, and the longitude is 8.9890189502952° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 50% - 90%", + "(C) 10% - 80%", + "(D) 30% - 60%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0460", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_4_6730_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.73148591092223° N, and the longitude is 10.444581878204735° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 20.0% - 30.0%", + "(C) 40% - 60%", + "(D) 10% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0461", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_7_53512_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 51.528240403206446° N, and the longitude is 9.768568751701823° E.", + "Answer Choices": [ + "(A) 60% - 90%", + "(B) 90.0% - 100.0%", + "(C) 0% - 40%", + "(D) 60% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0462", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_78346_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.89570269296198° N, and the longitude is 7.945626305617428° E.", + "Answer Choices": [ + "(A) 30% - 70%", + "(B) 60% - 80%", + "(C) 80.0% - 90.0%", + "(D) 20% - 40%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0463", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_77844_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 51.31764524831685° N, and the longitude is 9.743733000362987° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 50%", + "(C) 80% - 90%", + "(D) 0% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0464", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_5_53249_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.85278433200615° N, and the longitude is 8.606676192561595° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 10% - 30%", + "(C) 90.0% - 100.0%", + "(D) 40% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0465", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_0_26877_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.93577856255123° N, and the longitude is 9.79409513696009° E.", + "Answer Choices": [ + "(A) 90% - 100%", + "(B) 70.0% - 80.0%", + "(C) 30% - 70%", + "(D) 0% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0466", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21919_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 52.26434919407881° N, and the longitude is 9.512269077958981° E.", + "Answer Choices": [ + "(A) 50.0% - 60.0%", + "(B) 80% - 90%", + "(C) 10% - 50%", + "(D) 60% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0467", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21815_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Betula? The latitude is 53.18324392051524° N, and the longitude is 8.33549833821219° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 30.0% - 40.0%", + "(C) 60% - 100%", + "(D) 70% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0468", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_9_34831_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.15094823397459° N, and the longitude is 9.899689168200693° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 70% - 90%", + "(C) 0% - 50%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0469", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_284517_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.088618386155794° N, and the longitude is 10.272102042970607° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 10% - 40%", + "(C) 60% - 70%", + "(D) 30% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0470", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_44838_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 53.274070811230544° N, and the longitude is 10.731292493455602° E.", + "Answer Choices": [ + "(A) 80% - 90%", + "(B) 0% - 90%", + "(C) 30.0% - 40.0%", + "(D) 20% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0471", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_47296_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 51.92734021888079° N, and the longitude is 10.269645995017626° E.", + "Answer Choices": [ + "(A) 20.0% - 30.0%", + "(B) 70% - 90%", + "(C) 0% - 70%", + "(D) 0% - 20%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0472", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_strobus_3_55392_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.45203592279387° N, and the longitude is 7.192834022354107° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 30% - 60%", + "(C) 60% - 90%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0473", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_21619_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.91210351848411° N, and the longitude is 10.62059947743381° E.", + "Answer Choices": [ + "(A) 80.0% - 90.0%", + "(B) 90% - 100%", + "(C) 10% - 40%", + "(D) 40% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0474", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_86542_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.78551636994594° N, and the longitude is 8.36422193789555° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 40% - 90%", + "(C) 90.0% - 100.0%", + "(D) 20% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0475", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Abies_alba_3_1641_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.85161778758299° N, and the longitude is 8.672814944267774° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 70% - 80%", + "(C) 10.0% - 20.0%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0476", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_11_81387_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.668326516990454° N, and the longitude is 9.441574936326349° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 60% - 70%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0477", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_3_48681_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.31114464716658° N, and the longitude is 9.755097981332632° E.", + "Answer Choices": [ + "(A) 10% - 40%", + "(B) 80% - 90%", + "(C) 40% - 80%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0478", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_6_86629_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.3596760059331° N, and the longitude is 7.254985151464911° E.", + "Answer Choices": [ + "(A) 0% - 70%", + "(B) 90% - 100%", + "(C) 20% - 80%", + "(D) 50.0% - 60.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0479", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_robur_3_87031_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.86921871251952° N, and the longitude is 8.995973059591519° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 50%", + "(C) 30% - 90%", + "(D) 40% - 70%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0480", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_5_224698_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.65329172764031° N, and the longitude is 9.06690970001896° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 0% - 90%", + "(C) 40% - 70%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0481", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24429_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.65763100037862° N, and the longitude is 10.453916287983708° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 50% - 100%", + "(C) 0% - 30%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0482", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fraxinus_excelsior_6_30915_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fraxinus? The latitude is 52.50521943725245° N, and the longitude is 10.921779733596484° E.", + "Answer Choices": [ + "(A) 20% - 70%", + "(B) 70% - 90%", + "(C) 10% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0483", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Acer_pseudoplatanus_1_8620_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Acer? The latitude is 51.848540968313465° N, and the longitude is 10.330228513016692° E.", + "Answer Choices": [ + "(A) 10% - 50%", + "(B) 40% - 90%", + "(C) 90% - 100%", + "(D) 60.0% - 70.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0484", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_264903_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.958406972556226° N, and the longitude is 10.176009452778345° E.", + "Answer Choices": [ + "(A) 40% - 90%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 30% - 50%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0485", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_1_82156_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.8086561003024° N, and the longitude is 9.604205321542805° E.", + "Answer Choices": [ + "(A) 30% - 60%", + "(B) 80% - 90%", + "(C) 90.0% - 100.0%", + "(D) 60% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0486", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_kaempferi_3_42275_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 52.547708518531714° N, and the longitude is 9.445316704896532° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 70% - 90%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0487", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_20293_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Cleared? The latitude is 51.751720816875306° N, and the longitude is 10.378888061221534° E.", + "Answer Choices": [ + "(A) 30% - 90%", + "(B) 0% - 70%", + "(C) 40% - 90%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0488", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_4_49952_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 52.122672763487955° N, and the longitude is 9.634561410502476° E.", + "Answer Choices": [ + "(A) 10% - 80%", + "(B) 60% - 90%", + "(C) 30% - 60%", + "(D) 90.0% - 100.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0489", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Cleared_0_24405_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Fagus? The latitude is 51.73564086734748° N, and the longitude is 9.546780108450491° E.", + "Answer Choices": [ + "(A) 30% - 80%", + "(B) 20.0% - 30.0%", + "(C) 40% - 80%", + "(D) 40% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0490", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_318137_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.27739880171732° N, and the longitude is 10.698995392811133° E.", + "Answer Choices": [ + "(A) 60% - 80%", + "(B) 90.0% - 100.0%", + "(C) 80% - 90%", + "(D) 40% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0491", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_7_83884_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 52.38034167046129° N, and the longitude is 10.797603078675834° E.", + "Answer Choices": [ + "(A) 90.0% - 100.0%", + "(B) 20% - 80%", + "(C) 10% - 80%", + "(D) 10% - 30%", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0492", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_2_61695_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.07888739238455° N, and the longitude is 9.561671479664643° E.", + "Answer Choices": [ + "(A) 40% - 80%", + "(B) 90.0% - 100.0%", + "(C) 50% - 90%", + "(D) 0% - 10%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0493", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_sylvestris_4_221750_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 52.63441101164866° N, and the longitude is 9.081651028350146° E.", + "Answer Choices": [ + "(A) 0% - 30%", + "(B) 20% - 30%", + "(C) 90.0% - 100.0%", + "(D) 80% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0494", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Picea_abies_6_46511_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Picea? The latitude is 51.87389851384472° N, and the longitude is 10.240332291757415° E.", + "Answer Choices": [ + "(A) 70% - 80%", + "(B) 60% - 70%", + "(C) 10% - 20%", + "(D) 80.0% - 90.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0495", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Fagus_sylvatica_8_6073_BI_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 51.46205892213685° N, and the longitude is 10.168780429667562° E.", + "Answer Choices": [ + "(A) 40% - 100%", + "(B) 50% - 90%", + "(C) 10% - 30%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0496", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Quercus_petraea_2_82782_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Quercus? The latitude is 53.06774568337227° N, and the longitude is 9.375295151207466° E.", + "Answer Choices": [ + "(A) 10% - 20%", + "(B) 80.0% - 90.0%", + "(C) 50% - 70%", + "(D) 90% - 100%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0497", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pseudotsuga_menziesii_3_77228_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pseudotsuga? The latitude is 52.914295562118085° N, and the longitude is 7.9222217587042785° E.", + "Answer Choices": [ + "(A) 20% - 40%", + "(B) 40% - 70%", + "(C) 50% - 60%", + "(D) 70.0% - 80.0%", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0498", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Larix_decidua_0_35241_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Larix? The latitude is 51.70177625158714° N, and the longitude is 9.75185327473106° E.", + "Answer Choices": [ + "(A) 60% - 70%", + "(B) 90.0% - 100.0%", + "(C) 30% - 80%", + "(D) 50% - 90%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + }, + { + "Question_id": "Tree Species Proportion Prediction/0499", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TreeSatAI/dataset/Pinus_nigra_5_51620_WEFL_NLF.tif" + ], + "Text": "What percentage of all the trees in this picture are Pinus? The latitude is 53.85222736341018° N, and the longitude is 8.599076957349133° E.", + "Answer Choices": [ + "(A) 70% - 90%", + "(B) 90.0% - 100.0%", + "(C) 40% - 80%", + "(D) 30% - 80%", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Perception", + "L4-task": "Tree Species Proportion Prediction", + "Dataset": "TreeSatAI", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Animal_Classification.json b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Animal_Classification.json new file mode 100644 index 0000000000000000000000000000000000000000..e09fdf4954a2b015002f710de1f7f4730189604e --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Animal_Classification.json @@ -0,0 +1,2270 @@ +[ + { + "Question_id": "Animal Classification/0000", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes forreferring objects. Bounding box in the format of (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 448x448. Bounding box:[<657><198><663><204>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2240.y2688.png" + ] + }, + { + "Question_id": "Animal Classification/0001", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<576><272><583><278>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2240.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0002", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<774><170><781><174>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0003", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<757><20><761><23>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagul", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0004", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<642><278><648><283>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0005", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<613><287><618><291>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0006", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<819><221><825><227>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0007", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<736><200><742><209>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y2688.png" + ] + }, + { + "Question_id": "Animal Classification/0008", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<848><336><855><341>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0009", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<477><30><482><34>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0010", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<800><117><806><124>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0011", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<513><210><518><217>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagul", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x9408.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0012", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<516><279><520><282>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0013", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<554><211><562><217>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) dolphin", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y2240.png" + ] + }, + { + "Question_id": "Animal Classification/0014", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<540><342><547><348>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0015", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<716><168><721><174>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4032.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0016", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<620><373><625><379>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y2240.png" + ] + }, + { + "Question_id": "Animal Classification/0017", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<679><405><685><410>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4928.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0018", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<631><233><636><238>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0019", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<522><154><526><158>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5824.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0020", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<592><161><599><170>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0021", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<861><354><874><363>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0022", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<673><175><680><181>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) cow", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4928.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0023", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<633><284><644><294>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) arctic fox", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0024", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<726><335><731><341>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagul", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0025", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<768><65><773><71>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) seagull", + "(C) seal", + "(D) polar bearseagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0026", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<457><212><462><221>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0027", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<750><149><757><155>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0028", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<825><61><832><71>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0029", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<871><141><877><148>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0030", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<760><205><768><212>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x8512.y1792.png" + ] + }, + { + "Question_id": "Animal Classification/0031", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<536><243><548><257>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) seal", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0032", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<654><103><659><107>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) bear", + "(C) panda", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y2688.png" + ] + }, + { + "Question_id": "Animal Classification/0033", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<589><53><597><61>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0034", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<844><355><851><362>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) penguin", + "(C) seal", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0035", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<728><323><736><330>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) seagull", + "(C) penguin", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3136.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0036", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<691><48><696><55>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) seagull", + "(C) seal", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0037", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<530><53><542><67>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin ", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4928.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0038", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<809><423><817><431>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y1792.png" + ] + }, + { + "Question_id": "Animal Classification/0039", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<544><213><551><222>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0040", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<754><134><762><140>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0041", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<679><65><688><73>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0042", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<761><156><771><162>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin ", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y2240.png" + ] + }, + { + "Question_id": "Animal Classification/0043", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<682><73><687><78>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0044", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<810><10><815><16>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) seagull", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0045", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<498><181><504><186>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0046", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<759><207><770><216>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0047", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<615><167><626><184>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0048", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<530><363><535><371>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3136.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0049", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<846><390><852><395>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4480.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0050", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<595><296><607><309>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3136.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0051", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<605><144><614><150>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x4480.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0052", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<659><314><666><322>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3584.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0053", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<518><344><524><349>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y2688.png" + ] + }, + { + "Question_id": "Animal Classification/0054", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<660><179><664><183>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0055", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<785><255><795><264>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3584.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0056", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<482><104><494><116>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0057", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<819><92><823><97>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x2240.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0058", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<611><86><616><91>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x2688.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0059", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<643><193><650><199>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0060", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<831><203><836><209>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0061", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<776><260><789><268>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0062", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<865><67><873><73>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0063", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<872><343><878><350>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0064", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<734><240><741><246>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x5824.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0065", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<593><148><598><154>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x5824.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0066", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<592><58><599><63>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x6720.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0067", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<685><40><695><47>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y2240.png" + ] + }, + { + "Question_id": "Animal Classification/0068", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<676><56><686><66>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0069", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<725><19><735><26>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9408.y896.png" + ] + }, + { + "Question_id": "Animal Classification/0070", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<817><98><828><110>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0071", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<790><103><801><115>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0072", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<651><330><663><345>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x4928.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0073", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<661><165><666><172>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x5376.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0074", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<469><302><475><306>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3136.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0075", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<467><191><473><196>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguinl", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0076", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<717><152><728><160>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0077", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<794><100><799><108>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y1344.png" + ] + }, + { + "Question_id": "Animal Classification/0078", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<756><137><766><144>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0079", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<858><35><862><39>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0080", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<857><326><862><332>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0081", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<458><409><464><416>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0082", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<859><15><864><18>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D)penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x3584.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0083", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<812><22><824><44>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) seagull", + "(C) seal", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0084", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<640><312><648><321>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) sea lion", + "(C) arctic fox", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y4032.png" + ] + }, + { + "Question_id": "Animal Classification/0085", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<523><13><534><26>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D) penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0086", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<779><110><784><114>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0087", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<646><210><651><214>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0088", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<807><195><813><202>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3136.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0089", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<869><18><877><24>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0090", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<528><109><531><114>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y6272.png" + ] + }, + { + "Question_id": "Animal Classification/0091", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<647><130><654><135>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5824.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0092", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<661><288><667><293>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y5376.png" + ] + }, + { + "Question_id": "Animal Classification/0093", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<647><204><656><212>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0094", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<860><429><866><433>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0095", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<719><416><728><422>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y3136.png" + ] + }, + { + "Question_id": "Animal Classification/0096", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<488><415><494><419>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) polar bear", + "(C) penguin", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0097", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<799><400><804><406>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) polar bear", + "(B) penguin", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9408.y448.png" + ] + }, + { + "Question_id": "Animal Classification/0098", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<599><123><606><132>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seagull", + "(B) polar bear", + "(C) seal", + "(D)penguin", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y6720.png" + ] + }, + { + "Question_id": "Animal Classification/0099", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<734><306><741><312>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y2688.png" + ] + }, + { + "Question_id": "Animal Classification/0100", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<514><289><520><295>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) seagull", + "(C) seal", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x2688.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0101", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<512><94><529><105>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Animal Classification/0102", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<549><190><564><218>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) elephant seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y3584.png" + ] + }, + { + "Question_id": "Animal Classification/0103", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<726><297><734><305>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x7168.y4480.png" + ] + }, + { + "Question_id": "Animal Classification/0104", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<776><250><788><261>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0105", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<776><250><788><261>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) seal", + "(B) seagull", + "(C) penguin", + "(D) polar bear", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0106", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<653><273><663><282>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x7616.y4928.png" + ] + }, + { + "Question_id": "Animal Classification/0107", + "Question Type": "Single Choice", + "Text": "Identifying animal species from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format of (xmin, ymin,xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 448x448.Bounding box:[<863><115><868><121>] ", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Animal Classification", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) penguin", + "(B) polar bear", + "(C) seal", + "(D) seagull", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x8064.y5376.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Geographical_Location_Inference_of_Plant_Species.json b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Geographical_Location_Inference_of_Plant_Species.json new file mode 100644 index 0000000000000000000000000000000000000000..9db35aa732ec42a3fc0db046a637e1dcbdab5f3a --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Geographical_Location_Inference_of_Plant_Species.json @@ -0,0 +1,10502 @@ +[ + { + "Question_id": "Geographical Location Inference of Plant Species/0000", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b9d22b53c691c00060c0262_1437.tif" + ], + "Text": "The species shown in the figure is Balkan mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 24.7171611786° N, Longitude: 42.1180534363° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0001", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f711df61d951a00058695d8_1976.tif" + ], + "Text": "The species shown in the figure is Taiwan subtropical evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.666595459° N, Longitude: 24.0620479584° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0002", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ff330589ef28c00068659a9_4026.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 56.3586158752° N, Longitude: 55.4096260071° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0003", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae7f5fa0b093000130affcc_983.tif" + ], + "Text": "The species shown in the figure is Granitic Seychelles forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 55.5148620605° N, Longitude: -4.7352485657° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0004", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a276972bac48e5b1c561a15_3117.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 120.0134735107° N, Longitude: 30.2739868164° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0005", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5de7f5ea2290870005e59995_4923.tif" + ], + "Text": "The species shown in the figure is Serra do Mar coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -43.4827880859° S, Longitude: -22.497882843° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0006", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e25ec6e36067e0005c2752d_3412.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 37.1979904175° N, Longitude: -17.4048252106° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0007", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7177d91d951a00058695e8_1528.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 14.8160142899° N, Longitude: 45.6928482056° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0008", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a219_3050.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 169.3077392578° N, Longitude: -19.4393367767° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0009", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5de7f5ea2290870005e59995_4933.tif" + ], + "Text": "The species shown in the figure is Serra do Mar coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -43.4864654541° S, Longitude: -22.4961738586° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0010", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ca97be23bc29600053c1623_2429.tif" + ], + "Text": "The species shown in the figure is Appalachian-Blue Ridge forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -83.2695388794° S, Longitude: 36.4120445251° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0011", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e4fb2fb24710000056a515c_2255.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -58.7253570557° S, Longitude: -9.6718072891° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0012", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d00073d8276e4000507811b_3036.tif" + ], + "Text": "The species shown in the figure is Taiheiyo evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 139.1053771973° N, Longitude: 35.9950370789° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0013", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f3b3441df88ab000761cb39_1811.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: -56.1577911377° S, Longitude: -15.4558048248° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0014", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d9afef50ca8d70007c491f8_2986.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.6813354492° N, Longitude: -4.875164032° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0015", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607bd156bfb5350008e66597_3654.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -93.9063034058° S, Longitude: 45.1765937805° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0016", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aeff_3580.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 36.8356742859° N, Longitude: 56.0429420471° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0017", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607af86cbfb5350008e66588_3401.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 15.2841291428° N, Longitude: 52.9188613892° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0018", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a579_4657.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 35.0759887695° N, Longitude: 54.6785964966° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0019", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9a3d6412ef7220a51f_3623.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -74.0243835449° S, Longitude: 41.9321327209° E", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0020", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fba7574f867fd0007e9774a_2475.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: -68.0404510498° S, Longitude: -16.6220302582° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0021", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bfdbd20351e730005346227_1395.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -80.6742477417° S, Longitude: 35.032371521° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0022", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a514dfc5a9ef7cb5ddabac1_1588.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -0.8653980494° S, Longitude: 51.280128479° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0023", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bcdcf3ab9e5f20005f7da40_423.tif" + ], + "Text": "The species shown in the figure is Western Guinean lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -10.7908468246° S, Longitude: 6.3305253983° E", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0024", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10408a2b6a08001185f427_127.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.3427200317° N, Longitude: -6.0489044189° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0025", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3ea615e7ff3f00054889d4_955.tif" + ], + "Text": "The species shown in the figure is Irrawaddy moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 96.1999130249° N, Longitude: 21.5949802399° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0026", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ff5a55038bfed0005ea56fb_3289.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 24.0179901123° N, Longitude: 49.8392601013° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0027", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e8b4a54a652050007863a89_4309.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 119.8526611328° N, Longitude: -0.9619910121° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0028", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60606bd0eeae3c000693003f_1170.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -55.3032836914° S, Longitude: -16.0775909424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0029", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be93d6412ef7220c4a6_2765.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -119.2404708862° S, Longitude: 37.9379234314° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0030", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7a37029636900059d6491_2078.tif" + ], + "Text": "The species shown in the figure is Upper Gangetic Plains moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 82.9868850708° N, Longitude: 25.260093689° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0031", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dded5bc0140b80006d2e565_339.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -51.5982093811° S, Longitude: -15.6351556778° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0032", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bf6676cad75b80007102067_324.tif" + ], + "Text": "The species shown in the figure is Western Java rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 110.3793487549° N, Longitude: -7.7427043915° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0033", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e3df93f3cc4da00055f53ff_687.tif" + ], + "Text": "The species shown in the figure is Cantabrian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -8.2911338806° S, Longitude: 41.4456138611° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0034", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aee9_3393.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -89.3674163818° S, Longitude: 43.0906333923° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0035", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d15131557915d0007f8d266_3747.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 12.5051994324° N, Longitude: 55.7749977112° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0036", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d4efc4c317dd900055f7412_4538.tif" + ], + "Text": "The species shown in the figure is Eastern Great Lakes lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -73.9298171997° S, Longitude: 42.7378234863° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0037", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e17cc7f76e4f20005c1b85c_3046.tif" + ], + "Text": "The species shown in the figure is Willamette Valley forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -122.9054489136° S, Longitude: 45.4908256531° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0038", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd0f6dda7dadc0006433b5b_4711.tif" + ], + "Text": "The species shown in the figure is Central African mangroves. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 3.3922128677° N, Longitude: 6.4924869537° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0039", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d96feee0a75b70006703919_4982.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(D) Latitude: 39.6813354492° N, Longitude: -4.8585553169° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0040", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209ebb_4865.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -73.765586853° S, Longitude: 18.2223300934° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0041", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fb52130d89ab70006abca33_3.tif" + ], + "Text": "The species shown in the figure is Zambezian and Mopane woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 28.8450603485° N, Longitude: -15.9518413544° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0042", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aee9_3582.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -89.37109375° S, Longitude: 43.0933303833° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0043", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a135953bac48e5b1c24c537_3058.tif" + ], + "Text": "The species shown in the figure is Puget lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -122.3932113647° S, Longitude: 47.6670761108° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0044", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bac9a13692f850005383f6e_1885.tif" + ], + "Text": "The species shown in the figure is Sumatran lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 98.2506103516° N, Longitude: 2.1139810085° E", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0045", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aed6_3381.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -88.2472381592° S, Longitude: 44.2836914062° E", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0046", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b963d6412ef7220a3d7_3224.tif" + ], + "Text": "The species shown in the figure is Central American pine-oak forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -90.6055984497° S, Longitude: 14.6004953384° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0047", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3adc00b093000130affa6_749.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.2582702637° N, Longitude: -6.22651577° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0048", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6112fad7ac1a340005a1ccf4_287.tif" + ], + "Text": "The species shown in the figure is West Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -1.0489150286° S, Longitude: 9.6559038162° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0049", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1bd8e593e1130005fc0e92_760.tif" + ], + "Text": "The species shown in the figure is Bahia coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -39.4792480469° S, Longitude: -13.9689998627° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0050", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3cb31865775c0007e79448_1580.tif" + ], + "Text": "The species shown in the figure is Petén-Veracruz moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -88.421295166° S, Longitude: 17.5710754395° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0051", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_2641.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.2255477905° N, Longitude: -6.0075955391° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0052", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209e91_2469.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -73.7545471191° S, Longitude: 18.2205715179° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0053", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a14b831bac48e5b1c281943_3652.tif" + ], + "Text": "The species shown in the figure is Ucayali moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -76.4392776489° S, Longitude: -6.3851752281° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0054", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b003ade2b6a08001185f13e_333.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3408622742° N, Longitude: -6.0162410736° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0055", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fd3d253b33bf80007f3f821_4666.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -93.3497390747° S, Longitude: 44.9732933044° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0056", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cf43896c25f7e00059bac5f_7.tif" + ], + "Text": "The species shown in the figure is North Island temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 175.3367156982° N, Longitude: -40.2215118408° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0057", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1cc58493e1130005fc0eb0_3538.tif" + ], + "Text": "The species shown in the figure is Bahia coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -38.9130058289° S, Longitude: -12.7452726364° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0058", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3923e0b093000130aff38_1999.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.4141654968° N, Longitude: -6.4090161324° W", + "(B) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0059", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aefa_2715.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 125.0142745972° N, Longitude: -8.2804584503° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0060", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a2d4387bac48e5b1c64facc_4579.tif" + ], + "Text": "The species shown in the figure is Alps conifer and mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 5.6509981155° N, Longitude: 45.2361793518° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0061", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c892a92225fc20007ab4e31_3373.tif" + ], + "Text": "The species shown in the figure is Celtic broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -6.3398571014° S, Longitude: 54.1800804138° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0062", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639bf5ec014e000618876d_322.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -62.4942550659° S, Longitude: -12.11921978° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0063", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7f8f729636900059d6498_3082.tif" + ], + "Text": "The species shown in the figure is Magdalena Valley montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -74.0431518555° S, Longitude: 4.7062296867° E", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0064", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607af86cbfb5350008e66588_3937.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 15.2859687805° N, Longitude: 52.9177474976° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0065", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60d72a025e4fd500077d46e7_2064.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 124.322265625° N, Longitude: 13.9559278488° E", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0066", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5eda8d6cc692f1000793f1df_691.tif" + ], + "Text": "The species shown in the figure is Sonoran desert. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -111.1443557739° S, Longitude: 32.4014472961° E", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0067", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b903d6412ef7220a03e_3669.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -73.9669647217° S, Longitude: 41.933380127° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0068", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7f8f729636900059d6498_1584.tif" + ], + "Text": "The species shown in the figure is Magdalena Valley montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: -74.0394744873° S, Longitude: 4.7062296867° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0069", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7f8f729636900059d6498_2771.tif" + ], + "Text": "The species shown in the figure is Magdalena Valley montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -74.0431518555° S, Longitude: 4.7025380135° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0070", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a237ea5bac48e5b1c4bf531_1650.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 119.9950866699° N, Longitude: 30.2919902802° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0071", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bbd459c3baffb0005fe9ba1_4149.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -84.1197280884° S, Longitude: 33.6630020142° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0072", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59fc9657bac48e5b1ced2a2f_4095.tif" + ], + "Text": "The species shown in the figure is Uatuma-Trombetas moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: -60.0943336487° S, Longitude: -3.0214521885° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0073", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b8fc8f88752bd000830170d_1381.tif" + ], + "Text": "The species shown in the figure is Pontic steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 35.0812606812° N, Longitude: 48.4468231201° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0074", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a70b6785a9ef7cb5d2bf31e_4068.tif" + ], + "Text": "The species shown in the figure is Valdivian temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -71.1842041016° S, Longitude: -41.1002006531° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0075", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d6a17892103c90007707fa9_271.tif" + ], + "Text": "The species shown in the figure is Sumatran lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 100.3994216919° N, Longitude: -1.2188192606° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0076", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639bf5ec014e000618876d_1113.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -62.4942550659° S, Longitude: -12.1174097061° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0077", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ca0936a9bc6570005e10aa2_2643.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 23.483165741° N, Longitude: 56.7647819519° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0078", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_245.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.2273902893° N, Longitude: -5.9965443611° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0079", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b793d6412ef722094d2_4106.tif" + ], + "Text": "The species shown in the figure is Mindanao-Eastern Visayas rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 125.4745635986° N, Longitude: 12.0339193344° E", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0080", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a135953bac48e5b1c24c537_1648.tif" + ], + "Text": "The species shown in the figure is Puget lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -122.4024124146° S, Longitude: 47.6658363342° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0081", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7f8f729636900059d6498_2563.tif" + ], + "Text": "The species shown in the figure is Magdalena Valley montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -74.0376281738° S, Longitude: 4.7062296867° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0082", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8f3d6412ef72209fd4_4355.tif" + ], + "Text": "The species shown in the figure is Hispaniolan dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -72.2995071411° S, Longitude: 18.5558223724° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0083", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a5a21a25a9ef7cb5df1937e_4154.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 45.88489151° N, Longitude: 41.9337272644° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0084", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b1096542b6a08001185f4c9_3784.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3593635559° N, Longitude: -6.1993231773° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0085", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bc119b7c7e1cf0008e45e25_1276.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 38.3105049133° N, Longitude: 55.5361709595° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0086", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a219_4110.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 169.3059082031° N, Longitude: -19.4428272247° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0087", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b793d6412ef722094d2_2105.tif" + ], + "Text": "The species shown in the figure is Mindanao-Eastern Visayas rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 125.4782409668° N, Longitude: 12.0339193344° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0088", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b703d6412ef72208f5a_4492.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 121.1580886841° N, Longitude: 14.0517168045° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0089", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a8213345a9ef7cb5d5973bb_2573.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -174.9857330322° S, Longitude: -21.1161613464° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0090", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3ac1c0b093000130aff8f_3124.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 39.2798423767° N, Longitude: -6.1740775108° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0091", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbdd9ef1f79c3000788a403_4275.tif" + ], + "Text": "The species shown in the figure is South Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -116.1237335205° S, Longitude: 44.0765342712° E", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0092", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8f3d6412ef72209fd4_4783.tif" + ], + "Text": "The species shown in the figure is Hispaniolan dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -72.2995071411° S, Longitude: 18.5575771332° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0093", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60c44a21338cc80005cfdd0b_400.tif" + ], + "Text": "The species shown in the figure is Tigris-Euphrates alluvial salt marsh. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 47.4198112488° N, Longitude: 31.0089416504° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0094", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d87983a0e02d300050aa10f_3583.tif" + ], + "Text": "The species shown in the figure is Central U.S. hardwood forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -85.9059524536° S, Longitude: 37.0159378052° E", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0095", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d8bd155a62db1000612178d_360.tif" + ], + "Text": "The species shown in the figure is Chilean matorral. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -72.6518173218° S, Longitude: -38.7546310425° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0096", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae7f5fa0b093000130affcc_726.tif" + ], + "Text": "The species shown in the figure is Granitic Seychelles forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 55.5167007446° N, Longitude: -4.744477272° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0097", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60b0cccea9600f0008458140_2308.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 23.986492157° N, Longitude: 49.8135032654° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0098", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10408a2b6a08001185f427_1712.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.3519172668° N, Longitude: -6.0599541664° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0099", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e8b4a54a652050007863a89_4252.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 119.8526611328° N, Longitude: -0.9656947851° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0100", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be63d6412ef7220c37a_2204.tif" + ], + "Text": "The species shown in the figure is Fiji tropical dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 177.5288085938° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0101", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d0511a873de290005853a93_4756.tif" + ], + "Text": "The species shown in the figure is Central Indochina dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 98.8847808838° N, Longitude: 18.5918159485° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0102", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a597fb25a9ef7cb5df003cf_3769.tif" + ], + "Text": "The species shown in the figure is Richmond temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 172.995300293° N, Longitude: -41.2435836792° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0103", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60c1b7e8c3b42f000788d30a_953.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 37.4722366333° N, Longitude: 56.9476928711° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0104", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61cb8771081c15000543455a_1665.tif" + ], + "Text": "The species shown in the figure is Po Basin mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 11.9007501602° N, Longitude: 44.3068161011° E", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0105", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c97e2fb23189800059f4d41_3074.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 1.067990303° N, Longitude: 52.3638572693° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0106", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d9afef50ca8d70007c491f8_1498.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(D) Latitude: 39.6739768982° N, Longitude: -4.865937233° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0107", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b953d6412ef7220a31c_3831.tif" + ], + "Text": "The species shown in the figure is Mindanao-Eastern Visayas rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 124.8367996216° N, Longitude: 11.2355899811° E", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0108", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ff330589ef28c00068659a9_2956.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 56.360458374° N, Longitude: 55.40858078° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0109", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e2566772554740005d5c9e8_4212.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 37.2016677856° N, Longitude: -17.4083576202° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0110", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbfc070d0c51c0005eb1e02_2964.tif" + ], + "Text": "The species shown in the figure is Eastern Himalayan broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 85.2974090576° N, Longitude: 27.7092914581° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0111", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d973639e2b1f300057cb3a8_4162.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 39.8004989624° N, Longitude: -5.2589697838° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0112", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a16788cbac48e5b1c2c47bf_1269.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 120.0003509521° N, Longitude: 30.2814235687° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0113", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c6522c346bdea00053984d1_3261.tif" + ], + "Text": "The species shown in the figure is Granitic Seychelles forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 55.5308761597° N, Longitude: -4.69190979° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0114", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fa016bbd3a8ab0007ea6a66_392.tif" + ], + "Text": "The species shown in the figure is Central Andean dry puna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -66.1436538696° S, Longitude: -21.1709518433° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0115", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b913d6412ef7220a0d1_2416.tif" + ], + "Text": "The species shown in the figure is Northern California coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -122.3439712524° S, Longitude: 37.4933433533° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0116", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cb64e020a3a5c0005ff12ff_642.tif" + ], + "Text": "The species shown in the figure is Central Andean puna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -65.618309021° S, Longitude: -17.6234531403° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0117", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5de55a69b3b5ce0006c2d960_4273.tif" + ], + "Text": "The species shown in the figure is Southern Great Lakes forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -83.8850784302° S, Longitude: 41.4522018433° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0118", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607af86cbfb5350008e66588_2914.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 15.2804498672° N, Longitude: 52.9177474976° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0119", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd0f6dda7dadc0006433b5b_4896.tif" + ], + "Text": "The species shown in the figure is Central African mangroves. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 3.3903729916° N, Longitude: 6.4943270683° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0120", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a2325625820c0005e458d4_181.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 24.0241832733° N, Longitude: 49.8158874512° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0121", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bf4e3addc18930005c2b4dc_1746.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 120.1791610718° N, Longitude: -3.8815493584° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0122", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fff0f93c46165000547372d_22.tif" + ], + "Text": "The species shown in the figure is Gulf of Oman desert and semi-desert. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 55.3927497864° N, Longitude: 25.1301574707° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0123", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dbb240d05580100062e0210_3726.tif" + ], + "Text": "The species shown in the figure is Mato Grosso seasonal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -51.5789451599° S, Longitude: -10.6633501053° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0124", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a429463bac48e5b1c9b41b5_1292.tif" + ], + "Text": "The species shown in the figure is Lower Gangetic Plains moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 92.2025909424° N, Longitude: 21.0842838287° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0125", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e28a0d12329e800051134a5_10.tif" + ], + "Text": "The species shown in the figure is Araucaria moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -49.8149032593° S, Longitude: -24.1489295959° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0126", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e068f3605e6590005c2f71a_2137.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -72.1787796021° S, Longitude: 41.9170608521° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0127", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b1041cb2b6a08001185f42f_2844.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.261390686° N, Longitude: -6.069211483° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0128", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209e91_3603.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: -73.7545471191° S, Longitude: 18.2170562744° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0129", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e649d26e6c4ec000688ffab_4936.tif" + ], + "Text": "The species shown in the figure is Nihonkai montane deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 138.434677124° N, Longitude: 36.4605979919° E", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0130", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/618ebf6d502455000734581c_555.tif" + ], + "Text": "The species shown in the figure is Crimean Submediterranean forest complex. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 34.4230232239° N, Longitude: 44.6828536987° E", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0131", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d9afef50ca8d70007c491f8_2250.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(B) Latitude: 39.6739768982° N, Longitude: -4.8677825928° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0132", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b953d6412ef7220a366_4888.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 42.4102668762° N, Longitude: 43.0854682922° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0133", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cd1de27e885bf000637c38e_3206.tif" + ], + "Text": "The species shown in the figure is Southeastern conifer forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -85.3777542114° S, Longitude: 29.9164733887° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0134", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6168ac60ea4de60007d530eb_4867.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -84.5850753784° S, Longitude: 33.5440826416° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0135", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e2566772554740005d5c9e8_4622.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 37.1961479187° N, Longitude: -17.4012928009° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0136", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a276972bac48e5b1c561a15_4030.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.0116348267° N, Longitude: 30.2803726196° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0137", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d96feee0a75b70006703919_4805.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(B) Latitude: 39.6831741333° N, Longitude: -4.8604011536° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0138", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b913d6412ef7220a0d1_3743.tif" + ], + "Text": "The species shown in the figure is Northern California coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -122.3421325684° S, Longitude: 37.4918785095° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0139", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c13db9205f40a0007517d15_1790.tif" + ], + "Text": "The species shown in the figure is Atlantic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 4.5942106247° N, Longitude: 51.8848648071° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0140", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5abb761965bd8f00110f3e4c_2038.tif" + ], + "Text": "The species shown in the figure is Atlantic coastal pine barrens. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -70.5729598999° S, Longitude: 41.5831222534° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0141", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639ceaec014e0006188772_2200.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -62.4860038757° S, Longitude: -12.0156965256° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0142", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3cb31865775c0007e79448_4098.tif" + ], + "Text": "The species shown in the figure is Petén-Veracruz moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -88.4157791138° S, Longitude: 17.5657806396° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0143", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a219_3184.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 169.3077392578° N, Longitude: -19.4445724487° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0144", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae4afd70b093000130affb1_2386.tif" + ], + "Text": "The species shown in the figure is Eastern Guinean forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -1.8932121992° S, Longitude: 5.9732842445° E", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0145", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e1193a95f5069000738f16a_4912.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 33.6421470642° N, Longitude: 49.3176612854° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0146", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f75542e61151700054968d1_1920.tif" + ], + "Text": "The species shown in the figure is North Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -116.7850646973° S, Longitude: 51.0113754272° E", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0147", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbdd9ef1f79c3000788a403_4664.tif" + ], + "Text": "The species shown in the figure is South Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: -116.1218948364° S, Longitude: 44.0765342712° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0148", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a14b831bac48e5b1c281943_3201.tif" + ], + "Text": "The species shown in the figure is Ucayali moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -76.4355926514° S, Longitude: -6.3906965256° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0149", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f53b99404c2a50006bd6a05_1304.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 6.6496219635° N, Longitude: 46.814617157° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0150", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bbd459c3baffb0005fe9ba1_2592.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -84.1197280884° S, Longitude: 33.6614646912° E", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0151", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e9d2bc9054194000589a41a_3484.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 17.5827636719° N, Longitude: 59.721370697° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0152", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be83d6412ef7220c45c_2144.tif" + ], + "Text": "The species shown in the figure is Timor and Wetar deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 124.871383667° N, Longitude: -9.319483757° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0153", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e5bce9680995300058c6037_1600.tif" + ], + "Text": "The species shown in the figure is Po Basin mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 7.5904994011° N, Longitude: 45.064491272° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0154", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3adc00b093000130affa6_1176.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 39.2325134277° N, Longitude: -6.2209925652° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0155", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be83d6412ef7220c45c_3598.tif" + ], + "Text": "The species shown in the figure is Timor and Wetar deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 124.8603515625° N, Longitude: -9.323138237° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0156", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209e91_2303.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -73.7545471191° S, Longitude: 18.21002388° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0157", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a219_2462.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 169.3077392578° N, Longitude: -19.4410820007° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0158", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb23d6412ef7220af16_2435.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.5140686035° N, Longitude: -8.6033353806° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0159", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60cc7f03eade0f00079b5848_3667.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 14.9562826157° N, Longitude: 52.6623802185° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0160", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59fc9657bac48e5b1ced2a2f_2615.tif" + ], + "Text": "The species shown in the figure is Uatuma-Trombetas moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -60.0943336487° S, Longitude: -3.0196025372° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0161", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7a37029636900059d6491_4052.tif" + ], + "Text": "The species shown in the figure is Upper Gangetic Plains moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 82.9832077026° N, Longitude: 25.2584209442° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0162", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6112fad7ac1a340005a1ccf4_1295.tif" + ], + "Text": "The species shown in the figure is West Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -1.0544342995° S, Longitude: 9.6595544815° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0163", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b0040ca2b6a08001185f14c_452.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 39.2723770142° N, Longitude: -5.9404006004° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0164", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b003ade2b6a08001185f13e_302.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.3629417419° N, Longitude: -6.040184021° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0165", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dde8d370140b80006d2e547_1241.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -49.2620849609° S, Longitude: -15.8428039551° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0166", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a808bed5a9ef7cb5d552d69_325.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 32.9533576965° N, Longitude: -26.072013855° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0167", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10356c2b6a08001185f417_2441.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.2779350281° N, Longitude: -6.0218148232° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0168", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bd13ced007b5600073957e8_2556.tif" + ], + "Text": "The species shown in the figure is East African montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 34.3952713013° N, Longitude: 1.0035223961° E", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0169", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bc119b7c7e1cf0008e45e25_2751.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 38.3233833313° N, Longitude: 55.5267791748° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0170", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d9afef50ca8d70007c491f8_1941.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(B) Latitude: 39.690536499° N, Longitude: -4.8733186722° W", + "(C) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0171", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_1065.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 39.3376426697° N, Longitude: -5.9619998932° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0172", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209e91_2273.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -73.7471923828° S, Longitude: 18.215297699° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0173", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e72ba9b133f1a000511bead_1539.tif" + ], + "Text": "The species shown in the figure is Northern Anatolian conifer and deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 36.4668807983° N, Longitude: 40.326171875° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0174", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae378c00b093000130afe28_2107.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2526931763° N, Longitude: -6.0889964104° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0175", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/600fce6e55481e0005e312a8_2264.tif" + ], + "Text": "The species shown in the figure is Sundaland heath forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 116.9504776001° N, Longitude: -1.2026996613° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0176", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fba7574f867fd0007e9774a_3290.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -68.0422897339° S, Longitude: -16.6255779266° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0177", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10356c2b6a08001185f417_2315.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.2742576599° N, Longitude: -6.019973278° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0178", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a248_2085.tif" + ], + "Text": "The species shown in the figure is Greater Negros-Panay rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 122.0850906372° N, Longitude: 11.4049196243° E", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0179", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f059147ce2c9900068d83ee_824.tif" + ], + "Text": "The species shown in the figure is Iberian sclerophyllous and semi-deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -1.7484699488° S, Longitude: 38.3565368652° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0180", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209ebb_4638.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -73.7674255371° S, Longitude: 18.2135391235° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0181", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e92a43ec6bbac0005e30fd2_3465.tif" + ], + "Text": "The species shown in the figure is Nihonkai montane deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 139.044052124° N, Longitude: 37.541519165° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0182", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae378c00b093000130afe28_2734.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2526931763° N, Longitude: -6.0761051178° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0183", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d629d8d1b36840007184206_1897.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 48.3331947327° N, Longitude: 54.2742080688° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0184", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ca75114b21ec90007944d7d_844.tif" + ], + "Text": "The species shown in the figure is East Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 31.27161026° N, Longitude: 3.256059885° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0185", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b973d6412ef7220a418_3609.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -120.0955047607° S, Longitude: 38.6990394592° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0186", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b1096542b6a08001185f4c9_3496.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.36120224° N, Longitude: -6.1974821091° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0187", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e17cc7f76e4f20005c1b85c_4117.tif" + ], + "Text": "The species shown in the figure is Willamette Valley forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: -122.9036102295° S, Longitude: 45.4921188354° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0188", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6108af51343da30006976e20_1196.tif" + ], + "Text": "The species shown in the figure is Greater Negros-Panay rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 123.2367095947° N, Longitude: 12.0570383072° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0189", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e72ba9b133f1a000511bead_3172.tif" + ], + "Text": "The species shown in the figure is Northern Anatolian conifer and deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 36.4760818481° N, Longitude: 40.327583313° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0190", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639bf5ec014e000618876d_851.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -62.4942550659° S, Longitude: -12.1210298538° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0191", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61951f134cf5080007593269_191.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -2.2899463177° S, Longitude: 51.3623886108° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0192", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5aea3d3b8153990013b938e8_2858.tif" + ], + "Text": "The species shown in the figure is Bajío dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -101.2242202759° S, Longitude: 19.6489677429° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0193", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b6473dd40e11005cf16cc89_3433.tif" + ], + "Text": "The species shown in the figure is Crimean Submediterranean forest complex. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 34.4223937988° N, Longitude: 44.6815795898° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0194", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3923e0b093000130aff38_3866.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.4160041809° N, Longitude: -6.4034948349° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0195", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d87983a0e02d300050aa10f_3049.tif" + ], + "Text": "The species shown in the figure is Central U.S. hardwood forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -85.9096298218° S, Longitude: 37.017414093° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0196", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b973d6412ef7220a415_4876.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -119.9172363281° S, Longitude: 39.1104431152° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0197", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8f3d6412ef72209fd4_4926.tif" + ], + "Text": "The species shown in the figure is Hispaniolan dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -72.3013458252° S, Longitude: 18.5540676117° E", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0198", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dbb240d05580100062e0210_3374.tif" + ], + "Text": "The species shown in the figure is Mato Grosso seasonal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -51.573425293° S, Longitude: -10.6651697159° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0199", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b943d6412ef7220a2af_1634.tif" + ], + "Text": "The species shown in the figure is Sao Tome, Principe and Annobon moist lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 6.7363710403° N, Longitude: 0.3411012292° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0200", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a248_1778.tif" + ], + "Text": "The species shown in the figure is Greater Negros-Panay rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 122.0777359009° N, Longitude: 11.4103651047° E", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0201", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aed6_1753.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -88.2619552612° S, Longitude: 44.2823677063° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0202", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_1036.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2255477905° N, Longitude: -5.9891767502° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0203", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c466c6c437ee1000616311f_1575.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 168.3070220947° N, Longitude: -16.3203716278° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0204", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_1892.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.3155670166° N, Longitude: -5.9877872467° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0205", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d706fa55583d40006c15788_5024.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -81.7010345459° S, Longitude: 35.7189254761° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0206", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3a7f00b093000130aff66_1724.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3575057983° N, Longitude: -6.1611390114° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0207", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd0f370a7dadc0006433b56_2559.tif" + ], + "Text": "The species shown in the figure is Nigerian lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 3.393638134° N, Longitude: 6.5009417534° E", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0208", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_310.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2089920044° N, Longitude: -5.9965443611° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0209", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f628b5f9d06cc0006243274_2928.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 122.8378753662° N, Longitude: 0.8110579252° E", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0210", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a7e134e5a9ef7cb5d4ef05f_3752.tif" + ], + "Text": "The species shown in the figure is Maputaland coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 33.5434799194° N, Longitude: -24.7450122833° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0211", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bce3d12b9e5f20005f7da4d_4268.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 7.693441391° N, Longitude: 50.3722343445° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0212", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c5cde10e84ca0000599359f_1247.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -121.927986145° S, Longitude: 36.5360298157° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0213", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a5c13545a9ef7cb5df674f1_776.tif" + ], + "Text": "The species shown in the figure is North Island temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 174.9217681885° N, Longitude: -41.1992263794° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0214", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae31f3c0b093000130afda4_3361.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 39.2884712219° N, Longitude: -6.0149226189° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0215", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae378c00b093000130afe28_3273.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.2526931763° N, Longitude: -6.0926795006° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0216", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1cc58493e1130005fc0eb0_2645.tif" + ], + "Text": "The species shown in the figure is Bahia coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -38.9130058289° S, Longitude: -12.748884201° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0217", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9a3d6412ef7220a51f_3436.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -74.0188674927° S, Longitude: 41.9307594299° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0218", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b953d6412ef7220a34d_449.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 42.396522522° N, Longitude: 43.0824623108° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0219", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7a37029636900059d6491_3606.tif" + ], + "Text": "The species shown in the figure is Upper Gangetic Plains moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 82.9942474365° N, Longitude: 25.260093689° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0220", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_3207.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.3174057007° N, Longitude: -5.9841036797° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0221", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b993d6412ef7220a4ad_4021.tif" + ], + "Text": "The species shown in the figure is Taiwan subtropical evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 121.0742263794° N, Longitude: 24.7583236694° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0222", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c8b6813a8ac330005a58af6_4795.tif" + ], + "Text": "The species shown in the figure is Celtic broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -5.7300372124° S, Longitude: 54.5450439453° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0223", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60e988c5719f470008094136_216.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 26.4279384613° N, Longitude: 54.1343002319° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0224", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d29ec177a18fd0005e2978e_531.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 121.1397171021° N, Longitude: 16.9355430603° E", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0225", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5eada7de3295f300072a6d80_689.tif" + ], + "Text": "The species shown in the figure is Iberian sclerophyllous and semi-deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -0.1321233511° S, Longitude: 40.8811187744° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0226", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b518afc4bda9e648eedbd9d_2598.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 120.5292282104° N, Longitude: 14.9885149002° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0227", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b003ade2b6a08001185f13e_533.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 39.3408622742° N, Longitude: -6.0180830956° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0228", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ff330589ef28c00068659a9_3410.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 56.3567771912° N, Longitude: 55.4096260071° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0229", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e43dbd3d9a1b700063006df_79.tif" + ], + "Text": "The species shown in the figure is Brigalow tropical savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 149.8063812256° N, Longitude: -25.6519794464° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0230", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b863d6412ef72209aff_1493.tif" + ], + "Text": "The species shown in the figure is Western Great Lakes forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -92.0015945435° S, Longitude: 46.8386421204° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0231", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bba1c4f9ed15b0006d24f3b_2029.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 39.0092544556° N, Longitude: 55.8163223267° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0232", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10238f2b6a08001185f398_2465.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 39.3031616211° N, Longitude: -5.9440693855° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0233", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d96feee0a75b70006703919_4707.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(D) Latitude: 39.6868553162° N, Longitude: -4.865937233° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0234", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7177d91d951a00058695e8_1974.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 14.8068161011° N, Longitude: 45.6928482056° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0235", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10428f2b6a08001185f441_2451.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.2237205505° N, Longitude: -6.0365748405° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0236", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5da4eb2dcac1190007698b1b_4853.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -64.9450683594° S, Longitude: -20.8239364624° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0237", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e4fbd3024710000056a516f_4022.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -58.313369751° S, Longitude: -10.9738998413° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0238", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f2fb5190d59fe00057c32ac_4535.tif" + ], + "Text": "The species shown in the figure is Himalayan subtropical broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 86.2503356934° N, Longitude: 27.0047187805° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0239", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b3622402b6a08001185f8d8_138.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 9.079955101° N, Longitude: 48.5204277039° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0240", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a9980b15a9ef7cb5d982284_4177.tif" + ], + "Text": "The species shown in the figure is Tongan tropical moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -175.2900543213° S, Longitude: -21.1549530029° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0241", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b963d6412ef7220a3dd_3501.tif" + ], + "Text": "The species shown in the figure is Veracruz moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: -98.7047195435° S, Longitude: 21.4414710999° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0242", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b911275a0d7280005fab35d_4120.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 6.3574385643° N, Longitude: 49.5612792969° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0243", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad9eb6a91b5310010e0d56f_1156.tif" + ], + "Text": "The species shown in the figure is Balkan mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 24.761177063° N, Longitude: 42.148223877° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0244", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a25ae87bac48e5b1c51946f_699.tif" + ], + "Text": "The species shown in the figure is West Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 2.1370947361° N, Longitude: 13.4723405838° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0245", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a276972bac48e5b1c561a15_3800.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.0171508789° N, Longitude: 30.2739868164° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0246", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cb0ece9fa020e0006eb43d4_1209.tif" + ], + "Text": "The species shown in the figure is Chilean matorral. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: -70.3238677979° S, Longitude: -27.3519363403° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0247", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d87983a0e02d300050aa10f_2133.tif" + ], + "Text": "The species shown in the figure is Central U.S. hardwood forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -85.9077911377° S, Longitude: 37.0144615173° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0248", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bd13ced007b5600073957e8_2711.tif" + ], + "Text": "The species shown in the figure is East African montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 34.4026298523° N, Longitude: 1.0053743124° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0249", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fe3cf0b5f36590007d9f04f_4081.tif" + ], + "Text": "The species shown in the figure is Jalisco dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -104.2471923828° S, Longitude: 18.9995346069° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0250", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d385458a93b8e000752d2cc_3359.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 7.395157814° N, Longitude: 50.4573898315° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0251", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b853d6412ef72209ad9_2699.tif" + ], + "Text": "The species shown in the figure is Ecuadorian dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -80.7178497314° S, Longitude: -0.9552943707° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0252", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10356c2b6a08001185f417_1831.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.2742576599° N, Longitude: -6.0218148232° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0253", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad9eb6a91b5310010e0d56f_1212.tif" + ], + "Text": "The species shown in the figure is Balkan mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 24.7593364716° N, Longitude: 42.1468544006° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0254", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10238f2b6a08001185f398_3656.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 39.301322937° N, Longitude: -5.9385433197° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0255", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60c44a21338cc80005cfdd0b_634.tif" + ], + "Text": "The species shown in the figure is Tigris-Euphrates alluvial salt marsh. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 47.430847168° N, Longitude: 31.0089416504° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0256", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c4c03a120749e0007653157_748.tif" + ], + "Text": "The species shown in the figure is Mount Lofty woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 138.5063781738° N, Longitude: -34.8737831116° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0257", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7486da6115170005496874_58.tif" + ], + "Text": "The species shown in the figure is Southern Great Lakes forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -86.1352844238° S, Longitude: 40.4193611145° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0258", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3a7f00b093000130aff66_3144.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3593482971° N, Longitude: -6.157456398° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0259", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3ac1c0b093000130aff8f_1750.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 39.2632827759° N, Longitude: -6.1740775108° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0260", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b933d6412ef7220a205_1535.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -120.1960220337° S, Longitude: 39.1927146912° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0261", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_1261.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.2292289734° N, Longitude: -6.0075955391° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0262", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_296.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.3321228027° N, Longitude: -5.9822616577° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0263", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_3333.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.2255477905° N, Longitude: -5.994702816° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0264", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6112fad7ac1a340005a1ccf4_572.tif" + ], + "Text": "The species shown in the figure is West Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -1.0525945425° S, Longitude: 9.6577291489° E", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0265", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b973d6412ef7220a418_3972.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -120.0973510742° S, Longitude: 38.6990394592° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0266", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f75542e61151700054968d1_4132.tif" + ], + "Text": "The species shown in the figure is North Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -116.7850646973° S, Longitude: 51.0102157593° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0267", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1cc58493e1130005fc0eb0_1594.tif" + ], + "Text": "The species shown in the figure is Bahia coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -38.9185256958° S, Longitude: -12.748884201° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0268", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60a7f8f729636900059d6498_3483.tif" + ], + "Text": "The species shown in the figure is Magdalena Valley montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -74.0449905396° S, Longitude: 4.7043838501° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0269", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c892a92225fc20007ab4e31_1884.tif" + ], + "Text": "The species shown in the figure is Celtic broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -6.3380174637° S, Longitude: 54.1714477539° E", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0270", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6037bafb0c174800070d60da_4201.tif" + ], + "Text": "The species shown in the figure is Atlantic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 4.407995224° N, Longitude: 52.2178688049° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0271", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7177d91d951a00058695e8_3918.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 14.8178539276° N, Longitude: 45.6902694702° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0272", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ccf3cee28c3b90006c145ed_3628.tif" + ], + "Text": "The species shown in the figure is North Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -118.9697189331° S, Longitude: 52.6213645935° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0273", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639ceaec014e0006188772_3421.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -62.4823226929° S, Longitude: -12.0030193329° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0274", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f192faa47493f000549bf78_614.tif" + ], + "Text": "The species shown in the figure is Southern Atlantic mangroves. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -48.5212097168° S, Longitude: -27.6018695831° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0275", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f8de1dca11f71000673ec58_1768.tif" + ], + "Text": "The species shown in the figure is Western Siberian hemiboreal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 66.5351715088° N, Longitude: 56.5073928833° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0276", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e2566772554740005d5c9e8_4627.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 37.1961479187° N, Longitude: -17.3995265961° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0277", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3adc00b093000130affa6_2663.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.2564277649° N, Longitude: -6.2062635422° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0278", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5de1091c0c04590006d335b3_3551.tif" + ], + "Text": "The species shown in the figure is Cardamom Mountains rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 102.5627441406° N, Longitude: 12.8611726761° E", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0279", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a70b6785a9ef7cb5d2bf31e_1487.tif" + ], + "Text": "The species shown in the figure is Valdivian temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -71.1823577881° S, Longitude: -41.0988082886° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0280", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a5a21a25a9ef7cb5df1937e_3443.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 45.8793716431° N, Longitude: 41.9323539734° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0281", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e2566772554740005d5c9e8_4178.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 37.1998291016° N, Longitude: -17.3959941864° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0282", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a009b7ebac48e5b1cf6ef81_4013.tif" + ], + "Text": "The species shown in the figure is Iquitos varzeá. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -74.5957641602° S, Longitude: -8.342040062° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0283", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209ebb_4394.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -73.7674255371° S, Longitude: 18.21002388° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0284", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad7a7c891b5310010e0d550_4509.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 25.2960090637° N, Longitude: 53.8951873779° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0285", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a9f39ea5a9ef7cb5da727ff_4619.tif" + ], + "Text": "The species shown in the figure is Tongan tropical moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -175.1182556152° S, Longitude: -21.1949920654° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0286", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d970af00a75b7000670395f_4036.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.6909790039° N, Longitude: -4.9384512901° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0287", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c892a92225fc20007ab4e31_2034.tif" + ], + "Text": "The species shown in the figure is Celtic broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -6.3416967392° S, Longitude: 54.1714477539° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0288", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60bc2b27f59a4300057c5519_40.tif" + ], + "Text": "The species shown in the figure is Taiheiyo evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 139.4557342529° N, Longitude: 35.486869812° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0289", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb23d6412ef7220af16_2981.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 120.5067138672° N, Longitude: -8.6088285446° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0290", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6112fad7ac1a340005a1ccf4_1191.tif" + ], + "Text": "The species shown in the figure is West Sudanian savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -1.0507547855° S, Longitude: 9.6595544815° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0291", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60606bd0eeae3c000693003f_1214.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -55.2977638245° S, Longitude: -16.0811481476° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0292", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a789bd45a9ef7cb5d408eb2_1103.tif" + ], + "Text": "The species shown in the figure is Atlantic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 7.6000337601° N, Longitude: 51.9721412659° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0293", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d714d369abb100005e46d9f_186.tif" + ], + "Text": "The species shown in the figure is Central U.S. hardwood forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -87.5304107666° S, Longitude: 37.948387146° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0294", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607bd156bfb5350008e66597_3256.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -93.9118270874° S, Longitude: 45.1752929688° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0295", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e25ec6536067e0005c2752c_3591.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 36.9680557251° N, Longitude: -17.4742927551° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0296", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10356c2b6a08001185f417_2926.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 39.2705764771° N, Longitude: -6.0347075462° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0297", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b88665d3c07e100077c483a_1639.tif" + ], + "Text": "The species shown in the figure is Taiheiyo evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 132.5849761963° N, Longitude: 34.4855957031° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0298", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b913d6412ef7220a0b6_29.tif" + ], + "Text": "The species shown in the figure is California interior chaparral and woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -122.0797119141° S, Longitude: 37.2858810425° E", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0299", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d970af00a75b7000670395f_3773.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 39.6836166382° N, Longitude: -4.9439868927° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0300", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10238f2b6a08001185f398_2398.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.301322937° N, Longitude: -5.9403853416° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0301", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f8de1dca11f71000673ec58_2753.tif" + ], + "Text": "The species shown in the figure is Western Siberian hemiboreal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 66.5370101929° N, Longitude: 56.5094261169° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0302", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d971ce6e2b1f300057cb2fa_945.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 39.7345962524° N, Longitude: -4.9963889122° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0303", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1cc58493e1130005fc0eb0_1559.tif" + ], + "Text": "The species shown in the figure is Bahia coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -38.9148445129° S, Longitude: -12.7434663773° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0304", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b0040ca2b6a08001185f14c_2091.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 39.2742195129° N, Longitude: -5.9385585785° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0305", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cf2330d4e13be0005705534_2268.tif" + ], + "Text": "The species shown in the figure is Eastern Java-Bali montane rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 115.4322433472° N, Longitude: -8.4246110916° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0306", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae7f5fa0b093000130affcc_1251.tif" + ], + "Text": "The species shown in the figure is Granitic Seychelles forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 55.5148620605° N, Longitude: -4.7407855988° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0307", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a597fb25a9ef7cb5df003cf_3495.tif" + ], + "Text": "The species shown in the figure is Richmond temperate forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 172.9934539795° N, Longitude: -41.2477493286° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0308", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10358e2b6a08001185f418_1862.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2071723938° N, Longitude: -6.0692381859° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(D) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0309", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3ac1c0b093000130aff8f_2676.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2669639587° N, Longitude: -6.1759190559° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0310", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd59dbb4cae450005374d3e_2048.tif" + ], + "Text": "The species shown in the figure is Eastern Great Lakes lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -80.430770874° S, Longitude: 43.6816253662° E", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0311", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d8cabebabcfaa0008b1d26b_4528.tif" + ], + "Text": "The species shown in the figure is Rodope montane mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 23.3584728241° N, Longitude: 42.6450767517° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0312", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8f3d6412ef72209f6d_1169.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -120.0294952393° S, Longitude: 38.919380188° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0313", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a7e134e5a9ef7cb5d4ef05f_3845.tif" + ], + "Text": "The species shown in the figure is Maputaland coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 33.5453186035° N, Longitude: -24.7483730316° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0314", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ff330589ef28c00068659a9_3526.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 56.3586158752° N, Longitude: 55.4054412842° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0315", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_733.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 39.3266029358° N, Longitude: -5.967525959° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0316", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6018b89174ca1900066fa4cb_4443.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -79.0525894165° S, Longitude: 35.9145050049° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0317", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b0040ca2b6a08001185f14c_1071.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2631797791° N, Longitude: -5.9496107101° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0318", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3ea615e7ff3f00054889d4_1311.tif" + ], + "Text": "The species shown in the figure is Irrawaddy moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 96.1962356567° N, Longitude: 21.6001415253° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0319", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c27e495e30a0600058cb86d_818.tif" + ], + "Text": "The species shown in the figure is Southern Anatolian montane conifer and deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 33.9801330566° N, Longitude: 36.5187110901° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0320", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b911275a0d7280005fab35d_1567.tif" + ], + "Text": "The species shown in the figure is Western European broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 6.351919651° N, Longitude: 49.5708503723° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0321", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d97233be2b1f300057cb329_2405.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.7031135559° N, Longitude: -5.0892248154° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0322", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3c6d8bbc33050006d379aa_346.tif" + ], + "Text": "The species shown in the figure is Eastern Guinean forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -1.7307416201° S, Longitude: 4.9801068306° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0323", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d2d1302f416f40006cffcc6_546.tif" + ], + "Text": "The species shown in the figure is Sonoran desert. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -115.9406890869° S, Longitude: 33.5182533264° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0324", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3ea615e7ff3f00054889d4_253.tif" + ], + "Text": "The species shown in the figure is Irrawaddy moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 96.1999130249° N, Longitude: 21.6018619537° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0325", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61201a81b7012200056b5c6e_150.tif" + ], + "Text": "The species shown in the figure is Atlantic dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -44.8559341431° S, Longitude: -15.9595384598° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0326", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b7284639102adba313a5c3a_3282.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 17.780670166° N, Longitude: 46.8114929199° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0327", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e43dbd3d9a1b700063006df_442.tif" + ], + "Text": "The species shown in the figure is Brigalow tropical savanna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 149.8063812256° N, Longitude: -25.6536483765° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0328", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/616de51e73cc220005b8e08b_1056.tif" + ], + "Text": "The species shown in the figure is Atlantic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -0.2429631054° S, Longitude: 46.6981391907° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0329", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e118f5c5f5069000738f161_3065.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 34.3088302612° N, Longitude: 49.0545349121° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0330", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d97350ae2b1f300057cb38a_2068.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.8111991882° N, Longitude: -5.2097558975° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0331", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5eda8d6cc692f1000793f1df_479.tif" + ], + "Text": "The species shown in the figure is Sonoran desert. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -111.146194458° S, Longitude: 32.4014472961° E", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0332", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10408a2b6a08001185f427_4180.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.3427200317° N, Longitude: -6.0691623688° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0333", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb23d6412ef7220af16_1924.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.5085525513° N, Longitude: -8.6051664352° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0334", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607c9008bfb5350008e665af_2656.tif" + ], + "Text": "The species shown in the figure is Carpathian montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 23.5719947815° N, Longitude: 49.0352668762° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0335", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b973d6412ef7220a418_4131.tif" + ], + "Text": "The species shown in the figure is Sierra Nevada forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -120.1083831787° S, Longitude: 38.7048072815° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0336", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bc119b7c7e1cf0008e45e25_1151.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 38.3123435974° N, Longitude: 55.5361709595° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0337", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b729f5e9102ad0b033a5c3f_2249.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 18.7956314087° N, Longitude: 47.6660575867° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0338", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a579_4694.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 35.0778312683° N, Longitude: 54.6796607971° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0339", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60e6417b5bc2dc00058bbe15_3679.tif" + ], + "Text": "The species shown in the figure is Bolivian Yungas. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -67.5714035034° S, Longitude: -15.8347959518° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0340", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b983d6412ef7220a48e_2242.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: 103.3146591187° N, Longitude: -4.7906122208° W", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0341", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b913d6412ef7220a0b6_477.tif" + ], + "Text": "The species shown in the figure is California interior chaparral and woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -122.0778656006° S, Longitude: 37.300579071° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0342", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f12fdeebaa90f0006a0ab23_5063.tif" + ], + "Text": "The species shown in the figure is Eastern Java-Bali rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 110.9983291626° N, Longitude: -8.0335283279° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0343", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cc2f46f3dc94a00069404fd_1109.tif" + ], + "Text": "The species shown in the figure is Southern Great Lakes forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -86.1337127686° S, Longitude: 40.4323234558° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0344", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a009b7ebac48e5b1cf6ef81_3520.tif" + ], + "Text": "The species shown in the figure is Iquitos varzeá. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -74.5976028442° S, Longitude: -8.3402080536° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0345", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad7a7c891b5310010e0d550_4946.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 25.3015289307° N, Longitude: 53.8941001892° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0346", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b953d6412ef7220a366_4192.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 42.4084281921° N, Longitude: 43.0854682922° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0347", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61d4908089c86000078daf72_618.tif" + ], + "Text": "The species shown in the figure is Chilean matorral. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -70.6234588623° S, Longitude: -33.4514007568° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0348", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a2d4387bac48e5b1c64facc_4862.tif" + ], + "Text": "The species shown in the figure is Alps conifer and mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 5.6491584778° N, Longitude: 45.2400779724° E", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0349", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60e9b6c1719f47000809413b_608.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 30.7822685242° N, Longitude: 50.1175956726° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0350", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320390b093000130afdab_3063.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.3339614868° N, Longitude: -5.967525959° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0351", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a5a21dc5a9ef7cb5df19529_2027.tif" + ], + "Text": "The species shown in the figure is Caucasus mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 43.7697296143° N, Longitude: 41.8953132629° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0352", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5da4eb2dcac1190007698b1b_4508.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -64.9487533569° S, Longitude: -20.8222084045° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0353", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd0f370a7dadc0006433b56_2150.tif" + ], + "Text": "The species shown in the figure is Nigerian lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 3.3917982578° N, Longitude: 6.4972615242° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0354", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e9d2bc9054194000589a41a_3781.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 17.5827636719° N, Longitude: 59.7195129395° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0355", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d971d17e2b1f300057cb307_208.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.7079086304° N, Longitude: -5.0092849731° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0356", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/6087b78e6914ef000561b333_4577.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 22.3057041168° N, Longitude: 48.6195678711° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0357", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10408a2b6a08001185f427_1164.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3537597656° N, Longitude: -6.0691623688° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0358", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d15131557915d0007f8d266_3627.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 12.5033597946° N, Longitude: 55.7739601135° E", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0359", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e9d2bc9054194000589a41a_4070.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 17.5846042633° N, Longitude: 59.7204437256° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0360", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8f3d6412ef72209f97_1001.tif" + ], + "Text": "The species shown in the figure is Northwestern Andean montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -78.4307937622° S, Longitude: 0.0142869083° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0361", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320900b093000130afdb4_3949.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 39.2163505554° N, Longitude: -6.005753994° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0362", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61a5879bca228100065cb98a_2371.tif" + ], + "Text": "The species shown in the figure is Nihonkai montane deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 134.3922424316° N, Longitude: 35.2179069519° E", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0363", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10358e2b6a08001185f418_3165.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.2200508118° N, Longitude: -6.0471382141° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0364", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d96feee0a75b70006703919_4988.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(C) Latitude: 39.6721382141° N, Longitude: -4.8677825928° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0365", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d3561a98a5c8b000519fdac_1802.tif" + ], + "Text": "The species shown in the figure is Balkan mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: 25.2743816376° N, Longitude: 42.3983802795° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0366", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cd4a49f4b7c75000784da34_1962.tif" + ], + "Text": "The species shown in the figure is Peruvian Yungas. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: -78.5691452026° S, Longitude: -7.198662281° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0367", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60e9b6c1719f47000809413b_1385.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 30.7841091156° N, Longitude: 50.1187782288° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0368", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d706fa55583d40006c15788_4658.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -81.6991882324° S, Longitude: 35.7204284668° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0369", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b983d6412ef7220a48e_1468.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: 103.3164978027° N, Longitude: -4.7795386314° W", + "(D) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0370", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b713a5291cf644aafeeacc4_453.tif" + ], + "Text": "The species shown in the figure is Scandinavian and Russian taiga. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 25.2162742615° N, Longitude: 60.3457489014° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0371", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cf70198c25f7e00059bac96_3354.tif" + ], + "Text": "The species shown in the figure is Hawaii tropical moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -157.8287353516° S, Longitude: 21.4026260376° E", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0372", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a9980b15a9ef7cb5d982284_4806.tif" + ], + "Text": "The species shown in the figure is Tongan tropical moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1376934052° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0373", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c5cde10e84ca0000599359f_111.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -121.9298248291° S, Longitude: 36.5389976501° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0374", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/610c08bea2f7d6000711f8bf_2138.tif" + ], + "Text": "The species shown in the figure is Eastern Cordillera real montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -77.6101150513° S, Longitude: -0.1395897418° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0375", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fa016bbd3a8ab0007ea6a66_363.tif" + ], + "Text": "The species shown in the figure is Central Andean dry puna. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -66.1436538696° S, Longitude: -21.1726760864° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0376", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f35fe824e328d00066b0165_4329.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 118.6060028076° N, Longitude: -8.7650527954° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0377", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62beb3d6412ef7220c5aa_2209.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 39.2206878662° N, Longitude: -6.7909255028° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0378", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad7a7c891b5310010e0d550_4264.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 25.2978496552° N, Longitude: 53.8941001892° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0379", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d97277fe2b1f300057cb341_2120.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.8175926208° N, Longitude: -5.1010422707° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0380", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209ebb_4685.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: -73.750869751° S, Longitude: 18.2223300934° E", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0381", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b90f92da0d7280005fab355_4200.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 120.9827423096° N, Longitude: 14.5932664871° E", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0382", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb03d6412ef7220aea8_3498.tif" + ], + "Text": "The species shown in the figure is Sumatran lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 102.26612854° N, Longitude: -3.8027584553° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0383", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae378c00b093000130afe28_2808.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: 39.2434921265° N, Longitude: -6.0871548653° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0384", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c83a075f6a3c00007326598_3051.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 0.5122551918° N, Longitude: 50.8529777527° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0385", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d5ee0fe1d3eab00054f8e69_1822.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 49.1757659912° N, Longitude: 54.4897766113° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0386", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c5cde10e84ca0000599359f_1012.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -121.9298248291° S, Longitude: 36.5345458984° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0387", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320420b093000130afdad_4434.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 39.3247337341° N, Longitude: -5.9242572784° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0388", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59fc9657bac48e5b1ced2a2f_2087.tif" + ], + "Text": "The species shown in the figure is Uatuma-Trombetas moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -60.0961723328° S, Longitude: -3.0251512527° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0389", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b6473dd40e11005cf16cc89_1788.tif" + ], + "Text": "The species shown in the figure is Crimean Submediterranean forest complex. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 34.4223937988° N, Longitude: 44.6828918457° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0390", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60d6e00dc700c600080d5531_278.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 23.9725036621° N, Longitude: 50.0525817871° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0391", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a57f_349.tif" + ], + "Text": "The species shown in the figure is Central Zambezian Miombo woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 33.8535957336° N, Longitude: -13.980638504° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0392", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e4fbd3024710000056a516f_3864.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -58.3115310669° S, Longitude: -10.9738998413° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0393", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dbb240d05580100062e0210_2969.tif" + ], + "Text": "The species shown in the figure is Mato Grosso seasonal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -51.5771064758° S, Longitude: -10.6633501053° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0394", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607c9008bfb5350008e665af_3550.tif" + ], + "Text": "The species shown in the figure is Carpathian montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 23.5701560974° N, Longitude: 49.0340576172° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0395", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d7cb858ecaf880008a9bc7d_4753.tif" + ], + "Text": "The species shown in the figure is Balkan mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 25.6095409393° N, Longitude: 42.4182701111° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0396", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f12fdeebaa90f0006a0ab23_4587.tif" + ], + "Text": "The species shown in the figure is Eastern Java-Bali rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 110.9983291626° N, Longitude: -8.0408630371° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0397", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d97277fe2b1f300057cb341_2140.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.8157539368° N, Longitude: -5.0936632156° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0398", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5da4eb2dcac1190007698b1b_4400.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: -64.9524307251° S, Longitude: -20.8222084045° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0399", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f363b374e328d00066b0175_3544.tif" + ], + "Text": "The species shown in the figure is Lesser Sundas deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 118.465171814° N, Longitude: -8.6456890106° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0400", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60b0cccea9600f0008458140_2309.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 23.9883327484° N, Longitude: 49.8087425232° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0401", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be73d6412ef7220c423_1488.tif" + ], + "Text": "The species shown in the figure is Timor and Wetar deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 124.8154830933° N, Longitude: -9.061665535° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0402", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b953d6412ef7220a31f_4879.tif" + ], + "Text": "The species shown in the figure is Mindanao-Eastern Visayas rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 124.9218292236° N, Longitude: 11.2478046417° E", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0403", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a429463bac48e5b1c9b41b5_1051.tif" + ], + "Text": "The species shown in the figure is Lower Gangetic Plains moist deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 92.1897125244° N, Longitude: 21.0842838287° E", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0404", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59fc9657bac48e5b1ced2a2f_1595.tif" + ], + "Text": "The species shown in the figure is Uatuma-Trombetas moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: -60.0924949646° S, Longitude: -3.0233016014° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0405", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f0ed88e31da55000562467f_1982.tif" + ], + "Text": "The species shown in the figure is Palawan rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 120.2086715698° N, Longitude: 12.0003166199° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0406", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d8cabebabcfaa0008b1d26b_4415.tif" + ], + "Text": "The species shown in the figure is Rodope montane mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 23.3547935486° N, Longitude: 42.6464347839° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0407", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cf06748b9ff690005693589_3969.tif" + ], + "Text": "The species shown in the figure is Western Java montane rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 109.7671127319° N, Longitude: -7.3555607796° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0408", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60bffba9ef5d220007c24a8c_2385.tif" + ], + "Text": "The species shown in the figure is North Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -120.8602600098° S, Longitude: 53.5692062378° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0409", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae4afd70b093000130affb1_1424.tif" + ], + "Text": "The species shown in the figure is Eastern Guinean forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -1.8895326853° S, Longitude: 5.9659161568° E", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0410", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5aea3d3b8153990013b938e8_3683.tif" + ], + "Text": "The species shown in the figure is Trans-Mexican Volcanic Belt pine-oak forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: -101.2279052734° S, Longitude: 19.6472244263° E", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0411", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ea54c1cc70abb0005869ea7_4738.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 119.9188461304° N, Longitude: -1.0397523642° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0412", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d29ec177a18fd0005e2978e_1290.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 121.1323547363° N, Longitude: 16.9302310944° E", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0413", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f2fb5190d59fe00057c32ac_4364.tif" + ], + "Text": "The species shown in the figure is Himalayan subtropical broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 86.2503356934° N, Longitude: 26.9997749329° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0414", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60c2f2c4c3b42f000788d321_3758.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 24.0412597656° N, Longitude: 49.8149261475° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0415", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e118f5c5f5069000738f161_1449.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 34.3088302612° N, Longitude: 49.0569534302° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0416", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dc40b06d0e638000592ebe6_644.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -47.7994689941° S, Longitude: -19.4650096893° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0417", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f12fdeebaa90f0006a0ab23_4621.tif" + ], + "Text": "The species shown in the figure is Eastern Java-Bali rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 110.9983291626° N, Longitude: -8.03536129° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0418", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b1042892b6a08001185f43c_4378.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 39.2632446289° N, Longitude: -6.0705666542° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0419", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/607af86cbfb5350008e66588_1909.tif" + ], + "Text": "The species shown in the figure is Baltic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 15.2841291428° N, Longitude: 52.9199714661° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0420", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be83d6412ef7220c45c_4603.tif" + ], + "Text": "The species shown in the figure is Timor and Wetar deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 124.8861083984° N, Longitude: -9.3341026306° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0421", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a8213345a9ef7cb5d5973bb_3067.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -174.9839019775° S, Longitude: -21.1230659485° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0422", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dbb240d05580100062e0210_1926.tif" + ], + "Text": "The species shown in the figure is Mato Grosso seasonal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -51.5771064758° S, Longitude: -10.6669893265° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0423", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be63d6412ef7220c3a5_757.tif" + ], + "Text": "The species shown in the figure is Maputaland coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: 33.6268157959° N, Longitude: -25.0253314972° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0424", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a592_3087.tif" + ], + "Text": "The species shown in the figure is New England-Acadian forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -72.8298416138° S, Longitude: 42.1615333557° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0425", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e92a43ec6bbac0005e30fd2_3345.tif" + ], + "Text": "The species shown in the figure is Nihonkai montane deciduous forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 139.0458831787° N, Longitude: 37.541519165° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0426", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320420b093000130afdad_4948.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.3320922852° N, Longitude: -5.9279413223° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0427", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e2566772554740005d5c9e8_4612.tif" + ], + "Text": "The species shown in the figure is Southern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: 37.2016677856° N, Longitude: -17.3995265961° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0428", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dbb240d05580100062e0210_3072.tif" + ], + "Text": "The species shown in the figure is Mato Grosso seasonal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -51.5771064758° S, Longitude: -10.6706285477° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0429", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b10408a2b6a08001185f427_645.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 39.3482398987° N, Longitude: -6.047062397° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0430", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b635ac0a37c3dcbe3ea5287_3847.tif" + ], + "Text": "The species shown in the figure is Celtic broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -8.9200248718° S, Longitude: 51.7673721313° E", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0431", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b7a3d6412ef7220953b_2104.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 169.2075042725° N, Longitude: -18.747800827° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0432", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b8d3d6412ef72209e91_3661.tif" + ], + "Text": "The species shown in the figure is Hispaniolan moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -73.7692642212° S, Longitude: 18.2117824554° E", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0433", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5deee6d4e5d474000640673a_5061.tif" + ], + "Text": "The species shown in the figure is Bahamian pine mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -77.0843048096° S, Longitude: 26.4718723297° E", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0434", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbdd9ef1f79c3000788a403_4211.tif" + ], + "Text": "The species shown in the figure is South Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(C) Latitude: -116.1237335205° S, Longitude: 44.0672531128° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0435", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60606bd0eeae3c000693003f_184.tif" + ], + "Text": "The species shown in the figure is Cerrado. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -55.3088035583° S, Longitude: -16.0722541809° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0436", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ad6e3b291b5310010e0d543_1059.tif" + ], + "Text": "The species shown in the figure is Mesopotamian shrub desert. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 35.0483436584° N, Longitude: 31.343793869° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0437", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a5b7_700.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: -73.9257278442° S, Longitude: 40.7630882263° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0438", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a2649ffbac48e5b1c532826_4516.tif" + ], + "Text": "The species shown in the figure is Changjiang Plain evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 120.0146942139° N, Longitude: 30.2836952209° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0439", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be63d6412ef7220c3a5_292.tif" + ], + "Text": "The species shown in the figure is Maputaland coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 33.62865448° N, Longitude: -25.0303611755° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0440", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ea54c1cc70abb0005869ea7_4584.tif" + ], + "Text": "The species shown in the figure is Sulawesi lowland rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 119.9170074463° N, Longitude: -1.0360486507° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0441", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd0f6dda7dadc0006433b5b_4890.tif" + ], + "Text": "The species shown in the figure is Nigerian lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: 3.3885333538° N, Longitude: 6.4980072975° E", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0442", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e28a0d12329e800051134a5_301.tif" + ], + "Text": "The species shown in the figure is Araucaria moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -49.8149032593° S, Longitude: -24.1472415924° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0443", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bafcf9ea28dc0000543f068_4185.tif" + ], + "Text": "The species shown in the figure is North Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: -119.0241546631° S, Longitude: 52.6790504456° E", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0444", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cafa1a0f58c0800075d4fc2_3566.tif" + ], + "Text": "The species shown in the figure is Northwestern Andean montane forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -78.5070648193° S, Longitude: -0.1534825712° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0445", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b9b3d6412ef7220a57f_796.tif" + ], + "Text": "The species shown in the figure is Central Zambezian Miombo woodlands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: 33.8535957336° N, Longitude: -13.9824352264° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0446", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d78e8faf719820008245cfa_3068.tif" + ], + "Text": "The species shown in the figure is Taiheiyo evergreen forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 130.0772094727° N, Longitude: 33.2165107727° E", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0447", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d0511a873de290005853a93_4429.tif" + ], + "Text": "The species shown in the figure is Central Indochina dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 98.8866195679° N, Longitude: 18.59532547° E", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0448", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b943d6412ef7220a2af_1782.tif" + ], + "Text": "The species shown in the figure is Sao Tome, Principe and Annobon moist lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 6.7308516502° N, Longitude: 0.3392491341° E", + "(B) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0449", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5da4eb2dcac1190007698b1b_4422.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -64.950592041° S, Longitude: -20.8273963928° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0450", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d5293f4c522e6000532f61b_2193.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 0.997025013° N, Longitude: 51.236831665° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0451", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d971d17e2b1f300057cb307_1041.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 39.7207870483° N, Longitude: -4.9963698387° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0452", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be83d6412ef7220c468_2610.tif" + ], + "Text": "The species shown in the figure is North Atlantic moist mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -1.3407262564° S, Longitude: 60.5501480103° E", + "(C) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0453", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5bbd459c3baffb0005fe9ba1_2903.tif" + ], + "Text": "The species shown in the figure is Southeastern mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -84.1160430908° S, Longitude: 33.6660804749° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0454", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ddb95a2aff195000554e7e4_4956.tif" + ], + "Text": "The species shown in the figure is Himalayan subtropical pine forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 83.9089813232° N, Longitude: 28.1285877228° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0455", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b703d6412ef72208f5a_4989.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: 121.15625° N, Longitude: 14.048125267° E", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0456", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae320420b093000130afdad_4403.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3302536011° N, Longitude: -5.9168887138° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0457", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b7a3d6412ef7220953b_2492.tif" + ], + "Text": "The species shown in the figure is Vanuatu rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(D) Latitude: 169.2111816406° N, Longitude: -18.747800827° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0458", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ddb95a2aff195000554e7e4_5042.tif" + ], + "Text": "The species shown in the figure is Himalayan subtropical pine forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 83.9108200073° N, Longitude: 28.1302185059° E", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0459", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59fc9657bac48e5b1ced2a2f_1633.tif" + ], + "Text": "The species shown in the figure is Uatuma-Trombetas moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -60.0998535156° S, Longitude: -3.0233016014° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0460", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a789bd45a9ef7cb5d408eb2_865.tif" + ], + "Text": "The species shown in the figure is Atlantic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 7.5981936455° N, Longitude: 51.9732780457° E", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0461", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f0eda6b31da550005624682_4299.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(C) Latitude: 120.211151123° N, Longitude: 11.993970871° E", + "(D) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0462", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b5d6c3bfb9b12de9d9dac90_217.tif" + ], + "Text": "The species shown in the figure is Eastern Mediterranean conifer-sclerophyllous-broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 34.7612686157° N, Longitude: 31.7993354797° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0463", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3923e0b093000130aff38_1562.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(B) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(D) Latitude: 39.417842865° N, Longitude: -6.4090161324° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0464", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e639ceaec014e0006188772_2906.tif" + ], + "Text": "The species shown in the figure is Madeira-Tapajós moist forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -62.4804840088° S, Longitude: -12.0066413879° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0465", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60f138e489ec130007b828c3_566.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(B) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(C) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(D) Latitude: 120.3972549438° N, Longitude: -3.4146471024° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0466", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f85751a7d446d0005fa8178_3150.tif" + ], + "Text": "The species shown in the figure is Central European mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: 24.7970485687° N, Longitude: 50.0569648743° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0467", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60d2046feade0f00079b58bd_2876.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: 124.2057723999° N, Longitude: 14.0132932663° E", + "(D) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0468", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3a7f00b093000130aff66_3982.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 39.3611869812° N, Longitude: -6.1703453064° W", + "(B) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0469", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5dd599f64cae450005374d2e_1207.tif" + ], + "Text": "The species shown in the figure is Atlantic Coast restingas. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -35.2047157288° S, Longitude: -5.8342614174° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0470", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d96feee0a75b70006703919_4409.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1704845428° W", + "(B) Latitude: -175.291885376° S, Longitude: -21.1825637817° W", + "(C) Latitude: -175.282699585° S, Longitude: -21.1825637817° W", + "(D) Latitude: 39.6776580811° N, Longitude: -4.865937233° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0471", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d67dfdddf35140006907ab3_1055.tif" + ], + "Text": "The species shown in the figure is . Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -85.377784729° S, Longitude: 29.9136505127° E", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0472", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b729f5e9102ad0b033a5c3f_2733.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 18.7974700928° N, Longitude: 47.6635742188° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0473", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62bb13d6412ef7220aed6_1715.tif" + ], + "Text": "The species shown in the figure is Upper Midwest forest-savanna transition. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: -88.2546005249° S, Longitude: 44.2823677063° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0474", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae4afd70b093000130affb1_1757.tif" + ], + "Text": "The species shown in the figure is Eastern Guinean forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: -1.8876930475° S, Longitude: 5.9696002007° E", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0475", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbdd9ef1f79c3000788a403_4265.tif" + ], + "Text": "The species shown in the figure is South Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -116.1329345703° S, Longitude: 44.0539855957° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0476", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5ae3adc00b093000130affa6_672.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 39.2472305298° N, Longitude: -6.22651577° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0477", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5a135953bac48e5b1c24c537_2212.tif" + ], + "Text": "The species shown in the figure is Puget lowland forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(B) Latitude: -122.3968963623° S, Longitude: 47.6633491516° E", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0478", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fbdd9ef1f79c3000788a403_4568.tif" + ], + "Text": "The species shown in the figure is South Central Rockies forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -116.1200561523° S, Longitude: 44.0685768127° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0479", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c3c6d8bbc33050006d379aa_28.tif" + ], + "Text": "The species shown in the figure is Eastern Guinean forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(D) Latitude: -1.7289018631° S, Longitude: 4.9837970734° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0480", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/61cb8771081c15000543455a_532.tif" + ], + "Text": "The species shown in the figure is Po Basin mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: 11.9007501602° N, Longitude: 44.3041725159° E", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0481", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5b1042892b6a08001185f43c_5035.tif" + ], + "Text": "The species shown in the figure is Northern Zanzibar-Inhambane coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 39.279800415° N, Longitude: -6.0926656723° W", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0482", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b703d6412ef72208f44_3134.tif" + ], + "Text": "The species shown in the figure is Mindanao-Eastern Visayas rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(B) Latitude: 125.0078201294° N, Longitude: 11.251742363° E", + "(C) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(D) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0483", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7177d91d951a00058695e8_3109.tif" + ], + "Text": "The species shown in the figure is Pannonian mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(C) Latitude: 14.8086557388° N, Longitude: 45.6954231262° E", + "(D) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0484", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f7b47dc803f62000513f7ee_1517.tif" + ], + "Text": "The species shown in the figure is Himalayan subtropical broadleaf forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(B) Latitude: 86.255859375° N, Longitude: 26.993183136° E", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0485", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1654f81cf0f6000579ad20_1078.tif" + ], + "Text": "The species shown in the figure is Northern mixed grasslands. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: -100.8722763062° S, Longitude: 48.516746521° E", + "(D) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0486", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5cdd8aef6e10670005c5996e_2231.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: -2.3405015469° S, Longitude: 51.8321838379° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0487", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60d2046feade0f00079b58bd_2180.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 124.2039260864° N, Longitude: 14.0132932663° E", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0488", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e24f9cf2554740005d5c9bb_2983.tif" + ], + "Text": "The species shown in the figure is Northeastern coastal forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(B) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(C) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(D) Latitude: -71.6334533691° S, Longitude: 42.1340103149° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0489", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5c6522c346bdea00053984d1_2793.tif" + ], + "Text": "The species shown in the figure is Granitic Seychelles forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 55.5235176086° N, Longitude: -4.6992931366° W", + "(B) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0490", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d1943a65a23bb00066ee0d9_2654.tif" + ], + "Text": "The species shown in the figure is Bahia interior forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(B) Latitude: -39.0876426697° S, Longitude: -12.6670751572° W", + "(C) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(D) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0491", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5f12fdeebaa90f0006a0ab23_4891.tif" + ], + "Text": "The species shown in the figure is Eastern Java-Bali rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(C) Latitude: 110.9946517944° N, Longitude: -8.0335283279° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0492", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62b703d6412ef72208f5a_4950.tif" + ], + "Text": "The species shown in the figure is Luzon rain forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2937316895° S, Longitude: -21.1842880249° W", + "(B) Latitude: 121.1470489502° N, Longitude: 14.0894298553° E", + "(C) Latitude: -175.2882080078° S, Longitude: -21.1894645691° W", + "(D) Latitude: -175.3047637939° S, Longitude: -21.1739349365° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0493", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fe072620cf0b40005ddf6c3_4083.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: 10.6943941116° N, Longitude: 59.4643783569° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0494", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60e988c5719f470008094136_259.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 26.4040203094° N, Longitude: 54.1375389099° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0495", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/60c1b7e8c3b42f000788d30a_165.tif" + ], + "Text": "The species shown in the figure is Sarmatic mixed forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 37.4740791321° N, Longitude: 56.9497032166° E", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(D) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0496", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5d5293f4c522e6000532f61b_2708.tif" + ], + "Text": "The species shown in the figure is English Lowlands beech forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 177.5324859619° N, Longitude: -17.6693782806° W", + "(B) Latitude: 0.9988647699° N, Longitude: 51.236831665° E", + "(C) Latitude: 177.5343170166° N, Longitude: -17.665851593° W", + "(D) Latitude: 177.5306396484° N, Longitude: -17.6676158905° W", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0497", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/59e62be63d6412ef7220c3a5_1314.tif" + ], + "Text": "The species shown in the figure is Maputaland coastal forest mosaic. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(D) Latitude: 33.6341743469° N, Longitude: -25.0286846161° W", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0498", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5fba7574f867fd0007e9774a_3597.tif" + ], + "Text": "The species shown in the figure is Bolivian montane dry forests. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: 175.0385437012° N, Longitude: -41.1387672424° W", + "(B) Latitude: 175.0385437012° N, Longitude: -41.1401596069° W", + "(C) Latitude: -68.0404510498° S, Longitude: -16.6238040924° W", + "(D) Latitude: 175.0403747559° N, Longitude: -41.1387672424° W", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + }, + { + "Question_id": "Geographical Location Inference of Plant Species/0499", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/OAM-TCD/dataset/images/5e23284750259f000541fc4e_4258.tif" + ], + "Text": "The species shown in the figure is East European forest steppe. Which latitude and longitude is this figure most likely to be located at?", + "Answer Choices": [ + "(A) Latitude: -175.2992553711° S, Longitude: -21.1290626526° W", + "(B) Latitude: -175.2955780029° S, Longitude: -21.123884201° W", + "(C) Latitude: -175.3029327393° S, Longitude: -21.123884201° W", + "(D) Latitude: 32.8014678955° N, Longitude: 49.8114891052° E", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Geographical Location Inference of Plant Species", + "Dataset": "OAM-TCD", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Global_Animal_Counting.json b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Global_Animal_Counting.json new file mode 100644 index 0000000000000000000000000000000000000000..40faf3e367c89e703b55ba951bbedd6b5f6cd120 --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Global_Animal_Counting.json @@ -0,0 +1,2312 @@ +[ + { + "Question_id": "Global Animal Counting/0000", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 54", + "(B) 55", + "(C) 56", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2240.y2688.png" + ] + }, + { + "Question_id": "Global Animal Counting/0001", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 20 ", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2240.y3136.png" + ] + }, + { + "Question_id": "Global Animal Counting/0002", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 149", + "(B) 150", + "(C) 151", + "(D) 152", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0003", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 83", + "(B) 84", + "(C) 85", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0004", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 140", + "(B) 141", + "(C) 142", + "(D) 143", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0005", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 117", + "(B) 118", + "(C) 119", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0006", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 72", + "(B) 73", + "(C) 74", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0007", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 30", + "(B) 32", + "(C) 33", + "(D) 34", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y2688.png" + ] + }, + { + "Question_id": "Global Animal Counting/0008", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 71", + "(B) 72", + "(C) 73", + "(D) 74", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0009", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 33", + "(B) 34", + "(C) 35", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0010", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 85", + "(B) 86", + "(C) 87", + "(D) 88", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0011", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 78", + "(B) 79", + "(C) 80", + "(D) 81", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0012", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 39", + "(B) 40", + "(C) 41", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y2240.png" + ] + }, + { + "Question_id": "Global Animal Counting/0013", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 60", + "(B) 61", + "(C) 62", + "(D) 63", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0014", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 14", + "(B) 15", + "(C) 16", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4032.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0015", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 19", + "(B) 20", + "(C) 21", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y2240.png" + ] + }, + { + "Question_id": "Global Animal Counting/0016", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 70", + "(B) 71", + "(C) 72", + "(D) 73", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4928.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0017", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 24", + "(B) 25", + "(C) 26", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0018", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 13", + "(B) 14", + "(C) 15", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5824.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0019", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 67", + "(B) 68", + "(C) 69", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0020", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y3136.png" + ] + }, + { + "Question_id": "Global Animal Counting/0021", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 78", + "(B) 79", + "(C) 80", + "(D) 81", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x4928.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0022", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 179", + "(B) 180", + "(C) 200", + "(D) 183", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0023", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 46", + "(B) 47", + "(C) 48", + "(D) 49", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0024", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 61", + "(B) 51", + "(C) 82", + "(D) 93", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0025", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 118", + "(B) 119", + "(C) 120", + "(D) 121", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0026", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 100", + "(B) 101", + "(C) 102", + "(D) 103", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0027", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 42", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0028", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0029", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x8512.y1792.png" + ] + }, + { + "Question_id": "Global Animal Counting/0030", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 50", + "(B) 49", + "(C) 48", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4032.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0031", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 83", + "(B) 84", + "(C) 85", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x2688.y2688.png" + ] + }, + { + "Question_id": "Global Animal Counting/0032", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0033", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0034", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 50", + "(B) 52", + "(C) 53", + "(D) 54", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3136.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0035", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 518", + "(B) 519", + "(C) 520", + "(D) 521", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0036", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 43", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x4928.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0037", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 17", + "(B) 18", + "(C) 19", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y1792.png" + ] + }, + { + "Question_id": "Global Animal Counting/0038", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 46", + "(B) 47", + "(C) 48", + "(D) 49", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0039", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x1792.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0040", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A)146", + "(B) 147", + "(C) 148", + "(D)149", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0041", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y2240.png" + ] + }, + { + "Question_id": "Global Animal Counting/0042", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0043", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 250", + "(B) 251", + "(C) 252", + "(D) 253", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0044", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7616.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0045", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0046", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 54", + "(B) 60", + "(C) 63", + "(D) 66", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0047", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0048", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3136.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0049", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4480.y3136.png" + ] + }, + { + "Question_id": "Global Animal Counting/0050", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 295", + "(B) 296", + "(C) 297", + "(D) 298", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3136.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0051", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 137", + "(B) 138", + "(C) 139", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x4480.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0052", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 13", + "(B) 14", + "(C) 15", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3584.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0053", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y2688.png" + ] + }, + { + "Question_id": "Global Animal Counting/0054", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 24", + "(B) 27", + "(C) 21", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0055", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 190", + "(B) 191", + "(C) 192", + "(D) 193", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x3584.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0056", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 175", + "(B) 176", + "(C) 177", + "(D) 178", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0057", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 50", + "(B) 41", + "(C) 25", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x2240.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0058", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 50", + "(B) 51", + "(C) 52", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x2688.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0059", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 370", + "(B) 372", + "(C) 374", + "(D) 376", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0060", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0061", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 70", + "(B) 71", + "(C) 72", + "(D) 73", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0062", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 153", + "(B) 154", + "(C) 155", + "(D) 156", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0063", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 19", + "(B) 20", + "(C) 21", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0064", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 49", + "(B) 50", + "(C) 51", + "(D) 52", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x5824.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0065", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x5824.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0066", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 160", + "(B) 163", + "(C) 165", + "(D) 166", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x6720.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0067", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 67", + "(B) 68", + "(C) 69", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3584.y2240.png" + ] + }, + { + "Question_id": "Global Animal Counting/0068", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 126", + "(B) 127", + "(C) 128", + "(D) 129", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0069", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 47", + "(B) 48", + "(C) 49", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9408.y896.png" + ] + }, + { + "Question_id": "Global Animal Counting/0070", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 152", + "(B) 153", + "(C) 154", + "(D) 155", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4480.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0071", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 120", + "(B) 121", + "(C) 122", + "(D) 123", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x3584.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0072", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 52", + "(B) 53", + "(C) 54", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x4928.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0073", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 39", + "(B) 40", + "(C) 49", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x5376.y3136.png" + ] + }, + { + "Question_id": "Global Animal Counting/0074", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 76", + "(B) 77", + "(C) 78", + "(D) 79", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x3136.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0075", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 14", + "(B) 15", + "(C) 16", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x5376.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0076", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 209", + "(B) 210", + "(C) 309", + "(D) 310", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0077", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9856.y1344.png" + ] + }, + { + "Question_id": "Global Animal Counting/0078", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 60", + "(B) 61", + "(C) 62", + "(D) 63", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0079", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 149", + "(B) 147", + "(C) 146", + "(D) 143", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4928.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0080", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 56", + "(B) 59", + "(C) 55", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0081", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 10", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x2240.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0082", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": 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"Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 30", + "(B) 35", + "(C) 37", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4928.y4032.png" + ] + }, + { + "Question_id": "Global Animal Counting/0085", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 42", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4480.y5376.png" + ] + }, + { + "Question_id": "Global Animal Counting/0086", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 114", + "(B) 115", + "(C) 116", + "(D) 117", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0087", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 360", + "(B) 361", + "(C) 362", + "(D) 363", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_003~030_rg.chop.x5376.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0088", 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"raw/Biosphere/animal/penguin/Bas2019_01c_012~281_rg.chop.x7168.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0090", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 85", + "(B) 86", + "(C) 87", + "(D) 88", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y6272.png" + ] + }, + { + "Question_id": "Global Animal Counting/0091", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 58", + "(B) 59", + "(C) 60", + "(D) 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"L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_008~154_rg.chop.x4032.y3136.png" + ] + }, + { + "Question_id": "Global Animal Counting/0096", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0023~008_rg.chop.x4032.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0097", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 17", + "(B) 19", + "(C) 21", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_05C_0022~019_rg.chop.x9408.y448.png" + ] + }, + { + "Question_id": "Global Animal Counting/0098", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 116", + "(B) 117", + "(C) 118", + "(D) 119", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_017~397_rg.chop.x5376.y6720.png" + ] + }, + { + "Question_id": "Global Animal Counting/0099", + "Question Type": "Single Choice", + "Text": "How many penguins are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 19", + "(B) 20", + "(C) 21", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x4032.y2688.png" + ] + }, + { + "Question_id": "Global Animal Counting/0100", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x2688.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0101", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x3584.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0102", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0103", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 56", + "(B) 59", + "(C) 54", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x9408.y5824.png" + ] + }, + { + "Question_id": "Global Animal Counting/0104", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 29", + "(B) 30", + "(C) 32", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_04d_010~247_rg.chop.x1344.y3584.png" + ] + }, + { + "Question_id": "Global Animal Counting/0105", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x7168.y4480.png" + ] + }, + { + "Question_id": "Global Animal Counting/0106", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0107", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x5376.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0108", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x7616.y4928.png" + ] + }, + { + "Question_id": "Global Animal Counting/0109", + "Question Type": "Single Choice", + "Text": "How many animals are there in the entire picture?", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Global Animal Counting", + "Dataset": "penguin", + "L1-task": "Biosphere", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/animal/penguin/Bas2019_01c_014~312_rg.chop.x8064.y5376.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Species_Distribution_Prediction.json b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Species_Distribution_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..ab57335874a9e23f0ea49ae701b9a2c92cd26732 --- /dev/null +++ b/jsons/Biosphere/Species_Distribution_Prediction/Reasoning/Species_Distribution_Prediction.json @@ -0,0 +1,21002 @@ +[ + { + "Question_id": "Species Distribution Prediction/0000", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/86062172.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.370776218° N, and the longitude is 81.2460208323° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Vireo gilvus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0001", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145888009.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 2.29909036° N, and the longitude is 103.65129708° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Kurochkinegramma hypogrammicum", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0002", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110612529.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6689138889° N, and the longitude is 79.2993611111° W.", + "Answer Choices": [ + "(A) Dryobates villosus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0003", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/29585694.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9496758467° N, and the longitude is 116.677919465° W.", + "Answer Choices": [ + "(A) Polioptila californica", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0004", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/177092138.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 26.9859650894° N, and the longitude is 102.0572299493° W.", + "Answer Choices": [ + "(A) Tyrannus verticalis", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0005", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116679467.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.3035984996° N, and the longitude is 4.5551896643° E.", + "Answer Choices": [ + "(A) Otus scops", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0006", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45364830.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.193640987° N, and the longitude is 25.0272385596° E.", + "Answer Choices": [ + "(A) Phylloscopus trochilus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0007", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/160159661.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.2020400877° N, and the longitude is 25.1671236648° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Spinus spinus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0008", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/134564034.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.8943908393° S, and the longitude is 71.4079440248° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Sciaphylax hemimelaena", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0009", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84777291.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.3304147894° N, and the longitude is 73.1261171036° W.", + "Answer Choices": [ + "(A) Spiza americana", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0010", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39091655.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.7316355087° N, and the longitude is 3.5464453896° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Corvus corone", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0011", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/178980960.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.0085369303° N, and the longitude is 42.8601975686° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Phylloscopus collybita", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0012", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193884247.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.3291969112° N, and the longitude is 39.6888193677° E.", + "Answer Choices": [ + "(A) Cuculus canorus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0013", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52621228.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8627° N, and the longitude is 83.637767° W.", + "Answer Choices": [ + "(A) Hylocichla mustelina", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0014", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112267475.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.3256723952° N, and the longitude is 8.4908679105° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Poecile montanus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0015", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162881455.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5871663491° N, and the longitude is 73.5530793958° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga americana", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0016", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202283369.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.5776104436° N, and the longitude is 99.5194893717° W.", + "Answer Choices": [ + "(A) Hirundo rustica erythrogaster", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0017", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/134090062.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.597125° N, and the longitude is 103.3328861111° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Pseudacris maculata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0018", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189958291.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.351426° N, and the longitude is 103.771079° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Microhyla heymonsi", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0019", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/169858932.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2010239624° N, and the longitude is 121.8023555648° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Thryomanes bewickii", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0020", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192342216.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.6248148827° N, and the longitude is 23.6467403486° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Periparus ater", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0021", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72549778.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9680865738° N, and the longitude is 83.7287820829° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Dryocopus pileatus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0022", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112793971.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7849174906° N, and the longitude is 96.9313339749° W.", + "Answer Choices": [ + "(A) Vireo atricapilla", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0023", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130123577.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.3452209259° N, and the longitude is 14.0140772774° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Troglodytes troglodytes", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0024", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22628.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.282° S, and the longitude is 54.129° W.", + "Answer Choices": [ + "(A) Physalaemus ephippifer", + "(B) Acanthis hornemanni", + "(C) Poecile atricapillus", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0025", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/62992828.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.629929° S, and the longitude is 152.832108° E.", + "Answer Choices": [ + "(A) Pachycephala rufiventris", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0026", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164333261.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7857457092° N, and the longitude is 87.5813960308° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Cardellina canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0027", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/175943966.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.5423710984° N, and the longitude is 84.377628416° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Spinus tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0028", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/119195772.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1912626972° N, and the longitude is 25.0298295815° E.", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0029", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44407447.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.87894486° N, and the longitude is 82.77040193° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Dumetella carolinensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0030", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/165066785.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.5541895371° N, and the longitude is 88.3408582139° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Xanthocephalus xanthocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0031", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81374881.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.8267944444° N, and the longitude is 92.0857166667° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga ruticilla", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0032", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47484679.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.3823649533° N, and the longitude is 76.0622500174° W.", + "Answer Choices": [ + "(A) Pipilo erythrophthalmus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0033", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/63693494.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.412078544° N, and the longitude is 120.6563355343° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Phylloscopus borealis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0034", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104738598.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.0370764805° S, and the longitude is 172.9949694979° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Nestor notabilis", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0035", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/142617303.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.599297° N, and the longitude is 14.008117° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus corax tingitanus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0036", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/55245365.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.885° N, and the longitude is 116.824167° W.", + "Answer Choices": [ + "(A) Tadarida brasiliensis", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0037", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41193284.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.1184986622° N, and the longitude is 75.0256972457° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0038", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/125059041.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.5515646411° N, and the longitude is 21.1061451584° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Fringilla coelebs", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0039", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/79390000.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.173318771° N, and the longitude is 8.7446973846° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Sitta europaea", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0040", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/203382873.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.8269716667° N, and the longitude is 30.127075° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Garrulus glandarius", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0041", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/163933556.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.31192° N, and the longitude is 103.8144116667° E.", + "Answer Choices": [ + "(A) Cacomantis sonneratii", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0042", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/59248821.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.401277366° N, and the longitude is 80.5608100796° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Orchelimum pulchellum", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0043", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199543077.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.4409800495° N, and the longitude is 14.077151902° E.", + "Answer Choices": [ + "(A) Regulus regulus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0044", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167355156.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 11.413374797° N, and the longitude is 76.6356566313° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Sholicola major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0045", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/163567185.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 15.5595° N, and the longitude is 88.0264138333° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Turdus grayi", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0046", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39625030.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.215038748° N, and the longitude is 24.8987526337° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0047", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45536804.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.2507149722° N, and the longitude is 83.923185° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Turdus migratorius", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0048", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161806577.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.3837513999° N, and the longitude is 76.0243164003° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Dolichonyx oryzivorus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0049", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/15751297.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6142527801° N, and the longitude is 79.3877506256° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Sterna hirundo", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0050", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194543511.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.443471464° N, and the longitude is 71.4985354407° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Geothlypis trichas", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0051", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149920092.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4831671474° N, and the longitude is 1.9787688553° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Streptopelia decaocto", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0052", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76004135.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7636116667° N, and the longitude is 116.8458333333° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Megascops kennicottii", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0053", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145216177.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.48121527° N, and the longitude is 123.1156078385° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Passerina amoena", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0054", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/70742858.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.4541283333° N, and the longitude is 73.1456666667° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Pinicola enucleator", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0055", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71004570.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2417336293° N, and the longitude is 80.4617461338° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Agelaius phoeniceus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0056", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52861714.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.5993012937° N, and the longitude is 103.9124682608° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Passerina caerulea", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0057", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197518517.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.2749925801° N, and the longitude is 11.5863506868° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0058", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167192686.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.4852833571° N, and the longitude is 79.2000562325° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Empidonax alnorum", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0059", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197518730.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.9055408621° N, and the longitude is 159.5074789356° W.", + "Answer Choices": [ + "(A) Pluvialis fulva", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0060", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145711465.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.1095595552° N, and the longitude is 123.0056898775° W.", + "Answer Choices": [ + "(A) Tringa melanoleuca", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0061", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69842111.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.96090562° S, and the longitude is 117.35416536° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Zanda", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0062", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193743234.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.7611342571° S, and the longitude is 151.0702226311° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Phylloscopus collybita", + "(C) Eopsaltria australis", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0063", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/177740368.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.0089640322° N, and the longitude is 75.3001161226° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Molothrus ater", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0064", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/43150685.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.64191° N, and the longitude is 98.6259533333° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Mimus polyglottos", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0065", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/97008228.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.1084891895° N, and the longitude is 36.6049157828° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Sitta europaea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0066", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104148275.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.6947155162° S, and the longitude is 150.6855195749° E.", + "Answer Choices": [ + "(A) Cacomantis variolosus variolosus", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0067", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45290539.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.2065908689° N, and the longitude is 25.0453649378° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Passer domesticus", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0068", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120497394.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.6530763° N, and the longitude is 39.4754865° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Asio otus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0069", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171894737.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.7245795544° N, and the longitude is 83.7176471945° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Crotalus horridus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0070", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/191260383.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.3465944239° N, and the longitude is 103.7875101042° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Caprimulgus macrurus", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0071", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112721174.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.4065853729° N, and the longitude is 123.3646631241° W.", + "Answer Choices": [ + "(A) Haematopus bachmani", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0072", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/128420576.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.9357091863° N, and the longitude is 56.0178495034° E.", + "Answer Choices": [ + "(A) Asio otus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0073", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/77984583.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.0148510311° N, and the longitude is 118.3855961867° W.", + "Answer Choices": [ + "(A) Tadarida brasiliensis", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0074", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/155478845.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.9567361° N, and the longitude is 89.0033992° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga petechia", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0075", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/50898425.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.5179307° N, and the longitude is 122.5125736° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Molothrus ater", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0076", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109582818.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.3680194444° S, and the longitude is 47.5445888889° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Acanthis hornemanni", + "(C) Calidris minuta", + "(D) Prionacris erosa", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0077", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192668489.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.06399954° N, and the longitude is 84.51470898° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Sitta pusilla", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0078", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/93454893.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.3370372658° N, and the longitude is 9.7619151324° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Motacilla alba", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0079", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108792758.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.4477775422° S, and the longitude is 144.6626948733° E.", + "Answer Choices": [ + "(A) Colluricincla harmonica", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0080", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194480925.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.180184627° N, and the longitude is 5.8703607138° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Streptopelia decaocto", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0081", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/111531888.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.790414924° N, and the longitude is 37.4321408942° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Turdus merula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0082", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146867386.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.502546° N, and the longitude is 84.709555° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Hyla chrysoscelis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0083", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72202621.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.1343540048° N, and the longitude is 70.9382137656° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Lithobates sylvaticus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0084", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122407223.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.4673833333° S, and the longitude is 174.2654583333° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Egretta novaehollandiae", + "(C) Phylloscopus collybita", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0085", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103453738.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.1413622081° N, and the longitude is 98.3789439963° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Psarocolius montezuma", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0086", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200390491.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.2887201918° N, and the longitude is 83.7049048461° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Agelaius phoeniceus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0087", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69624054.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.9877616199° N, and the longitude is 77.4864277855° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Passer domesticus domesticus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0088", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45568071.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.1232276127° N, and the longitude is 8.707844156° E.", + "Answer Choices": [ + "(A) Chloris chloris", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0089", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/54171132.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1693094444° N, and the longitude is 24.9557934807° E.", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0090", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145538757.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.759379535° N, and the longitude is 104.8566719259° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Poecile atricapillus", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0091", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82903548.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.7441803692° N, and the longitude is 82.2796366217° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Junco hyemalis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0092", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96195319.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.9539588722° N, and the longitude is 137.1911284065° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Velarifictorus micado", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0093", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/133796269.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8957777406° N, and the longitude is 77.1546923213° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Corvus ossifragus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0094", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/40652358.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.32473° N, and the longitude is 99.174946° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Toxostoma curvirostre", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0095", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/187675456.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.2006657195° N, and the longitude is 79.4355724823° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Cardinalis cardinalis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0096", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/182119718.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.5144610214° S, and the longitude is 153.0923929811° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Oriolus sagittatus", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0097", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201776621.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.7650653151° N, and the longitude is 7.0218117431° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Chorthippus mollis ignifer", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0098", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/19213482.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.03059° N, and the longitude is 77.498508° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus ossifragus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0099", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/141388070.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.761523908° N, and the longitude is 83.9690675308° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Buteo lineatus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0100", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161236487.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.788749045° N, and the longitude is 83.2306730391° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Icterus spurius", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0101", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45595647.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.1648321639° N, and the longitude is 8.9458522244° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Columba palumbus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0102", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71254780.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.03143576° N, and the longitude is 88.09867738° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Cardinalis cardinalis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0103", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197794452.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.9360148836° N, and the longitude is 77.4689766717° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Corvus brachyrhynchos", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0104", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80385942.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.967591° N, and the longitude is 83.728008° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Baeolophus bicolor", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0105", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193427610.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.7765656923° N, and the longitude is 95.8788496003° W.", + "Answer Choices": [ + "(A) Oreoscoptes montanus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0106", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/142354456.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9873255743° S, and the longitude is 18.4232481912° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Arthroleptella lightfooti", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0107", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71018486.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 0.0940933333° N, and the longitude is 76.890415° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Acanthis hornemanni", + "(C) Mimus gilvus", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0108", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121494692.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.3214906382° N, and the longitude is 95.9083438006° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Spiza americana", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0109", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106237585.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.5483537256° N, and the longitude is 114.0013567427° E.", + "Answer Choices": [ + "(A) Passer montanus", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0110", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/57306028.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.9109761203° N, and the longitude is 35.9624206286° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Pelophylax ridibundus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0111", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146038004.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 7.7371803349° N, and the longitude is 98.776860828° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Eudynamys scolopaceus", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0112", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106201972.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7915099701° N, and the longitude is 116.9883267581° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0113", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/100152755.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1732452705° N, and the longitude is 24.9513062402° E.", + "Answer Choices": [ + "(A) Regulus regulus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0114", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45370688.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1947592108° N, and the longitude is 25.0242921905° E.", + "Answer Choices": [ + "(A) Turdus merula", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0115", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/91235375.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 14.8754077883° N, and the longitude is 102.0285349712° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Vanellus indicus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0116", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84874742.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.8966136521° N, and the longitude is 37.8328161037° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0117", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151591353.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.3032232003° N, and the longitude is 101.7643230434° E.", + "Answer Choices": [ + "(A) Poecile montanus", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0118", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80335589.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.8935336851° N, and the longitude is 37.8183399744° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Dendrocopos major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0119", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/97426348.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.60262° N, and the longitude is 94.447542° W.", + "Answer Choices": [ + "(A) Crotophaga sulcirostris", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0120", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105937869.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.9221132153° N, and the longitude is 97.8831115611° W.", + "Answer Choices": [ + "(A) Mareca strepera", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0121", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194675187.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Spizelloides arborea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0122", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124265385.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.3144746001° N, and the longitude is 120.3432464294° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Junco hyemalis", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0123", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/5062568.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.8506466667° N, and the longitude is 97.6995° W.", + "Answer Choices": [ + "(A) Melanerpes carolinus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0124", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/137232564.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.9933841545° N, and the longitude is 111.5630107901° W.", + "Answer Choices": [ + "(A) Cistothorus palustris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0125", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/173535720.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.0071965324° N, and the longitude is 118.2511694896° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Bubo virginianus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0126", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/114399812.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.8125523478° N, and the longitude is 76.8916453142° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Protonotaria citrea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0127", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/92135343.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 17.1359708687° N, and the longitude is 96.7851094264° W.", + "Answer Choices": [ + "(A) Spinus psaltria", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0128", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/187067742.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 0.564104° S, and the longitude is 130.516251° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Gavicalis versicolor", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0129", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/79932314.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.7785212583° N, and the longitude is 25.4442242905° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0130", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108725955.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7345726136° N, and the longitude is 73.7636035063° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Molothrus ater", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0131", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110400594.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.0053296° N, and the longitude is 8.0876593° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Alauda arvensis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0132", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196543582.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.8946507232° N, and the longitude is 20.6349216029° E.", + "Answer Choices": [ + "(A) Garrulus glandarius", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0133", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197641619.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.6160633488° N, and the longitude is 82.3250872819° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Molothrus ater", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0134", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66618575.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 20.7252083333° N, and the longitude is 103.290535° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Myiarchus tuberculifer", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0135", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120193980.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.7930417289° N, and the longitude is 92.1079864775° W.", + "Answer Choices": [ + "(A) Corvus corax", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0136", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/135805064.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.4057416667° N, and the longitude is 73.9353333333° W.", + "Answer Choices": [ + "(A) Haemorhous mexicanus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0137", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/68758838.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.991396395° S, and the longitude is 50.3004252719° W.", + "Answer Choices": [ + "(A) Tyrannus melancholicus", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0138", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96620346.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.1974310005° S, and the longitude is 46.7424489476° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Turdus leucomelas", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0139", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112062912.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.0196719472° N, and the longitude is 30.3516995377° E.", + "Answer Choices": [ + "(A) Turdus iliacus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0140", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39253985.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8744° N, and the longitude is 83.709183° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0141", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105271964.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.5219307° S, and the longitude is 68.9716054° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Poecile atricapillus", + "(C) Acanthis hornemanni", + "(D) Icterus croconotus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0142", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/38145618.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1739108937° N, and the longitude is 24.9694671006° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Cyanistes caeruleus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0143", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189996485.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.0790006786° N, and the longitude is 74.4363942837° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Spinus pinus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0144", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/53808776.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.9805426409° N, and the longitude is 119.1080904891° W.", + "Answer Choices": [ + "(A) Melospiza lincolnii", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0145", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/111055969.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.2262998174° N, and the longitude is 104.7133058243° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Vireo bellii", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0146", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205454865.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.7833166667° N, and the longitude is 82.7835277778° W.", + "Answer Choices": [ + "(A) Quiscalus major", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0147", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200051225.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.6965748° N, and the longitude is 104.919169° W.", + "Answer Choices": [ + "(A) Branta hutchinsii", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0148", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106777624.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.2789671177° S, and the longitude is 150.0898125408° E.", + "Answer Choices": [ + "(A) Atrapsalta collina", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0149", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41630721.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1752802511° N, and the longitude is 24.9141294229° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0150", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/19526638.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.6672616667° N, and the longitude is 117.8372316667° W.", + "Answer Choices": [ + "(A) Empidonax difficilis", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0151", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109212293.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.328229875° N, and the longitude is 3.7537710967° W.", + "Answer Choices": [ + "(A) Emberiza calandra", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0152", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46905844.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.31388863° N, and the longitude is 114.26607494° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Spilopelia chinensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0153", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120277190.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 13.5510199997° N, and the longitude is 89.2220315997° W.", + "Answer Choices": [ + "(A) Colinus cristatus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0154", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52583732.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7736316667° N, and the longitude is 116.8086616667° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Spizella atrogularis", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0155", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192345981.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.28281266° N, and the longitude is 1.08370846° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Streptopelia decaocto", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0156", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153708297.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4805941834° N, and the longitude is 1.9568350911° W.", + "Answer Choices": [ + "(A) Sitta europaea", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0157", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121076256.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7731531121° N, and the longitude is 16.8273055841° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Pelophylax perezi", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0158", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/181850284.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.2497061044° N, and the longitude is 121.1791299642° E.", + "Answer Choices": [ + "(A) Horornis acanthizoides concolor", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0159", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84831804.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.54940994° N, and the longitude is 120.62398959° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Microhyla butleri", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0160", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115087908.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.7980159501° N, and the longitude is 10.1723893379° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Tringa glareola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0161", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/154273259.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7430483333° N, and the longitude is 87.7233983333° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Cardinalis cardinalis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0162", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104620076.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.19261858° S, and the longitude is 138.47417286° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Eolophus roseicapilla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0163", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148440485.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.259155° S, and the longitude is 47.4529863889° E.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Poecile atricapillus", + "(C) Heterixalus alboguttatus", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0164", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/49698589.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 62.7749397392° N, and the longitude is 22.9904864657° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Actitis hypoleucos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0165", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110437351.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.8900315216° N, and the longitude is 74.0219389543° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0166", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194066812.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.6174440114° S, and the longitude is 144.954903528° E.", + "Answer Choices": [ + "(A) Ranoidea raniformis", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0167", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185552641.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.9948503923° N, and the longitude is 121.5805424379° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Hypothymis azurea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0168", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81322603.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.3467716213° N, and the longitude is 79.4339485466° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Lithobates clamitans", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0169", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153608653.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.0020025316° N, and the longitude is 114.0607554764° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Passer domesticus", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0170", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76707181.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.3646891012° N, and the longitude is 95.6294525161° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Spiza americana", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0171", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/68871273.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.6167652042° N, and the longitude is 10.4512450462° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Aegithalos caudatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0172", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103052226.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.0162630013° S, and the longitude is 61.2423094986° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Acanthis hornemanni", + "(D) Asemospiza obscura", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0173", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109240758.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.2642558369° N, and the longitude is 97.7754402377° W.", + "Answer Choices": [ + "(A) Mimus polyglottos", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0174", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199850226.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.62127363° N, and the longitude is 104.93622919° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Sturnus vulgaris", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0175", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/101678960.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9034833333° N, and the longitude is 116.4364916667° W.", + "Answer Choices": [ + "(A) Ligurotettix coquilletti", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0176", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107946228.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.5332949986° N, and the longitude is 24.787120296° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Pyrrhula pyrrhula pyrrhula", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0177", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161262088.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.210781633° N, and the longitude is 2.0892938368° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Phylloscopus collybita", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0178", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120475585.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.736846842° N, and the longitude is 30.5987614777° E.", + "Answer Choices": [ + "(A) Hippolais icterina", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0179", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/155753314.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.4941271866° N, and the longitude is 37.6893145895° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0180", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/174700613.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.7988765007° N, and the longitude is 0.0977671891° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Psittacula krameri", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0181", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/174598633.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.86388386° N, and the longitude is 120.34501387° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Hypsipetes leucocephalus", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0182", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115632857.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.368090772° N, and the longitude is 71.1468359085° W.", + "Answer Choices": [ + "(A) Icterus spurius", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0183", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103026527.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.2498121° N, and the longitude is 97.1113552° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Thryomanes bewickii", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0184", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/180670646.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.1918138889° N, and the longitude is 117.0751611111° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Artemisiospiza nevadensis", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0185", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122425474.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.44462867° N, and the longitude is 72.21843102° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Strix varia", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0186", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151383366.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Agelaius phoeniceus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0187", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69327348.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.4415241435° N, and the longitude is 82.5132039562° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Rupornis magnirostris", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0188", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196980300.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.7805842594° N, and the longitude is 121.0123216645° E.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Otus lettia glabripes", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0189", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/175292042.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.5457226063° N, and the longitude is 84.0280236111° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Ramphastos ambiguus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0190", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/27957719.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1734722222° N, and the longitude is 118.2748333333° W.", + "Answer Choices": [ + "(A) Okanagana wymorei", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0191", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/139540422.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 26.4736694634° S, and the longitude is 20.6125027049° E.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Philetairus socius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0192", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197771111.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.68417319° S, and the longitude is 172.89975793° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Phylloscopus collybita", + "(C) Haematopus unicolor", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0193", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/132719886.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.0852074277° N, and the longitude is 91.7737796023° W.", + "Answer Choices": [ + "(A) Melanerpes erythrocephalus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0194", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199568047.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.5407661612° N, and the longitude is 116.7407521212° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Euphagus cyanocephalus", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0195", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80419076.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.0371753849° N, and the longitude is 122.426679465° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Ammodramus savannarum", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0196", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85300569.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.0733549047° N, and the longitude is 96.8179428057° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Hirundo rustica", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0197", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118704178.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2434628729° N, and the longitude is 121.9152255523° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Spinus psaltria", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0198", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/135542082.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.6559366859° N, and the longitude is 17.8525813567° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Pyrrhocorax pyrrhocorax", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0199", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/26392265.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.281704° N, and the longitude is 99.042117° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Haemorhous mexicanus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0200", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167687067.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.6993706527° N, and the longitude is 25.3028345002° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Asio otus", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0201", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/32211039.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8018576417° N, and the longitude is 76.8319051452° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Eptesicus fuscus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0202", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83921444.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.2992851753° N, and the longitude is 10.7624562428° E.", + "Answer Choices": [ + "(A) Prunella modularis", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0203", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171951357.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.7487725541° N, and the longitude is 116.6954530032° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Sciurus griseus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0204", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104555492.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 8.6049597932° N, and the longitude is 82.9102849289° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Ramphastos ambiguus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0205", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185596382.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.43938865° N, and the longitude is 63.64589593° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Tamiasciurus hudsonicus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0206", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/180631967.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.695627303° N, and the longitude is 76.6759110958° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Corvus ossifragus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0207", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192567762.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.75343811° N, and the longitude is 96.85149314° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Solidago altissima", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0208", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/170188857.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.5384104179° N, and the longitude is 110.7610816509° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Icteria virens", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0209", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/63121536.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.5887690372° N, and the longitude is 119.3959573685° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Gavia immer", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0210", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/102951329.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1850904226° N, and the longitude is 8.896294125° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Corvus monedula", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0211", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108274337.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.49671013° N, and the longitude is 128.57237198° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Certhia americana", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0212", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/51005491.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.1262367653° N, and the longitude is 8.5011848222° E.", + "Answer Choices": [ + "(A) Turdus merula", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0213", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/59989052.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.0412675° N, and the longitude is 75.397252° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Corvus brachyrhynchos", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0214", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/92561123.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.4471116667° N, and the longitude is 84.2946883333° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Mimus polyglottos", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0215", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122691284.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.5896980851° N, and the longitude is 109.8090215362° W.", + "Answer Choices": [ + "(A) Hadoa duryi", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0216", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147043487.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.7644711282° N, and the longitude is 157.9324602304° W.", + "Answer Choices": [ + "(A) Himantopus mexicanus knudseni", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0217", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/70057730.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.92261302° N, and the longitude is 76.23962526° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Thryothorus ludovicianus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0218", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39248686.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.84081451° N, and the longitude is 77.46542349° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Branta canadensis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0219", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147549628.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4912487179° N, and the longitude is 1.9808036461° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Anas platyrhynchos", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0220", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151389377.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 8.1191811° N, and the longitude is 99.1013498° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Centropus sinensis", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0221", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162152652.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.1713759755° N, and the longitude is 61.3416732475° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus corax", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0222", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/187541632.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.93710908° S, and the longitude is 153.35079209° E.", + "Answer Choices": [ + "(A) Oriolus sagittatus", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0223", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/195053095.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.8151100677° N, and the longitude is 128.4822585663° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Bubo bubo", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0224", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115581994.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.9783751443° N, and the longitude is 47.2397950331° E.", + "Answer Choices": [ + "(A) Pyrrhocorax pyrrhocorax", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0225", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116661386.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.836495° S, and the longitude is 145.0975333333° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Trichoglossus moluccanus", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0226", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151033399.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.3653304551° N, and the longitude is 81.5885402262° W.", + "Answer Choices": [ + "(A) Progne subis", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0227", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/6811037.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.245043° N, and the longitude is 122.418115° W.", + "Answer Choices": [ + "(A) Haemorhous purpureus", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0228", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/172296473.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.7529821082° N, and the longitude is 2.4222340079° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Vespula germanica", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0229", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96804610.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0590480556° N, and the longitude is 120.1189594444° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Corvus corax", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0230", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/127314610.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9867255898° N, and the longitude is 92.7619624883° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Melospiza melodia", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0231", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120625194.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.0082046562° N, and the longitude is 127.8495617811° W.", + "Answer Choices": [ + "(A) Seiurus aurocapilla", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0232", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84585307.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.4944195298° N, and the longitude is 106.852378929° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Colaptes auratus", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0233", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42604967.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.9420918° N, and the longitude is 75.43329845° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Pipilo erythrophthalmus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0234", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/114350663.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.7191958716° N, and the longitude is 30.0926842913° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Linaria cannabina", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0235", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/158478230.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.9578956° N, and the longitude is 77.7066634° E.", + "Answer Choices": [ + "(A) Motacilla maderaspatensis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0236", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/184489987.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.3702382191° N, and the longitude is 5.5963677171° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Locustella luscinioides", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0237", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/20498905.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2599735581° N, and the longitude is 97.4125865638° W.", + "Answer Choices": [ + "(A) Setophaga petechia", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0238", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81625515.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.3009647159° N, and the longitude is 79.8013323919° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Charadrius vociferus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0239", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202847078.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4195272895° N, and the longitude is 1.9187078252° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Corvus monedula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0240", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/2899689.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 16.42265° S, and the longitude is 145.357622° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Ranoidea rheocola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0241", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/2007276.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.242441° N, and the longitude is 122.935496° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Agelaius phoeniceus", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0242", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69932696.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.7776523566° N, and the longitude is 12.6217752323° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Dryocopus martius", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0243", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171239793.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.1128459348° N, and the longitude is 71.2073208839° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Empidonax virescens", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0244", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202721102.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 26.3931557316° N, and the longitude is 81.8737181851° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Melanerpes carolinus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0245", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/60020952.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 20.3354152611° S, and the longitude is 40.4228233919° W.", + "Answer Choices": [ + "(A) Turdus amaurochalinus", + "(B) Poecile atricapillus", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0246", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/157322495.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.8474141091° N, and the longitude is 84.8582738773° W.", + "Answer Choices": [ + "(A) Agelaius phoeniceus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0247", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/43117924.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.6434845388° N, and the longitude is 6.262563765° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Luscinia megarhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0248", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/90177724.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.0210080945° N, and the longitude is 10.2365866676° E.", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0249", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71079831.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0360010738° N, and the longitude is 77.1154377636° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Turdus migratorius", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0250", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64904854.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.9282124964° S, and the longitude is 43.8755877658° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Turdus rufiventris", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0251", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151334276.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.3607908373° N, and the longitude is 94.2769006028° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Quiscalus quiscula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0252", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/127051012.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.6074517313° S, and the longitude is 60.7248251707° W.", + "Answer Choices": [ + "(A) Egretta thula", + "(B) Acanthis hornemanni", + "(C) Poecile atricapillus", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0253", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/91699351.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.2934639° N, and the longitude is 102.6474581° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Megatibicen tremulus", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0254", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103832077.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.1309895986° N, and the longitude is 85.8310819551° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Turdus migratorius", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0255", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/78025552.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.8381316667° N, and the longitude is 86.6433883333° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Phoenicurus phoenicurus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0256", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/65605278.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.8074494° S, and the longitude is 142.9868074° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Auscala flammea", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0257", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196883070.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7362497834° N, and the longitude is 73.7647967371° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Quiscalus quiscula", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0258", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52081020.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.4945015261° N, and the longitude is 81.2117596356° W.", + "Answer Choices": [ + "(A) Troglodytes hiemalis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0259", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109293923.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.4572405235° N, and the longitude is 80.0056009573° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Haemorhous mexicanus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0260", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153731153.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.9865899349° N, and the longitude is 88.8876317504° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Tachycineta bicolor", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0261", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22377268.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.7713083333° N, and the longitude is 83.6955083333° W.", + "Answer Choices": [ + "(A) Parkesia motacilla", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0262", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64181052.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.770255807° S, and the longitude is 58.5465371981° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Poecile atricapillus", + "(C) Fulica armillata", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0263", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/62153899.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.19047609° N, and the longitude is 76.5481853485° W.", + "Answer Choices": [ + "(A) Troglodytes aedon", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0264", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48114190.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.0371616° N, and the longitude is 122.9047315° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Pipilo maculatus", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0265", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69145959.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.3718997613° N, and the longitude is 76.5359314252° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Megaceryle alcyon", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0266", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/101273439.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.03929525° N, and the longitude is 118.59707583° W.", + "Answer Choices": [ + "(A) Larus occidentalis", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0267", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/79824483.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.7993004313° N, and the longitude is 39.3229034111° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Capreolus capreolus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0268", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189650785.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.9496527778° N, and the longitude is 138.4301916667° E.", + "Answer Choices": [ + "(A) Ornebius kanetataki", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0269", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161078292.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.0346163594° N, and the longitude is 73.194910028° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Pipilo erythrophthalmus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0270", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/98822312.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 8.7° N, and the longitude is 83.1946° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Megascops choliba", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0271", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205721438.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7376902327° N, and the longitude is 91.1429898441° W.", + "Answer Choices": [ + "(A) Melospiza melodia", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0272", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/139958049.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.683174° N, and the longitude is 97.64313° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Lithobates berlandieri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0273", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199179620.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.3921345547° S, and the longitude is 146.823595253° E.", + "Answer Choices": [ + "(A) Callocephalon fimbriatum", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0274", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/102454689.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.3609576269° N, and the longitude is 103.7771904096° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Irena puella", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0275", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185240745.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.9541240019° N, and the longitude is 105.1603279541° W.", + "Answer Choices": [ + "(A) Pseudacris maculata", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0276", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61741070.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8645782469° S, and the longitude is 151.2169189453° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Yoyetta celis", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0277", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110684075.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.5937472222° N, and the longitude is 7.6450111111° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Turdus merula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0278", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76015494.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.2420293629° S, and the longitude is 174.7886489259° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Prosthemadera novaeseelandiae novaeseelandiae", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0279", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108294135.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.0208444354° N, and the longitude is 10.2364780381° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Chloris chloris", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0280", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196087818.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 6.6775335276° N, and the longitude is 79.9201344699° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Psittacula krameri", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0281", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/20880667.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.030465° N, and the longitude is 77.498211° W.", + "Answer Choices": [ + "(A) Quiscalus quiscula", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0282", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/144593684.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.7618722571° N, and the longitude is 11.2600854412° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Parus major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0283", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/89150825.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.3166866235° N, and the longitude is 106.4806840027° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Toxostoma crissale", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0284", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/54034892.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.4409135° N, and the longitude is 8.7518029° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Phoenicurus ochruros", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0285", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/125980106.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.9828574582° N, and the longitude is 1.1401591077° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Apus apus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0286", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/29537360.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.7666541549° N, and the longitude is 11.3011628017° E.", + "Answer Choices": [ + "(A) Gryllus bimaculatus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0287", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/111546528.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.3068508933° N, and the longitude is 10.8142488065° E.", + "Answer Choices": [ + "(A) Alauda arvensis", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0288", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/102778149.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.6377708959° N, and the longitude is 122.8307493881° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cygnus buccinator", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0289", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/131871603.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.0701602997° N, and the longitude is 8.7777727997° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Cicada barbara", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0290", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80419989.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1757585057° N, and the longitude is 24.9443044753° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Hippolais icterina", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0291", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48383257.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.586082646° N, and the longitude is 127.0419300849° W.", + "Answer Choices": [ + "(A) Empidonax hammondii", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0292", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115955911.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.0978335965° N, and the longitude is 5.7167050866° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Sylvia atricapilla", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0293", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/127769754.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.9310375875° N, and the longitude is 94.6080292507° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Tyrannus tyrannus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0294", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/87319810.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.020763871° N, and the longitude is 10.236918591° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Turdus pilaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0295", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206018196.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.0567432448° N, and the longitude is 48.3104819432° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Charadrius dubius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0296", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148190322.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.4631837377° N, and the longitude is 116.868878603° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Streptopelia decaocto", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0297", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105656184.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.9532449722° N, and the longitude is 121.501366° E.", + "Answer Choices": [ + "(A) Pomatorhinus musicus", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0298", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/187798072.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.882445° N, and the longitude is 77.411595° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Sitta carolinensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0299", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118482408.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1886287168° N, and the longitude is 24.9361204582° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Curruca curruca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0300", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48950469.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.5173347692° N, and the longitude is 14.046792984° E.", + "Answer Choices": [ + "(A) Delichon urbicum urbicum", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0301", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161330460.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.0151809987° N, and the longitude is 110.6976237367° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Toxostoma rufum", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0302", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/102081579.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.7522403489° N, and the longitude is 80.5026843669° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga coronata", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0303", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47557803.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.3659092211° N, and the longitude is 78.3603543401° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Passerina cyanea", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0304", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153324429.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.3162913772° N, and the longitude is 20.9404282272° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Troglodytes troglodytes", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0305", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/13478609.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.8425170875° N, and the longitude is 101.9807717623° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Pipilo maculatus × ocai", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0306", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167483261.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.7039011681° N, and the longitude is 100.3877154824° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Cardinalis cardinalis", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0307", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/78187935.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.8168654391° N, and the longitude is 83.1056924378° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Hirundo rustica", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0308", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107129806.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.9289015167° N, and the longitude is 84.0345694241° W.", + "Answer Choices": [ + "(A) Mimus polyglottos", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0309", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104864054.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.743583194° N, and the longitude is 73.7408970483° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Buteo lineatus", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0310", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189358926.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.1393355244° N, and the longitude is 115.6642598831° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Egretta thula", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0311", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61664569.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.1808865015° N, and the longitude is 16.3887708262° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Chorthippus biguttulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0312", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204406163.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Cardinalis cardinalis", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0313", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122582711.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3186642406° N, and the longitude is 83.2375834103° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Chordeiles minor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0314", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41147859.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.5968233016° N, and the longitude is 122.3634381147° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Passer domesticus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0315", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/177528388.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.377605° N, and the longitude is 66.2003377° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Melanospiza bicolor", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0316", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202400338.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.6253149607° N, and the longitude is 96.3981425318° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Cardinalis cardinalis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0317", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/51002602.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.3109229° N, and the longitude is 20.1054918° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Garrulus glandarius", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0318", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72097173.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1737877492° N, and the longitude is 24.945127675° E.", + "Answer Choices": [ + "(A) Certhia familiaris", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0319", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73478911.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.7070666667° N, and the longitude is 77.927365° W.", + "Answer Choices": [ + "(A) Pseudacris crucifer", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0320", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47411156.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.877542° N, and the longitude is 83.685399° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0321", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45030479.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.9726836323° N, and the longitude is 77.5188541375° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Vireo flavifrons", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0322", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201296449.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.0012476754° N, and the longitude is 85.6310504497° W.", + "Answer Choices": [ + "(A) Sturnus vulgaris", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0323", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196452757.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.2501240727° N, and the longitude is 29.5712763785° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Picoides tridactylus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0324", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/168796434.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.3710586383° N, and the longitude is 6.2929022312° E.", + "Answer Choices": [ + "(A) Cicada orni", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0325", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/195152976.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.2053783238° S, and the longitude is 175.002699271° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Prosthemadera novaeseelandiae", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0326", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192574728.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.4767917027° N, and the longitude is 74.420530236° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Dryocopus pileatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0327", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/159565123.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.8500284998° N, and the longitude is 87.9645077884° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Molothrus ater", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0328", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/33643726.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.0265356848° N, and the longitude is 121.5306421384° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Hirundo rustica", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0329", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/129669154.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.225172° N, and the longitude is 61.947236° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Aegolius funereus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0330", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47963802.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.2219754982° N, and the longitude is 38.9733777375° E.", + "Answer Choices": [ + "(A) Turdus pilaris", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0331", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81306258.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.8980650098° N, and the longitude is 79.7569673136° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Vireo olivaceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0332", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106089813.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 26.1270516667° N, and the longitude is 97.9584666667° W.", + "Answer Choices": [ + "(A) Neotibicen superbus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0333", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104677756.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.1894570763° N, and the longitude is 80.81370196° W.", + "Answer Choices": [ + "(A) Melanerpes erythrocephalus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0334", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76570819.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.0432416557° N, and the longitude is 70.8134547164° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Icterus galbula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0335", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48931534.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.64007167° N, and the longitude is 11.727205° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Oriolus oriolus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0336", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153155562.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.1666550726° S, and the longitude is 153.3156789313° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Pteropus poliocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0337", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193835902.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.8823144315° N, and the longitude is 122.2682748177° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Sciurus niger", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0338", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108941748.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.7696386277° N, and the longitude is 1.3388134744° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Parus major", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0339", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81836051.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4653735° N, and the longitude is 13.5484873° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Turdus merula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0340", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/169870549.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.2121044014° N, and the longitude is 78.6879066137° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Setophaga pensylvanica", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0341", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/26804105.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.461438° N, and the longitude is 97.76337° W.", + "Answer Choices": [ + "(A) Incilius nebulifer", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0342", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/187160047.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.1868599802° N, and the longitude is 5.9205849655° W.", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0343", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151905449.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.245412° N, and the longitude is 121.6169569° E.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Pycnonotus sinensis", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0344", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/142308285.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.7943816667° N, and the longitude is 111.0135533333° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Mermiria bivittata", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0345", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116057944.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.8491118997° N, and the longitude is 60.640368° E.", + "Answer Choices": [ + "(A) Corvus corax", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0346", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199201240.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 22.3004003419° N, and the longitude is 114.1696449143° E.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Copsychus saularis", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0347", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108941983.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7392344805° N, and the longitude is 73.7402147319° W.", + "Answer Choices": [ + "(A) Pseudacris crucifer", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0348", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/35483328.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.2093566667° S, and the longitude is 146.8435413889° E.", + "Answer Choices": [ + "(A) Paracrinia haswelli", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0349", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/65594941.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.7578440833° N, and the longitude is 82.7637789722° W.", + "Answer Choices": [ + "(A) Corvus ossifragus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0350", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105710017.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.4029828739° S, and the longitude is 152.1240161174° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Manorina melanophrys", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0351", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/156608285.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.5344227135° N, and the longitude is 99.9390802813° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Euphagus carolinus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0352", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/93995796.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.6123879° N, and the longitude is 68.7269524997° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Coereba flaveola", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0353", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199373129.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.279223483° N, and the longitude is 14.7841095638° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0354", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200110053.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1805513699° N, and the longitude is 24.9494441843° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Passer domesticus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0355", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204048060.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.480704° N, and the longitude is 77.313354° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Melospiza melodia", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0356", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197552813.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.1246333859° N, and the longitude is 10.8286967129° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Delichon urbicum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0357", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42452426.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.770189204° N, and the longitude is 60.0014471635° E.", + "Answer Choices": [ + "(A) Chloris chloris", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0358", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/34659029.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 5.88845° N, and the longitude is 75.14861° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Leptodactylus fragilis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0359", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199271402.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.5998083333° N, and the longitude is 121.7317527778° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Erpornis zantholeuca", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0360", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/141730359.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.9847577728° N, and the longitude is 86.4559992403° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Sturnus vulgaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0361", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123037617.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.7535373867° N, and the longitude is 87.8258459768° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Lasiurus cinereus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0362", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/97467039.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.8312048925° N, and the longitude is 66.1097124964° W.", + "Answer Choices": [ + "(A) Anas platyrhynchos", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0363", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69053955.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.2834674819° N, and the longitude is 27.7454853414° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Garrulus glandarius", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0364", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/119217742.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.4892798803° N, and the longitude is 63.785525681° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Setophaga coronata", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0365", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200510707.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.3967155278° N, and the longitude is 8.823771788° E.", + "Answer Choices": [ + "(A) Alauda arvensis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0366", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206284536.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.7947755109° N, and the longitude is 31.8956346274° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Sturnus vulgaris", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0367", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108696937.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.9536145314° N, and the longitude is 114.2568135249° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Sturnella neglecta", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0368", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116912671.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.6127634508° N, and the longitude is 122.4499020314° W.", + "Answer Choices": [ + "(A) Vireo huttoni", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0369", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72695839.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 3.0032475° S, and the longitude is 59.9396902° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Poecile atricapillus", + "(C) Acanthis hornemanni", + "(D) Hypocnemis cantator", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0370", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/114016292.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.9484729865° N, and the longitude is 121.5008928756° E.", + "Answer Choices": [ + "(A) Sylvirana guentheri", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0371", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82048798.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9065930728° N, and the longitude is 76.121350978° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Spizella pallida", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0372", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/183058546.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.8382385507° N, and the longitude is 30.1252388059° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Dendrocopos leucotos", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0373", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/63972987.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1730364731° N, and the longitude is 24.9425607947° E.", + "Answer Choices": [ + "(A) Bombycilla garrulus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0374", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164655802.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.3556175157° N, and the longitude is 88.8759080131° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Setophaga pinus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0375", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46660976.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.6463703912° N, and the longitude is 65.7375841588° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Spizella passerina", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0376", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124449071.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.870038989° S, and the longitude is 54.1623029486° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Poecile atricapillus", + "(C) Calidris minuta", + "(D) Theristicus caudatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0377", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167063752.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.5680288384° S, and the longitude is 58.6816338135° W.", + "Answer Choices": [ + "(A) Myiopsitta monachus", + "(B) Calidris minuta", + "(C) Acanthis hornemanni", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0378", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/56752069.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2906869° N, and the longitude is 122.2621542001° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Aphelocoma californica", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0379", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82206454.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.6660771122° N, and the longitude is 120.3303380683° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Okanagana occidentalis", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0380", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/9134695.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.671644° N, and the longitude is 82.454831° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Odontoxiphidium apterum", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0381", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189130777.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.31436279° N, and the longitude is 79.65855358° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Buteo lineatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0382", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/36381316.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.6907640642° N, and the longitude is 70.6321771182° W.", + "Answer Choices": [ + "(A) Histrionicus histrionicus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0383", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107605059.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.9852521997° N, and the longitude is 122.5002494997° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Haemorhous mexicanus", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0384", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/11713819.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.0862858° N, and the longitude is 78.7833416° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Turdus migratorius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0385", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/78579142.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.2108287224° N, and the longitude is 95.540235382° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Dendrocygna autumnalis", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0386", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/21533255.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.9765194444° N, and the longitude is 87.6735222222° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Cardinalis cardinalis", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0387", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46046974.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9134002366° N, and the longitude is 76.256111394° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Troglodytes aedon", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0388", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/70510180.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.4497770747° N, and the longitude is 82.6284299266° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0389", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/160689953.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7106511417° S, and the longitude is 144.9782278797° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Trichoglossus moluccanus", + "(C) Phylloscopus collybita", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0390", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120063814.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9270102162° N, and the longitude is 93.3985184644° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Tamias striatus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0391", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/62785598.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.6552349129° S, and the longitude is 65.5616130571° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Poecile atricapillus", + "(C) Saltatricula multicolor", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0392", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/154919603.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.3083298152° N, and the longitude is 71.700126417° W.", + "Answer Choices": [ + "(A) Priotelus roseigaster", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0393", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116378696.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.9608067637° N, and the longitude is 90.0610921975° W.", + "Answer Choices": [ + "(A) Hyla cinerea", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0394", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110546026.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.8037266082° N, and the longitude is 123.0557555629° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Plectrophenax nivalis", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0395", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73166174.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.6749827603° N, and the longitude is 74.1306393549° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Calidris minuta", + "(C) Gallinula galeata", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0396", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/89888956.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.071822° N, and the longitude is 4.3373039° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus frugilegus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0397", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80206028.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.5750213692° N, and the longitude is 89.5039483226° W.", + "Answer Choices": [ + "(A) Vermivora cyanoptera", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0398", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81041853.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.8722578097° N, and the longitude is 37.4427813473° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Locustella fluviatilis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0399", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/168005252.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1827143152° S, and the longitude is 144.7116315087° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Acanthiza reguloides", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0400", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115373152.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.5487498° N, and the longitude is 90.5449717° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Passerina caerulea", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0401", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189655752.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.95938096° N, and the longitude is 120.82252971° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Dendrocitta formosae formosae", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0402", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171649607.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.56463689° N, and the longitude is 76.35913816° W.", + "Answer Choices": [ + "(A) Pipilo erythrophthalmus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0403", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/113645143.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.606423313° N, and the longitude is 79.3770313265° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Quiscalus quiscula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0404", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/158362644.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.7735734696° N, and the longitude is 21.2859410055° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Luscinia megarhynchos", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0405", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202794847.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1771305846° N, and the longitude is 3.5875439085° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Serinus serinus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0406", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122071276.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.4773211288° N, and the longitude is 28.2107722828° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla moreletti", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0407", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/160953597.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.006444753° N, and the longitude is 11.9709313983° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Aegithalos caudatus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0408", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/6802596.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.0563480728° N, and the longitude is 97.2350120256° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Icteria virens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0409", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39886816.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1527438864° N, and the longitude is 24.8799625956° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Passer domesticus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0410", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123384407.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 6.3270192079° N, and the longitude is 75.5646472208° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Synallaxis azarae", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0411", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46258773.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.66667236° N, and the longitude is 76.88420006° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Typha latifolia", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0412", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204196303.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.5085027778° N, and the longitude is 0.6926805556° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Corvus corone", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0413", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/160835627.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.6991324817° N, and the longitude is 81.9958782569° W.", + "Answer Choices": [ + "(A) Strix varia", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0414", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103174698.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.0776374414° N, and the longitude is 79.6488406085° W.", + "Answer Choices": [ + "(A) Campephilus melanoleucos", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0415", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107923907.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.863562517° S, and the longitude is 145.1278637487° E.", + "Answer Choices": [ + "(A) Acanthiza pusilla", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0416", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120340135.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.509638° N, and the longitude is 103.876371° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Acrocephalus dumetorum", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0417", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/126122939.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1916595599° N, and the longitude is 25.0303983931° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Chloris chloris", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0418", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/168801585.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.307908141° S, and the longitude is 141.6981843829° E.", + "Answer Choices": [ + "(A) Erebus purpurata", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0419", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/101552599.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.1104063325° N, and the longitude is 104.4633769984° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Melanotis caerulescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0420", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124243377.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.09096946° N, and the longitude is 83.72220833° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Corvus brachyrhynchos", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0421", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42295288.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8054714953° S, and the longitude is 150.9996517627° E.", + "Answer Choices": [ + "(A) Pteropus poliocephalus", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0422", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76086161.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1732805158° N, and the longitude is 24.9577451973° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Passer domesticus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0423", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/98225351.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.9929696719° N, and the longitude is 10.4454479367° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Motacilla alba", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0424", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161066355.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Tachycineta bicolor", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0425", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192282565.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.048905° S, and the longitude is 175.29978° E.", + "Answer Choices": [ + "(A) Prosthemadera novaeseelandiae novaeseelandiae", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0426", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197776132.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.4233168348° S, and the longitude is 149.0652547387° E.", + "Answer Choices": [ + "(A) Spilopelia chinensis", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0427", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148398969.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 5.0873425918° S, and the longitude is 39.0954791098° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Afrixalus delicatus", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0428", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/77528652.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.0879522229° N, and the longitude is 113.9226159887° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Tringa flavipes", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0429", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149638473.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.32683738° N, and the longitude is 68.28861871° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Loxia curvirostra", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0430", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202596889.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.4844219° S, and the longitude is 142.977244° E.", + "Answer Choices": [ + "(A) Zanda funerea", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0431", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108419269.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.7354270279° N, and the longitude is 140.1140105724° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Parus minor", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0432", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39597814.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.887949802° N, and the longitude is 98.4343672799° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Pyrocephalus rubinus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0433", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205989404.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2831645515° N, and the longitude is 90.3739265074° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Antrostomus vociferus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0434", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164724091.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.5059888889° N, and the longitude is 121.1153638889° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Muntiacus reevesi micrurus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0435", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/152928840.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 5.8151504846° N, and the longitude is 101.9856465477° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Copsychus pyrropygus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0436", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/192186449.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.2465026479° S, and the longitude is 153.2411407402° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Atrapsalta fuscata", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0437", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204351097.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.6822933° N, and the longitude is 81.2443254° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Parkesia motacilla", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0438", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153908732.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.1557706597° N, and the longitude is 2.1587286517° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0439", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39258286.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8668° N, and the longitude is 83.682183° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Pipilo erythrophthalmus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0440", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/175866501.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.0296288811° N, and the longitude is 113.9366580185° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Poecile gambeli", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0441", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/97427470.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.9721408526° S, and the longitude is 145.389892181° E.", + "Answer Choices": [ + "(A) Colluricincla harmonica", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0442", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194874726.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.6048017498° N, and the longitude is 84.8699624464° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Pyrrhula pyrrhula cineracea", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0443", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/175765258.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.2021783° N, and the longitude is 90.056153° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Cyanocitta cristata", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0444", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117572001.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.4397257536° N, and the longitude is 7.3100599274° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Hippolais polyglotta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0445", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121521159.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.8166477997° N, and the longitude is 65.3595944° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Agelaius phoeniceus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0446", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124535690.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.1411248993° N, and the longitude is 8.337633647° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Streptopelia turtur", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0447", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82719746.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.3031° S, and the longitude is 32.4544° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Acanthis hornemanni", + "(D) Dicrurus adsimilis adsimilis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0448", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/113013961.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.6616945° N, and the longitude is 120.4821989° W.", + "Answer Choices": [ + "(A) Agelaius phoeniceus", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0449", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/138123014.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1051354078° N, and the longitude is 121.0653068763° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Agelaius phoeniceus", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0450", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/159902869.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.2580803583° N, and the longitude is 80.7188456454° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Vireo olivaceus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0451", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/150956031.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.3098941803° N, and the longitude is 122.7923615277° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Junco hyemalis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0452", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/111055821.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.8469818738° N, and the longitude is 74.0807737475° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Acer saccharum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0453", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149753023.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.9397157054° N, and the longitude is 119.3965969434° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Pica hudsonia", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0454", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/139427539.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.6504035199° N, and the longitude is 73.5614154712° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Myiopsitta monachus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0455", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71725146.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.12885251° N, and the longitude is 81.41647879° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Lithobates sylvaticus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0456", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/67437470.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.9558578449° N, and the longitude is 122.0604633573° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Mareca americana", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0457", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109575504.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.5542879722° N, and the longitude is 27.4754259722° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Asio otus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0458", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/127570370.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.4701862973° N, and the longitude is 80.1032666482° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0459", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/59028299.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 20.4824605297° S, and the longitude is 25.1801067069° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Loxodonta africana", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0460", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/198579996.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.2776038887° N, and the longitude is 14.7596537335° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Parus major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0461", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/166613962.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.609244819° N, and the longitude is 82.3042332043° W.", + "Answer Choices": [ + "(A) Vireo griseus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0462", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/54074902.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.97963667° N, and the longitude is 113.65341167° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Himantopus mexicanus", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0463", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112055893.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1852841404° N, and the longitude is 24.941229187° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Passer domesticus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0464", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/65657423.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 10.4309364296° N, and the longitude is 84.5909342542° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Hesperoburhinus bistriatus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0465", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/157747580.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.669544181° N, and the longitude is 90.9584487045° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Limnothlypis swainsonii", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0466", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/38011275.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.705799467° N, and the longitude is 71.1362560094° W.", + "Answer Choices": [ + "(A) Corvus brachyrhynchos", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0467", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39896766.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.54671806° N, and the longitude is 80.02447314° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Thryothorus ludovicianus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0468", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118699245.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.03456386° N, and the longitude is 92.86115204° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Turdus migratorius", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0469", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/30702112.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.326919° N, and the longitude is 99.181143° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Psaltriparus minimus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0470", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106574891.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.1743022111° N, and the longitude is 81.8608547655° W.", + "Answer Choices": [ + "(A) Anhinga anhinga", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0471", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83341250.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1980594137° N, and the longitude is 118.1213045616° W.", + "Answer Choices": [ + "(A) Neotamias merriami", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0472", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61684702.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.81642111° N, and the longitude is 78.90300958° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Branta canadensis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0473", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76789521.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.797282789° N, and the longitude is 97.1221338783° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Agelaius phoeniceus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0474", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112155199.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.179280276° N, and the longitude is 24.8226127783° E.", + "Answer Choices": [ + "(A) Motacilla alba", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0475", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115430941.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.7269252677° N, and the longitude is 12.5282847131° E.", + "Answer Choices": [ + "(A) Erithacus rubecula", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0476", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194370129.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.9607883333° S, and the longitude is 174.9117133333° E.", + "Answer Choices": [ + "(A) Trichosurus vulpecula", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0477", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80252504.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.892188802° N, and the longitude is 105.1786331264° W.", + "Answer Choices": [ + "(A) Poecile gambeli", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0478", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81394995.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.4476967145° N, and the longitude is 119.6628951654° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Crotalus oreganus helleri", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0479", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/181908735.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.3810329953° N, and the longitude is 68.6325237913° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Contopus cooperi", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0480", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80956971.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5091492° N, and the longitude is 123.0901443° W.", + "Answer Choices": [ + "(A) Pipilo maculatus", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0481", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71329263.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0264261834° N, and the longitude is 76.7990493402° W.", + "Answer Choices": [ + "(A) Lithobates sphenocephalus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0482", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/184352710.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.2013842543° S, and the longitude is 151.5889166831° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Oriolus sagittatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0483", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80683208.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 21.1322227161° N, and the longitude is 86.8402719498° W.", + "Answer Choices": [ + "(A) Sciurus yucatanensis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0484", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147041344.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1810077465° N, and the longitude is 24.942984002° E.", + "Answer Choices": [ + "(A) Turdus merula", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0485", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41242267.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.185395° N, and the longitude is 93.6396583333° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Sturnella magna", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0486", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115497842.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.843242548° N, and the longitude is 84.7846665138° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Passerina cyanea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0487", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/34504119.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.3632563805° N, and the longitude is 111.9930554303° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Colaptes chrysoides", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0488", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/129696903.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.43667571° N, and the longitude is 27.40219173° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Riparia riparia", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0489", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107835960.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.977289° N, and the longitude is 81.167585° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Mimus polyglottos", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0490", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196350219.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 13.8148627148° N, and the longitude is 100.4691613922° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Culicicapa ceylonensis", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0491", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109901524.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.9579327365° S, and the longitude is 175.025622092° E.", + "Answer Choices": [ + "(A) Tadorna variegata", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0492", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/184835195.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.8656863328° S, and the longitude is 132.8151659431° E.", + "Answer Choices": [ + "(A) Territornis albilineata", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0493", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104791663.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.7817317675° S, and the longitude is 153.2594387935° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Henicopsaltria eydouxii", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0494", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/165272846.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.7315221225° N, and the longitude is 12.2499400587° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthus trivialis", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0495", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/107967310.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.0876349096° N, and the longitude is 95.2509346008° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Anser caerulescens", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0496", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147840271.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.0680773897° N, and the longitude is 84.693791193° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Tringa semipalmata", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0497", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/165449639.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.99325845° S, and the longitude is 147.4014801° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Sturnus vulgaris", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0498", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/138294750.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.8604113523° N, and the longitude is 97.364137955° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Melanerpes carolinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0499", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/163499960.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.6639972913° N, and the longitude is 73.9665930346° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Vireo olivaceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0500", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/55721086.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.6207701014° N, and the longitude is 24.0746855177° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Oecanthus pellucens", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0501", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82657019.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7522329722° N, and the longitude is 76.5118839722° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Scaphiopus holbrookii", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0502", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/155004050.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.0837384751° N, and the longitude is 70.9100313765° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Sayornis phoebe", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0503", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105142254.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9354294448° S, and the longitude is 18.4637376115° E.", + "Answer Choices": [ + "(A) Zosterops virens capensis", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0504", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153685020.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.6887055803° N, and the longitude is 127.925651595° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Anas zonorhyncha", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0505", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120150039.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.1476959083° N, and the longitude is 31.1797097209° E.", + "Answer Choices": [ + "(A) Phoenicurus ochruros", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0506", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/181024275.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.0559055556° N, and the longitude is 120.5973805556° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Dicrurus macrocercus harterti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0507", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83049706.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6280744931° N, and the longitude is 88.7801296417° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Cistothorus palustris", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0508", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199399347.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.5723492927° N, and the longitude is 73.9710444466° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Corvus ossifragus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0509", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/49547470.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.482591° N, and the longitude is 73.48643° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Corvus brachyrhynchos", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0510", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/186268769.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.547379° S, and the longitude is 48.54374° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Passer domesticus", + "(C) Acanthis hornemanni", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0511", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83782478.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.4157785229° N, and the longitude is 98.5530543319° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0512", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45359500.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.3510769606° N, and the longitude is 12.3571422796° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Erithacus rubecula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0513", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46431001.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.4963914005° N, and the longitude is 12.2386293891° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Otus scops scops", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0514", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/98006941.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.356382408° N, and the longitude is 81.8201172164° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Sturnus vulgaris", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0515", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73151534.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.92339968° N, and the longitude is 90.96484173° W.", + "Answer Choices": [ + "(A) Anaxyrus americanus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0516", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115586895.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.47671° N, and the longitude is 123.5470033333° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Cardellina pusilla", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0517", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/51978473.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.5697854418° S, and the longitude is 152.8138258102° E.", + "Answer Choices": [ + "(A) Philemon corniculatus", + "(B) Phylloscopus collybita", + "(C) Rissa tridactyla", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0518", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/18173484.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.0950127738° N, and the longitude is 80.9736000113° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Pandion haliaetus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0519", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/51912954.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.838167° N, and the longitude is 83.681985° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Hylocichla mustelina", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0520", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/125018631.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4726640885° N, and the longitude is 158.560224598° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Eumetopias jubatus jubatus", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0521", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167139326.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.0889761944° N, and the longitude is 112.4121131822° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Rhynchophanes mccownii", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0522", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116804679.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.0405030393° N, and the longitude is 40.890045102° E.", + "Answer Choices": [ + "(A) Anthus trivialis", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0523", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85765585.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1514088572° N, and the longitude is 77.6162657943° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Vireo solitarius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0524", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171842461.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.8883567811° N, and the longitude is 81.8972024708° W.", + "Answer Choices": [ + "(A) Elanoides forficatus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0525", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/183139121.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.0365824858° N, and the longitude is 93.6108690569° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Conocephalus brevipennis", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0526", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197023364.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.6009785848° S, and the longitude is 35.7190639632° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Ortalis araucuan", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0527", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124933960.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.20012° N, and the longitude is 118.31302° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Tibicinoides utahensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0528", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123093591.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.60286685° N, and the longitude is 27.53955788° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Glareola pratincola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0529", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199527724.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.6948041414° N, and the longitude is 104.9727326917° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Agelaius phoeniceus", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0530", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/114241045.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7537292323° N, and the longitude is 96.8493343537° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Leiothlypis celata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0531", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/127569580.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.2445793382° N, and the longitude is 81.7357044091° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Orthosoma brunneum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0532", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/154634575.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.4074838703° N, and the longitude is 113.4542146909° W.", + "Answer Choices": [ + "(A) Haemorhous mexicanus", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0533", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84031100.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.7565764227° N, and the longitude is 87.1173982044° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Phoenicurus phoenicurus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0534", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72902982.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5115895573° N, and the longitude is 8.9535795084° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Ardea cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0535", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/125335313.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.8072281874° N, and the longitude is 78.8623416241° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0536", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66280984.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.2716083333° N, and the longitude is 124.9253233333° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Pseudacris regilla", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0537", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176528167.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.4105083333° N, and the longitude is 122.2345583333° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Contopus sordidulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0538", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147635372.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 2.9581090007° N, and the longitude is 101.6925069605° E.", + "Answer Choices": [ + "(A) Picus puniceus", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0539", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/169876519.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6553783333° N, and the longitude is 79.3092733333° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Icterus galbula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0540", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162637058.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.39717129° N, and the longitude is 102.40232413° E.", + "Answer Choices": [ + "(A) Pellorneum bicolor", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0541", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69374406.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.37829444° N, and the longitude is 85.61875375° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Pseudacris feriarum", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0542", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/133453024.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.1297309943° N, and the longitude is 2.0743513852° W.", + "Answer Choices": [ + "(A) Erithacus rubecula", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0543", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/152854393.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.6142678019° N, and the longitude is 99.1214327887° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Toxostoma curvirostre", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0544", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123121254.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1656852105° N, and the longitude is 24.9628673315° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Haematopus ostralegus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0545", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71008967.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.1067007503° N, and the longitude is 14.3991303865° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Dendrocopos major", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0546", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116429795.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 63.5640233° N, and the longitude is 27.1966869° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0547", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/24531206.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.3471747629° N, and the longitude is 93.9008116607° W.", + "Answer Choices": [ + "(A) Gastrophryne carolinensis", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0548", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197614614.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.022365738° N, and the longitude is 76.7612006888° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Cardinalis cardinalis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0549", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/125357295.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.7438307608° N, and the longitude is 36.167842783° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Phoenicurus ochruros", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0550", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/178175575.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.3726393156° N, and the longitude is 24.3920409679° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Myrmeleotettix maculatus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0551", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/153434668.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.4042007152° N, and the longitude is 0.2882601583° W.", + "Answer Choices": [ + "(A) Chloris chloris", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0552", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72434532.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.8679256299° N, and the longitude is 121.5490771931° E.", + "Answer Choices": [ + "(A) Zhangixalus arvalis", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0553", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/6585093.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.9434083333° N, and the longitude is 125.5458133333° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Mniotilta varia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0554", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/78694532.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 16.7136695° S, and the longitude is 43.8600082° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Acanthis hornemanni", + "(C) Calidris minuta", + "(D) Icterus jamacaii", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0555", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185885522.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.37665302° S, and the longitude is 70.6141014° W.", + "Answer Choices": [ + "(A) Falco sparverius", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0556", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149820421.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.9877361111° N, and the longitude is 29.0519805556° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Dryobates minor", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0557", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46868393.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.4180835354° N, and the longitude is 46.7753781281° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Acrocephalus palustris", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0558", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197333119.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.3314642502° N, and the longitude is 74.1434699427° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Branta canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0559", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117967714.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1707543706° N, and the longitude is 24.9359656578° E.", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0560", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84534277.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.5709687854° N, and the longitude is 96.1651389767° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Melospiza melodia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0561", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/171424919.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.3427111075° N, and the longitude is 10.1901633267° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Corvus corax", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0562", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/156390294.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.5578539083° N, and the longitude is 4.7182842717° E.", + "Answer Choices": [ + "(A) Acrocephalus schoenobaenus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0563", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161361361.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.9551293508° N, and the longitude is 10.6327908486° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Cyanistes caeruleus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0564", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46168523.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.767644° N, and the longitude is 97.037318° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Cyanocitta cristata", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0565", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/31766074.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.5483507891° N, and the longitude is 82.2942765991° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus brachyrhynchos", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0566", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103629583.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4963264465° N, and the longitude is 13.4808950424° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Fulica atra", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0567", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/181046162.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.1901204997° N, and the longitude is 8.6642510997° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Serinus serinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0568", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48972081.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 13.7881368158° N, and the longitude is 89.0126404653° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Zenaida asiatica", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0569", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/12019513.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.7378748588° N, and the longitude is 123.0978046728° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Leiothlypis celata", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0570", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61393849.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.466013371° N, and the longitude is 13.3509907325° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Chorthippus brunneus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0571", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176246240.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9609522602° S, and the longitude is 18.4334469214° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Arthroleptella lightfooti", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0572", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110862506.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.60105914° N, and the longitude is 27.4663697° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Passer hispaniolensis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0573", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/25359895.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.905648° N, and the longitude is 74.381212° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Euphagus carolinus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0574", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164292733.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.3714474055° N, and the longitude is 95.623097308° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Alligator mississippiensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0575", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164473899.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.5832639848° N, and the longitude is 97.5778321985° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Passer domesticus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0576", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118100101.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.8559483° N, and the longitude is 75.4842793° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Calidris minuta", + "(D) Uromyias agilis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0577", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39847692.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1521240625° N, and the longitude is 24.8791738876° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Cyanistes caeruleus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0578", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106836986.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.2020040154° N, and the longitude is 75.066052224° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Agelaius phoeniceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0579", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/165426934.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3256171411° N, and the longitude is 122.1984043725° W.", + "Answer Choices": [ + "(A) Toxostoma redivivum", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0580", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206432689.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3670461035° N, and the longitude is 71.2606613198° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Cardinalis cardinalis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0581", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/857658.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.94626° N, and the longitude is 92.44653° W.", + "Answer Choices": [ + "(A) Orchelimum nigripes", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0582", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122725123.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 10.4453419955° N, and the longitude is 75.5215650606° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Brotogeris jugularis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0583", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/100141848.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.6016428681° S, and the longitude is 42.5920512742° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Acanthis hornemanni", + "(C) Poecile atricapillus", + "(D) Brachyteles hypoxanthus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0584", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44923393.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.89535249° N, and the longitude is 77.06039307° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Tachycineta bicolor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0585", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145712534.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7050033693° N, and the longitude is 80.5236719512° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Geothlypis philadelphia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0586", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/99559661.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.392327° N, and the longitude is 78.769045° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Cathartes aura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0587", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149057177.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1378440518° N, and the longitude is 117.860914059° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Sturnus vulgaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0588", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/155974400.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.38639238° N, and the longitude is 80.56030073° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Pseudacris crucifer", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0589", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/87873592.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.118463° N, and the longitude is 75.025598° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0590", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/91548466.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.07658883° N, and the longitude is 80.93393° W.", + "Answer Choices": [ + "(A) Diceroprocta olympusa", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0591", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/138435267.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.8650086298° N, and the longitude is 117.2171681323° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Empidonax minimus", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0592", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/53372086.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7634588° N, and the longitude is 88.0978609° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Molothrus ater", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0593", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106785588.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.3568997° S, and the longitude is 149.7689209° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Macrotristria maculicollis", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0594", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130347235.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.8770867026° N, and the longitude is 116.5066598042° W.", + "Answer Choices": [ + "(A) Pandion haliaetus", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0595", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72493779.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.6576767173° N, and the longitude is 116.4139496666° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Pseudacris cadaverina", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0596", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/175892112.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 24.1739199863° N, and the longitude is 120.789928548° E.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Spizixos semitorques", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0597", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82015264.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 61.2386732131° N, and the longitude is 21.4435368776° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Haematopus ostralegus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0598", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206588164.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.4733892981° N, and the longitude is 49.463211894° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Streptopelia decaocto", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0599", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118048121.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.2699877728° N, and the longitude is 113.826790197° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Agelaius phoeniceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0600", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72414594.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.20827662° N, and the longitude is 117.3944131° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Zalophus californianus", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0601", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84246142.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.935593621° N, and the longitude is 69.9204086915° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Roeseliana roeselii", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0602", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108061920.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.7922583333° N, and the longitude is 10.2988194444° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Poecile montanus montanus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0603", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66627755.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.2847980376° S, and the longitude is 65.6430410519° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Poecile atricapillus", + "(C) Cyanoliseus patagonus", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0604", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42641396.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.8671921207° N, and the longitude is 119.3437586797° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Pseudacris regilla", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0605", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122431803.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.812608989° N, and the longitude is 120.6704913201° E.", + "Answer Choices": [ + "(A) Hipposideros armiger terasensis", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0606", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45634291.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.8944944444° N, and the longitude is 109.1663444444° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Myiarchus tyrannulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0607", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/75347162.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.334377938° N, and the longitude is 121.9707035926° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Haemorhous mexicanus", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0608", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72917364.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1736663015° N, and the longitude is 24.9597073791° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Passer domesticus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0609", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71352914.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.9324085888° N, and the longitude is 95.9110007021° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Empidonax alnorum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0610", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167769271.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.4477465° N, and the longitude is 110.3072967° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Contopus sordidulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0611", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/198327983.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1759675815° N, and the longitude is 118.1282815664° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Sitta carolinensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0612", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200401668.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.7917629613° N, and the longitude is 116.274235825° W.", + "Answer Choices": [ + "(A) Agelaius phoeniceus", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0613", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205870122.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.1450301162° N, and the longitude is 82.2133423109° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Myiarchus crinitus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0614", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41615340.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1738915061° N, and the longitude is 24.903848851° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Haematopus ostralegus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0615", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48401434.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.8806843943° N, and the longitude is 76.143899078° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Setophaga ruticilla", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0616", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69765391.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.8167179598° N, and the longitude is 83.105097489° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0617", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108804084.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.198266945° N, and the longitude is 104.6781832378° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Zenaida asiatica", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0618", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145424287.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.6246930818° N, and the longitude is 79.961008234° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Passer domesticus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0619", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109952630.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.6233208065° N, and the longitude is 13.4563504072° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Poecile palustris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0620", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/143588137.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.5444716949° N, and the longitude is 110.1335440098° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Zenaida asiatica", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0621", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73432781.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7425873985° N, and the longitude is 75.534506254° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Turdus migratorius", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0622", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/77918943.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5088236828° N, and the longitude is 75.4435269535° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Hirundo rustica", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0623", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/169262332.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.5043093071° N, and the longitude is 84.5297155157° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Poecile atricapillus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0624", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205692777.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.6362438832° N, and the longitude is 11.7949668691° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Linaria cannabina", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0625", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/129843632.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.6888828738° N, and the longitude is 30.457421802° E.", + "Answer Choices": [ + "(A) Acrocephalus dumetorum", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0626", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/39323593.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1814272674° N, and the longitude is 24.9449254076° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Cyanistes caeruleus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0627", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/152597022.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.1453446684° N, and the longitude is 31.1723791154° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Turdus iliacus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0628", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83966660.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.0420412844° N, and the longitude is 114.1805273294° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Okanagana occidentalis", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0629", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/128801347.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.82657241° N, and the longitude is 71.33519242° W.", + "Answer Choices": [ + "(A) Cardinalis cardinalis", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0630", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69735323.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.770255807° S, and the longitude is 58.5465371981° W.", + "Answer Choices": [ + "(A) Tyrannus melancholicus", + "(B) Poecile atricapillus", + "(C) Calidris minuta", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0631", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122700883.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.2106333628° N, and the longitude is 81.2739895498° W.", + "Answer Choices": [ + "(A) Tringa melanoleuca", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0632", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105090360.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.34859° S, and the longitude is 70.35332° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Chilecicada partemporaria", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0633", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66837085.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.4022336336° N, and the longitude is 2.7063589434° E.", + "Answer Choices": [ + "(A) Branta canadensis", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0634", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96337071.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.7753499253° S, and the longitude is 170.0854413631° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Acanthisitta chloris chloris", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0635", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/43000599.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.1913819993° S, and the longitude is 138.4753854945° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Gymnorhina tibicen", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0636", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124497374.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.7415651821° N, and the longitude is 111.4390683967° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Troglodytes hiemalis", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0637", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/20445164.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.1339150614° N, and the longitude is 10.1342670992° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Mareca penelope", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0638", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/137485840.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.44618612° S, and the longitude is 150.84269533° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Phylloscopus collybita", + "(C) Scythrops novaehollandiae", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0639", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/119404084.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.4332978591° N, and the longitude is 1.5373831948° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Cepaea hortensis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0640", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22487237.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.7979644491° N, and the longitude is 100.3069976075° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Spinus psaltria", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0641", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147903182.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.1646783333° S, and the longitude is 71.7353583333° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Sylviorthorhynchus desmursii", + "(C) Calidris minuta", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0642", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109669251.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.5408743966° N, and the longitude is 123.1212419843° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Dryocopus pileatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0643", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/165400310.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.2643998629° N, and the longitude is 140.8465805095° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Horornis diphone", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0644", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115393450.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5054059625° N, and the longitude is 73.5021106248° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Colaptes auratus", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0645", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151463292.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.723586756° S, and the longitude is 150.3205801059° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Menura novaehollandiae", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0646", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72717675.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3257326336° N, and the longitude is 89.3773544382° W.", + "Answer Choices": [ + "(A) Euphagus carolinus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0647", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199047357.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.8483332474° S, and the longitude is 138.6060410115° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Hirundo neoxena", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0648", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162681018.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.74896° N, and the longitude is 79.62194° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Sturnella neglecta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0649", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201862138.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.5204904543° N, and the longitude is 98.9564202726° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Elanus caeruleus vociferus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0650", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46758105.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.2465647546° N, and the longitude is 2.0840250251° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Curruca communis", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0651", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81777499.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.3938305762° N, and the longitude is 131.951106931° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Agropsar sturninus", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0652", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148567681.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.3647575481° N, and the longitude is 90.0878420985° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Anser caerulescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0653", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61122614.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.3220882166° N, and the longitude is 2.1856063804° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Curruca communis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0654", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85241831.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.7452270423° N, and the longitude is 111.7109110986° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Passerella iliaca", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0655", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41355059.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.06226558° N, and the longitude is 75.05942695° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Dryobates pubescens", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0656", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85430689.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 64.2635662512° N, and the longitude is 23.8420302048° E.", + "Answer Choices": [ + "(A) Vanellus vanellus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0657", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52245659.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.0716094788° N, and the longitude is 11.0692914217° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Chorthippus brunneus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0658", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/56752078.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2908891° N, and the longitude is 122.2621841001° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Callipepla californica", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0659", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121215800.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.2747842464° N, and the longitude is 14.7741607949° E.", + "Answer Choices": [ + "(A) Curruca curruca", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0660", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122144873.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.0151082128° N, and the longitude is 79.3351735175° W.", + "Answer Choices": [ + "(A) Lithobates clamitans", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0661", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47890816.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0264262° N, and the longitude is 76.7990493° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Empidonax virescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0662", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66067987.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.8284829851° N, and the longitude is 99.5843299729° W.", + "Answer Choices": [ + "(A) Vireo atricapilla", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0663", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/131341625.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.9989023151° N, and the longitude is 81.2716504944° W.", + "Answer Choices": [ + "(A) Setophaga castanea", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0664", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/177581792.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.8788045913° N, and the longitude is 52.2875289258° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Calidris minuta", + "(D) Phaethornis longuemareus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0665", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/170977908.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.4142869097° N, and the longitude is 138.4422613407° E.", + "Answer Choices": [ + "(A) Anthus hodgsoni", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0666", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/37662465.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.4714233° N, and the longitude is 75.6302081° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Thryothorus ludovicianus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0667", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120374370.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.9885143131° N, and the longitude is 4.2871104553° W.", + "Answer Choices": [ + "(A) Apus apus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0668", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146869152.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 3.5958822° S, and the longitude is 73.1225523° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Acanthis hornemanni", + "(C) Myrmophylax atrothorax", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0669", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42520820.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.2110472222° N, and the longitude is 60.3175611111° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Castor canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0670", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/142847272.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0727840495° N, and the longitude is 76.7169019844° W.", + "Answer Choices": [ + "(A) Melanerpes carolinus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0671", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/89236184.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.7811346873° N, and the longitude is 71.0249714926° W.", + "Answer Choices": [ + "(A) Contopus virens", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0672", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/114446020.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.6603950421° N, and the longitude is 97.4631081988° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Agelaius phoeniceus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0673", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189572488.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.058504° N, and the longitude is 80.224534° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Parus monticolus monticolus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0674", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/150640729.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.83253734° N, and the longitude is 15.2330363° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Prunella modularis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0675", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/203298483.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.1927125786° N, and the longitude is 77.5126875422° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Agelaius phoeniceus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0676", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72555964.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.731212° N, and the longitude is 83.523268° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Buteo lineatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0677", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200082302.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.4158831845° N, and the longitude is 8.6621036567° E.", + "Answer Choices": [ + "(A) Psittacula krameri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0678", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167684331.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.8594627734° S, and the longitude is 138.6048592247° E.", + "Answer Choices": [ + "(A) Corvus mellori", + "(B) Rissa tridactyla", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0679", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73603061.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.4631003886° N, and the longitude is 24.669386254° E.", + "Answer Choices": [ + "(A) Chroicocephalus ridibundus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0680", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146198785.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 2.2558567695° N, and the longitude is 103.7396141134° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Stachyris leucotis", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0681", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176938173.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.9896484073° N, and the longitude is 49.0373591762° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Merops apiaster", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0682", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121130126.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7996671932° N, and the longitude is 74.4627240885° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Icterus galbula", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0683", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52167289.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.970578° N, and the longitude is 83.730157° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Dryobates pubescens", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0684", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/98988533.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.9511621537° N, and the longitude is 137.152355154° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Velarifictorus micado", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0685", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22435112.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.478774° N, and the longitude is 73.194569° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Passer domesticus", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0686", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81252476.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.8901983° N, and the longitude is 121.90791146° W.", + "Answer Choices": [ + "(A) Okanagana mariposa", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0687", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/102602177.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.5964616667° S, and the longitude is 58.3597383333° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Poecile atricapillus", + "(C) Elaenia mesoleuca", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0688", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/160043938.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.7990403011° N, and the longitude is 99.452531375° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Anthracoceros albirostris", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0689", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106755857.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.0761876389° S, and the longitude is 77.0517184806° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Acanthis hornemanni", + "(C) Poecile atricapillus", + "(D) Tyrannus melancholicus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0690", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/154211502.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1965747091° N, and the longitude is 118.4994090647° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Sayornis nigricans", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0691", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105517662.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.9571374657° N, and the longitude is 111.9163225409° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Circus hudsonius", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0692", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/35314147.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.8325466667° N, and the longitude is 82.19133° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Gryllus pennsylvanicus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0693", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/70559642.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.8213606209° N, and the longitude is 78.9428817846° W.", + "Answer Choices": [ + "(A) Cardinalis cardinalis", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0694", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146606148.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.2805932904° N, and the longitude is 14.7811861709° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Poecile palustris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0695", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/75898830.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.5138286182° N, and the longitude is 2.5940709561° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Turdus merula", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0696", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66260906.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.3551460388° N, and the longitude is 2.1087188176° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Carduelis carduelis", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0697", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202236896.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.1826751128° N, and the longitude is 80.6578724139° W.", + "Answer Choices": [ + "(A) Lithobates sylvaticus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0698", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45836855.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.5687477486° N, and the longitude is 101.8942552238° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Toxostoma curvirostre", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0699", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106605771.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.3913851112° N, and the longitude is 98.9844245464° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Psilopogon haemacephalus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0700", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/166976348.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.7857486048° N, and the longitude is 49.680377935° E.", + "Answer Choices": [ + "(A) Acrocephalus palustris", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0701", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108201526.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.402021875° N, and the longitude is 3.953188865° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Troglodytes troglodytes", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0702", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162225349.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.6845887348° N, and the longitude is 79.3787019954° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga pensylvanica", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0703", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/191160542.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 16.0663493833° S, and the longitude is 35.643662633° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Ptychadena taenioscelis", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0704", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/92005972.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.3431437° N, and the longitude is 90.99028569° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Baeolophus bicolor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0705", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80131884.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3382798163° N, and the longitude is 83.6373479122° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Chaetura pelagica", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0706", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202861895.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 8.6203733333° N, and the longitude is 82.9420866111° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Taraba major", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0707", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/141548854.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.8725805897° N, and the longitude is 93.1902038966° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Quiscalus quiscula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0708", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104293182.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3264122° N, and the longitude is 122.047852° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Calypte anna", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0709", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176414183.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.7982930263° N, and the longitude is 84.2510224555° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Eptesicus fuscus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0710", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/1992935.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 16.915577° S, and the longitude is 145.76444° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Haliastur indus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0711", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/6030698.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.784942° N, and the longitude is 72.609842° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Setophaga virens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0712", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118577725.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.100655° N, and the longitude is 80.471169° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Troglodytes aedon", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0713", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149495573.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.4893448338° N, and the longitude is 3.6706430885° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Sturnus vulgaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0714", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/190703632.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.6673464902° N, and the longitude is 105.104610453° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cyanocitta cristata", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0715", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44514583.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1913936063° N, and the longitude is 24.833727853° E.", + "Answer Choices": [ + "(A) Erithacus rubecula", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0716", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64040064.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.3494180393° N, and the longitude is 4.1440902714° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Pipistrellus nathusii", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0717", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/90076171.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.2255791587° N, and the longitude is 7.4495153502° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Corvus monedula", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0718", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/186255716.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 63.9201170433° N, and the longitude is 11.4283642173° E.", + "Answer Choices": [ + "(A) Passer montanus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0719", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106936474.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.2884127181° N, and the longitude is 12.3134882682° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Chorthippus biguttulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0720", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46983001.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.83315729° N, and the longitude is 14.08062769° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Pelophylax", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0721", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/157552299.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.6164483333° N, and the longitude is 0.4276866667° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Troglodytes troglodytes", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0722", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/99600910.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.5805515047° S, and the longitude is 153.239322161° E.", + "Answer Choices": [ + "(A) Psophodes olivaceus", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0723", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206733523.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.896259391° N, and the longitude is 37.849562142° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Gallinago gallinago", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0724", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46501495.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.516144° N, and the longitude is 72.943436° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Dumetella carolinensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0725", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185094813.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 5.0268149859° S, and the longitude is 119.7476283754° E.", + "Answer Choices": [ + "(A) Zosterops anomalus", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0726", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/133427985.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.1668476239° N, and the longitude is 108.4730566108° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Aeronautes saxatalis", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0727", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/20791822.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.7769482922° N, and the longitude is 80.3217626612° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Setophaga petechia aestiva", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0728", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201744760.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.7159899227° N, and the longitude is 81.7010685166° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Passer domesticus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0729", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/68713492.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.0333614167° N, and the longitude is 121.5358886667° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Hypsipetes leucocephalus", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0730", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/173249389.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.0457108416° N, and the longitude is 121.5297644311° E.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Amaurornis phoenicurus", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0731", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85203282.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.0674590106° N, and the longitude is 72.4589651731° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Troglodytes aedon", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0732", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130991800.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.12712° N, and the longitude is 106.44882° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Accipiter cooperii", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0733", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/11349095.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.9866324676° N, and the longitude is 76.9407156499° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acris crepitans", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0734", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/7889076.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6202016837° N, and the longitude is 79.3703198428° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Megaceryle alcyon", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0735", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/198718970.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.5933229666° S, and the longitude is 149.0442200884° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Merops ornatus", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0736", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/134985091.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.6471510695° N, and the longitude is 77.1766193849° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Dicrurus paradiseus", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0737", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194521812.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8929466667° N, and the longitude is 77.1778583333° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Melanerpes carolinus", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0738", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130300293.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.0285496039° N, and the longitude is 78.8956736202° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Orchelimum nigripes", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0739", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/167671553.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.962996114° N, and the longitude is 5.9765831195° E.", + "Answer Choices": [ + "(A) Sylvia borin", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0740", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/86128619.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.3756409241° N, and the longitude is 98.1200380116° W.", + "Answer Choices": [ + "(A) Aimophila ruficeps", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0741", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/43482247.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.2136646° N, and the longitude is 76.9157121° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Poecile carolinensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0742", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149886114.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7754766667° S, and the longitude is 145.3075580556° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Corvus mellori", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0743", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149321148.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.2767777661° N, and the longitude is 14.7616161106° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Periparus ater", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0744", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112981030.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.5377399942° N, and the longitude is 30.0797979977° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Phylloscopus trochilus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0745", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105638340.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3542978353° N, and the longitude is 71.1502980441° W.", + "Answer Choices": [ + "(A) Corvus brachyrhynchos", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0746", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/195809181.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.2110561° S, and the longitude is 170.88460483° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Himantopus leucocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0747", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/40319147.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.5436895723° S, and the longitude is 149.2085151442° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Cystosoma schmeltzi", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0748", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/68458696.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.912852° S, and the longitude is 28.333773° E.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Hyperolius quinquevittatus", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0749", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121476045.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.7343051304° N, and the longitude is 73.2495430611° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Catharus guttatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0750", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/195660465.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.0381861373° S, and the longitude is 49.4695313997° W.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Poecile atricapillus", + "(D) Melanerpes flavifrons", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0751", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130020239.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.0836305° N, and the longitude is 118.24617° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cervus canadensis", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0752", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162696442.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.6215175346° N, and the longitude is 34.9008732349° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Locustella fluviatilis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0753", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/78259979.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.3662508953° N, and the longitude is 95.6065762194° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Aramus guarauna", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0754", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96937311.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6379783333° N, and the longitude is 70.2560366667° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Sturnus vulgaris", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0755", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/58492594.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.364823124° S, and the longitude is 153.0768145047° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Pseudorhynchus lessonii", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0756", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185535650.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.5023444444° S, and the longitude is 142.9829333333° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Alisterus scapularis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0757", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/190610139.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.5480996874° N, and the longitude is 121.7903977075° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0758", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/172310027.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 15.9572313214° N, and the longitude is 73.9934516698° E.", + "Answer Choices": [ + "(A) Nyctibatrachus petraeus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0759", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162748583.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.0038476432° N, and the longitude is 75.1010577456° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Setophaga cerulea", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0760", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148397923.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 6.6789440615° S, and the longitude is 39.252977901° E.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Calidris minuta", + "(C) Afrixalus sylvaticus", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0761", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76178939.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9908239535° N, and the longitude is 93.1886181236° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Agelaius phoeniceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0762", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/156573442.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.169972395° N, and the longitude is 24.8259441746° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Passer montanus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0763", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/75651471.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3075526517° N, and the longitude is 3.5106929133° W.", + "Answer Choices": [ + "(A) Serinus serinus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0764", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123011837.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.0335774707° N, and the longitude is 7.8182520345° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Oecanthus dulcisonans", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0765", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71502233.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.8185250991° N, and the longitude is 10.3383723999° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Emberiza citrinella", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0766", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/49192024.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.6184619919° N, and the longitude is 73.8302784386° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Empidonax traillii", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0767", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73798219.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.057575022° N, and the longitude is 79.4177211821° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Toxostoma rufum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0768", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146198147.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.5081278195° N, and the longitude is 3.6580799661° E.", + "Answer Choices": [ + "(A) Athene noctua", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0769", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/132018309.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.8681916667° N, and the longitude is 118.405455° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Thalasseus maximus", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0770", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/57068783.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.5575231554° N, and the longitude is 30.1204599068° E.", + "Answer Choices": [ + "(A) Carduelis carduelis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0771", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189110422.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3527574508° N, and the longitude is 71.1485314742° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Thryothorus ludovicianus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0772", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64714482.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7919985158° N, and the longitude is 122.4754303598° W.", + "Answer Choices": [ + "(A) Colaptes auratus", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0773", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/161159647.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.0181866694° N, and the longitude is 122.9881737233° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Pandion haliaetus", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0774", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64672689.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.2087596082° N, and the longitude is 81.5112987919° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acanthis flammea", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0775", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147388368.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.37560346° N, and the longitude is 102.40095575° E.", + "Answer Choices": [ + "(A) Dicaeum chrysorrheum", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0776", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/21071270.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.5032169113° N, and the longitude is 94.3916210741° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Pseudacris crucifer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0777", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118143532.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.02589042° S, and the longitude is 18.36657055° E.", + "Answer Choices": [ + "(A) Acanthis hornemanni", + "(B) Poecile atricapillus", + "(C) Calidris minuta", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0778", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/196772560.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.6530241598° N, and the longitude is 12.1140126139° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Grus grus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0779", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/76696672.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.7472709603° N, and the longitude is 6.3560880348° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Gryllus campestris", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0780", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/23488099.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.555495° N, and the longitude is 86.7024916667° W.", + "Answer Choices": [ + "(A) Piranga olivacea", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0781", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/85113555.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.2884506571° N, and the longitude is 5.8990758285° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Hippolais icterina", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0782", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123995605.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.1909925331° N, and the longitude is 78.1638963616° W.", + "Answer Choices": [ + "(A) Tyrannus tyrannus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0783", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/143084711.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.8373933978° N, and the longitude is 0.3036823869° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Corvus monedula", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0784", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/198967129.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.34423935° N, and the longitude is 99.1340111293° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Vireo solitarius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0785", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/53648122.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1719813306° N, and the longitude is 24.9346828331° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Passer domesticus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0786", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200803230.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.6385673481° N, and the longitude is 120.4344748947° E.", + "Answer Choices": [ + "(A) Zhangixalus arvalis", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0787", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/74835632.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.78248027° N, and the longitude is 93.12326828° W.", + "Answer Choices": [ + "(A) Cardinalis cardinalis", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0788", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120556890.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.675225297° N, and the longitude is 112.8318378847° W.", + "Answer Choices": [ + "(A) Podiceps grisegena", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0789", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108596899.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.2332842629° N, and the longitude is 1.5401602909° W.", + "Answer Choices": [ + "(A) Corvus frugilegus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0790", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/188550547.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.4288306665° N, and the longitude is 71.3822818828° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Gryllus pennsylvanicus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0791", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162509827.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Tamiasciurus hudsonicus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0792", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/99044539.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.4301670181° S, and the longitude is 149.7630393058° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Calyptorhynchus lathami", + "(C) Phylloscopus collybita", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0793", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/205031310.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.6031948868° N, and the longitude is 121.9175369292° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Zenaida macroura", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0794", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124501421.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3062310411° N, and the longitude is 78.4042719752° W.", + "Answer Choices": [ + "(A) Hyla versicolor", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0795", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/7549268.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.7186410241° N, and the longitude is 95.5718386174° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Megatibicen pronotalis walkeri", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0796", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73744770.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.8230676° N, and the longitude is 80.341592° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Mniotilta varia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0797", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/155617730.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 25.0166291783° N, and the longitude is 77.4593934135° W.", + "Answer Choices": [ + "(A) Vireo crassirostris", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0798", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149400356.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.1874925289° N, and the longitude is 87.5341096316° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Bombycilla cedrorum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0799", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/61684125.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.81754098° N, and the longitude is 78.8996927° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Orchelimum pulchellum", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0800", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/157475722.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.0452290486° N, and the longitude is 14.529035197° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Erithacus rubecula", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0801", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/159239584.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.2155791585° N, and the longitude is 24.8334745318° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Oenanthe oenanthe", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0802", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193154383.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7518388889° N, and the longitude is 119.59105° W.", + "Answer Choices": [ + "(A) Pheucticus melanocephalus", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0803", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108407478.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.1371599768° N, and the longitude is 70.1177593168° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Cyphorhinus arada", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0804", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148990328.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2655033344° N, and the longitude is 121.9237812369° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Thryomanes bewickii", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0805", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164032386.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.889170073° N, and the longitude is 73.1667680035° W.", + "Answer Choices": [ + "(A) Melospiza melodia", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0806", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/12954884.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.0849374271° N, and the longitude is 72.6376533508° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Geothlypis philadelphia", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0807", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44531333.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.4499027778° N, and the longitude is 119.6637777778° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Melospiza melodia", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0808", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/14830108.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.5032134554° N, and the longitude is 80.8476430928° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Neotibicen winnemanna", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0809", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/96596973.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.2515284541° N, and the longitude is 6.0961249843° W.", + "Answer Choices": [ + "(A) Gryllus bimaculatus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0810", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/5236491.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.5958273246° N, and the longitude is 97.9334163666° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Hyla chrysoscelis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0811", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/178293596.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 20.3588333736° S, and the longitude is 40.299406963° W.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Rupornis magnirostris", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0812", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/179644818.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 8.24145342° S, and the longitude is 115.14204226° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Gallinula chloropus orientalis", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0813", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115714495.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.223077095° N, and the longitude is 3.8707519883° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Alauda arvensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0814", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/75026905.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.3097243784° N, and the longitude is 76.6288982984° W.", + "Answer Choices": [ + "(A) Corvus ossifragus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0815", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/50104800.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.0056126001° N, and the longitude is 71.3780832° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Contopus cooperi", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0816", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120935255.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.7478918772° N, and the longitude is 38.0449897796° E.", + "Answer Choices": [ + "(A) Dendrocopos major", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0817", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/150815372.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.5523465051° N, and the longitude is 110.7266394382° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Sayornis saya", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0818", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/51828286.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.2407253704° N, and the longitude is 2.0824439664° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Streptopelia decaocto", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0819", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/129507370.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.6061444444° N, and the longitude is 90.2623138889° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Strix varia", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0820", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/75995206.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.8801166667° N, and the longitude is 122.2891555556° W.", + "Answer Choices": [ + "(A) Lanius ludovicianus", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0821", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117949580.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 13.7629796579° N, and the longitude is 89.146250346° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Eumomota superciliosa", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0822", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/130503081.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.0531078019° N, and the longitude is 112.0836063302° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cyanocitta stelleri", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0823", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/132334457.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.9393783333° N, and the longitude is 73.90162° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Charadrius vociferus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0824", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/35692627.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 10.064624° N, and the longitude is 66.978806° W.", + "Answer Choices": [ + "(A) Engystomops pustulosus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0825", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48637698.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.1999764428° N, and the longitude is 38.9986042112° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Iduna caligata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0826", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/27549340.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.4020513889° N, and the longitude is 85.3774147222° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Ictidomys tridecemlineatus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0827", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/58365234.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.9099317711° N, and the longitude is 84.1609218344° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Buteo lineatus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0828", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/182606596.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6417285088° N, and the longitude is 3.8654771431° E.", + "Answer Choices": [ + "(A) Certhia brachydactyla", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0829", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44824858.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.5264263° N, and the longitude is 122.3240188° W.", + "Answer Choices": [ + "(A) Spinus psaltria", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0830", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/152353595.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4622327672° N, and the longitude is 4.8296606541° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0831", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/16032756.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9308508676° S, and the longitude is 18.3939531921° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Sphenoeacus afer", + "(C) Calidris minuta", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0832", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/122457078.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 56.9189333333° N, and the longitude is 60.636185° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Acrocephalus palustris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0833", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/144434784.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.4336824212° N, and the longitude is 0.2937960979° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Chroicocephalus ridibundus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0834", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146338950.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.3566369355° N, and the longitude is 2.0807539461° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Sylvia borin", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0835", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/164728668.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.6212964925° N, and the longitude is 73.0647310085° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Cardellina canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0836", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200401500.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.7397136224° N, and the longitude is 116.2177259149° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Sturnus vulgaris", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0837", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/70868852.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.6681714707° N, and the longitude is 2.9787855595° W.", + "Answer Choices": [ + "(A) Chloris chloris", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0838", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/143155477.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.70004029° N, and the longitude is 120.62613019° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Zhangixalus moltrechti", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0839", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/28463937.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.06210325° N, and the longitude is 103.4105529722° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Monochamus clamator", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0840", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/91431804.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.8771817804° N, and the longitude is 97.9841786714° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Megascops asio", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0841", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71008119.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.1651810729° N, and the longitude is 8.9459735172° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anas platyrhynchos", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0842", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/26693438.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.815456045° N, and the longitude is 70.9498217486° W.", + "Answer Choices": [ + "(A) Vireo flavifrons", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0843", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108952782.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.9557837554° N, and the longitude is 9.7711798989° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Parus major", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0844", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/101352154.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.3676372413° N, and the longitude is 71.2585797441° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0845", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145107376.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.4207561544° N, and the longitude is 79.0960514438° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Corvus brachyrhynchos", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0846", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/193755727.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3226756539° N, and the longitude is 121.8613098492° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Branta canadensis", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0847", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/40709525.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1562364843° N, and the longitude is 24.8802213849° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Passer domesticus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0848", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110342116.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3944455167° S, and the longitude is 144.2756408333° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Pachycephala pectoralis", + "(C) Morus bassanus", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0849", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206722715.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.7499789° N, and the longitude is 79.9059764° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Zenaida macroura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0850", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/71869430.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 4.6749827603° N, and the longitude is 74.1306393549° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Calidris minuta", + "(D) Spinus psaltria", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0851", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/104863859.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.9210959594° S, and the longitude is 145.3377665349° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Zanda funerea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0852", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/40125100.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1601681957° N, and the longitude is 24.8855468164° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Chloris chloris", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0853", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/183828015.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.0277739165° N, and the longitude is 30.2339947645° E.", + "Answer Choices": [ + "(A) Acheta domesticus", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0854", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/138306358.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.7607010488° N, and the longitude is 116.5490855122° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Dryobates nuttallii", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0855", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/123789924.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.3745197° N, and the longitude is 124.21172024° W.", + "Answer Choices": [ + "(A) Charadrius vociferus", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0856", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81817920.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.9993883333° N, and the longitude is 30.1110816667° E.", + "Answer Choices": [ + "(A) Turdus merula", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0857", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/200309070.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.4133333333° N, and the longitude is 86.713555° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Branta canadensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0858", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/174260925.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.9773866667° N, and the longitude is 2.36272° E.", + "Answer Choices": [ + "(A) Cicada orni", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0859", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/150212448.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.8713338515° N, and the longitude is 75.3692256567° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Lithobates sylvaticus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0860", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/172313113.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.6341486703° N, and the longitude is 120.5994071386° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Zhangixalus arvalis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0861", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46407889.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.03850079° N, and the longitude is 75.18674819° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0862", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/140830040.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.1034429487° N, and the longitude is 111.556239305° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Dryobates pubescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0863", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/162079169.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.5131177726° N, and the longitude is 90.5824258459° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Cyanocitta cristata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0864", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202650335.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.7248388889° N, and the longitude is 84.4639277778° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Molothrus ater", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0865", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73402012.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.5916378871° N, and the longitude is 118.8508639185° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Passerella iliaca", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0866", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/3179834.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.460933° N, and the longitude is 97.763329° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Lithobates berlandieri", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0867", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69623702.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8967717674° N, and the longitude is 77.4389275409° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Passer domesticus domesticus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0868", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/64978469.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.0064138833° N, and the longitude is 117.0131388833° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Anas platyrhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0869", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/105780562.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.5363908237° N, and the longitude is 77.4561888371° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Thryothorus ludovicianus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0870", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/21010938.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.4138949066° N, and the longitude is 114.1610649678° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Setophaga palmarum", + "(C) Arthroleptella lightfooti", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0871", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/45303043.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.2008841193° N, and the longitude is 25.0380635788° E.", + "Answer Choices": [ + "(A) Parus major", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0872", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/178665316.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1576072432° S, and the longitude is 18.8883441627° E.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Poecile atricapillus", + "(C) Cisticola fulvicapilla silberbauer", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0873", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/129647499.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.1749967685° S, and the longitude is 151.1197205138° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Calyptorhynchus lathami", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0874", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/41192086.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.1187347433° N, and the longitude is 75.0257109855° W.", + "Answer Choices": [ + "(A) Quiscalus quiscula", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0875", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/8770545.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.30871° N, and the longitude is 96.8026033333° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Cistothorus palustris", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0876", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81443984.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.2444512456° N, and the longitude is 2.0392362799° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fragaria vesca", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0877", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/156622892.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.1855987859° N, and the longitude is 82.3875881474° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Pipilo erythrophthalmus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0878", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148087989.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.48512459° N, and the longitude is 1.9770287722° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Corvus corone", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0879", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/185360806.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.0827069572° N, and the longitude is 106.6132904962° W.", + "Answer Choices": [ + "(A) Sturnus vulgaris", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0880", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84009043.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.3684981714° N, and the longitude is 110.623769846° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Lanius collaris", + "(D) Cervus canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0881", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/109023947.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 28.892915991° N, and the longitude is 95.6246509792° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Melanerpes carolinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0882", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/56826154.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.1802447222° N, and the longitude is 26.0896530556° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Cicada mordoganensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0883", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117755504.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.9046202399° N, and the longitude is 23.8909454866° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acrocephalus schoenobaenus", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0884", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115427580.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.271653358° N, and the longitude is 14.7699400038° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Poecile palustris", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0885", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/80414788.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.0625366667° N, and the longitude is 78.06638° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Sturnella magna", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0886", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110506075.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.89362351° N, and the longitude is 23.81467078° E.", + "Answer Choices": [ + "(A) Erithacus rubecula", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0887", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/69506102.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 0.6702611322° N, and the longitude is 36.7605513194° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Galago senegalensis braccatus", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0888", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/68629613.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.703333° N, and the longitude is 116.928056° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Parastrellus hesperus", + "(C) Lanius collaris", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0889", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/19565682.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.3819767001° N, and the longitude is 122.1767651° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Agelaius phoeniceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0890", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/67599139.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.8669507262° N, and the longitude is 97.6412729015° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0891", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/207071952.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.1532210968° N, and the longitude is 117.9324186154° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Icterus cucullatus", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0892", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/87089466.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.091875° N, and the longitude is 123.1375777778° W.", + "Answer Choices": [ + "(A) Okanagana vocalis", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0893", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116456073.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.5651567023° N, and the longitude is 25.241926387° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Botaurus stellaris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0894", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/18387074.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.402935° S, and the longitude is 153.086525° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Morus bassanus", + "(C) Phylloscopus collybita", + "(D) Atrapsalta corticina", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0895", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/9956894.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.042110838° N, and the longitude is 98.3327434895° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Toxostoma curvirostre", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0896", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/82007481.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 18.0411115062° N, and the longitude is 65.8775919632° W.", + "Answer Choices": [ + "(A) Spindalis portoricensis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0897", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/151116218.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 2.2082592561° S, and the longitude is 101.4843526892° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Pellorneum buettikoferi", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0898", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83195182.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 36.5881822141° N, and the longitude is 94.2666905513° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Pseudacris crucifer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0899", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72931143.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.515090855° N, and the longitude is 9.0988457052° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Coccothraustes coccothraustes", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0900", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/134757344.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.1287112403° N, and the longitude is 8.2715594396° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Stethophyma grossum", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0901", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176457890.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.75741478° N, and the longitude is 73.56816489° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Dryocopus pileatus", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0902", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/202013123.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 17.5484161035° N, and the longitude is 120.3760056943° E.", + "Answer Choices": [ + "(A) Phylloscopus borealis", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0903", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/87215521.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.484103499° N, and the longitude is 88.1171102264° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Antigone canadensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0904", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/188893111.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 0.6372334563° S, and the longitude is 76.1498692632° W.", + "Answer Choices": [ + "(A) Thamnomanes caesius", + "(B) Poecile atricapillus", + "(C) Acanthis hornemanni", + "(D) Calidris minuta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0905", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/97158080.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9667573689° N, and the longitude is 118.3400564171° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Myioborus pictus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0906", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/149037251.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4869041192° N, and the longitude is 1.9756504521° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Corvus corone", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0907", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197663632.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.7912659603° N, and the longitude is 122.7580395147° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Cacosternum platys", + "(C) Arthroleptella lightfooti", + "(D) Asio flammeus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0908", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/154351153.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Poecile atricapillus", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0909", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146949711.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 13.8148627148° N, and the longitude is 100.4691613922° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Rissa tridactyla", + "(D) Arundinax aedon", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0910", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/176836959.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.8638885442° N, and the longitude is 119.3892805493° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Setophaga petechia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0911", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22925320.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.80771282° N, and the longitude is 108.48891706° W.", + "Answer Choices": [ + "(A) Turdus migratorius", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0912", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121233282.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.0046116663° S, and the longitude is 20.4404599406° E.", + "Answer Choices": [ + "(A) Strongylopus grayii", + "(B) Calidris minuta", + "(C) Acanthis hornemanni", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0913", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/27924252.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 12.5899026468° S, and the longitude is 131.0531359343° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Phylloscopus collybita", + "(C) Sphecotheres vieilloti", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0914", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108866834.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.1699561378° N, and the longitude is 61.4552750676° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Chloris chloris", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0915", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148968965.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.4867938705° N, and the longitude is 1.9775088876° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0916", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/47717827.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.499864063° N, and the longitude is 46.4012822136° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Luscinia luscinia", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0917", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/203704924.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.724516° N, and the longitude is 9.195443° W.", + "Answer Choices": [ + "(A) Garrulus glandarius", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0918", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/1584596.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.80423° N, and the longitude is 114.589205° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Zenaida asiatica", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0919", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/112904232.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.4678525594° N, and the longitude is 99.1985379159° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Mimus polyglottos", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0920", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/146057818.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.32053852° N, and the longitude is 75.5844640727° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Branta canadensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0921", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/121088676.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.9008816667° N, and the longitude is 37.5973283333° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Turdus philomelos", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0922", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/83228234.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.1415209798° N, and the longitude is 118.4900716031° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Cacosternum platys", + "(D) Corvus corax", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0923", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189705498.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.3008353374° N, and the longitude is 16.294494532° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Poecile palustris", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0924", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/178397111.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.0377034538° N, and the longitude is 14.361568175° E.", + "Answer Choices": [ + "(A) Merops apiaster", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0925", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/10685150.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 19.905068631° N, and the longitude is 102.2111320496° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Vireo plumbeus", + "(C) Lanius collaris", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0926", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/110079916.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.9660257617° N, and the longitude is 3.9433592933° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Phylloscopus collybita", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0927", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/72092577.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.3613823889° N, and the longitude is 97.7385924722° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Thryothorus ludovicianus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0928", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/59777484.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.6142503457° S, and the longitude is 58.4827172969° W.", + "Answer Choices": [ + "(A) Cyanoliseus patagonus", + "(B) Poecile atricapillus", + "(C) Calidris minuta", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0929", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/106135449.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.49754171° N, and the longitude is 90.91685734° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Lanius ludovicianus", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0930", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/186606192.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.5781347091° N, and the longitude is 85.422662627° W.", + "Answer Choices": [ + "(A) Dryocopus pileatus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0931", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/180338946.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.0560560231° N, and the longitude is 61.9067501725° W.", + "Answer Choices": [ + "(A) Hirundo rustica", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0932", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/42062458.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.9063478098° N, and the longitude is 76.238942903° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Molothrus ater", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0933", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/195950529.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.7138589322° N, and the longitude is 113.9812049882° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Lanius collaris", + "(C) Cacosternum platys", + "(D) Corvus corax", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0934", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44928017.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.627274° N, and the longitude is 83.515378° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Setophaga pinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0935", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/198991153.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.68928607° S, and the longitude is 143.99707626° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Podargus strigoides", + "(C) Morus bassanus", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0936", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/73401299.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.2841844739° N, and the longitude is 89.9202456528° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Rallus crepitans", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0937", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117577825.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 49.005520733° N, and the longitude is 6.7088105902° E.", + "Answer Choices": [ + "(A) Acrocephalus arundinaceus", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0938", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/89993021.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 54.3670726134° N, and the longitude is 81.8332101838° E.", + "Answer Choices": [ + "(A) Merops apiaster", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0939", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/98667821.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.53563645° N, and the longitude is 2.1966930047° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Cygnus cygnus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0940", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/138292871.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.8061103057° N, and the longitude is 73.968582647° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Quiscalus quiscula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0941", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201326956.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.8661310495° N, and the longitude is 70.9441880252° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Haliaeetus leucocephalus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0942", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/148065539.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.1814222° N, and the longitude is 75.0299583° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Bubo virginianus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0943", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/86497386.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8266928344° N, and the longitude is 77.5465154527° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Corvus ossifragus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0944", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/150658861.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 29.1238051001° N, and the longitude is 82.2776986287° W.", + "Answer Choices": [ + "(A) Mimus polyglottos", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0945", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/86209727.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.13804° N, and the longitude is 90.5975° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Canis lupus", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0946", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204272922.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.3362519568° N, and the longitude is 6.2722507584° W.", + "Answer Choices": [ + "(A) Carduelis carduelis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0947", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/21591811.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.793560506° N, and the longitude is 34.7227406244° E.", + "Answer Choices": [ + "(A) Poecile atricapillus", + "(B) Calidris minuta", + "(C) Acanthis hornemanni", + "(D) Cercopithecus neglectus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0948", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/66553864.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.457025° N, and the longitude is 83.7277179722° W.", + "Answer Choices": [ + "(A) Spizella passerina", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0949", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197456337.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.6549045044° N, and the longitude is 73.9713916253° W.", + "Answer Choices": [ + "(A) Fulica americana", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0950", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/145250332.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.7304080921° S, and the longitude is 145.4906463941° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Rissa tridactyla", + "(C) Rusa unicolor", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0951", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/190209927.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.8151566667° N, and the longitude is 77.2972916667° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Cyanocitta cristata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0952", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/197942903.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 32.0419161824° S, and the longitude is 52.2560062597° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Physalaemus biligonigerus", + "(C) Acanthis hornemanni", + "(D) Poecile atricapillus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0953", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/118541924.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 53.9068073984° N, and the longitude is 106.0286674779° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Setophaga palmarum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0954", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/63113660.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 45.5093517966° N, and the longitude is 73.4548568057° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Sciurus carolinensis", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0955", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116288048.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.88452° N, and the longitude is 5.789845° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Aegithalos caudatus", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0956", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/135159904.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 44.2433412487° N, and the longitude is 72.4090395608° W.", + "Answer Choices": [ + "(A) Branta canadensis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0957", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/37025818.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.642981603° S, and the longitude is 172.487802431° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Anthornis melanura melanura", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0958", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/43703600.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.9676210755° N, and the longitude is 83.7291794633° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0959", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147978362.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 27.3049537345° S, and the longitude is 58.5130134968° W.", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Trogon surrucura", + "(C) Poecile atricapillus", + "(D) Acanthis hornemanni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0960", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/81336524.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.7929333333° N, and the longitude is 135.1719166667° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Arthroleptella lightfooti", + "(C) Empidonax hammondii", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0961", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/147160628.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 1.3962002024° N, and the longitude is 103.8849434907° E.", + "Answer Choices": [ + "(A) Phylloscopus collybita", + "(B) Morus bassanus", + "(C) Acrocephalus bistrigiceps", + "(D) Rissa tridactyla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0962", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/203552864.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.1122318909° S, and the longitude is 147.3420406302° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Morus bassanus", + "(D) Trichoglossus moluccanus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0963", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/103916888.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 33.0184824122° S, and the longitude is 150.033069402° E.", + "Answer Choices": [ + "(A) Rissa tridactyla", + "(B) Phylloscopus collybita", + "(C) Ranoidea wilcoxii", + "(D) Morus bassanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0964", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/188139092.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 38.6692783333° N, and the longitude is 77.288255° W.", + "Answer Choices": [ + "(A) Thryothorus ludovicianus", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0965", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/117948348.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 9.6469138424° N, and the longitude is 77.176669991° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Dicrurus paradiseus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0966", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/52246581.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 10.09672866° N, and the longitude is 83.48090143° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Oophaga pumilio", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0967", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/21922781.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 35.73358° N, and the longitude is 119.59706° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Quiscalus mexicanus", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0968", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/194029371.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.2802293504° N, and the longitude is 72.3484616546° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Sayornis saya", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0969", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/126430516.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.9463013536° N, and the longitude is 76.440047717° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Passerina cyanea", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0970", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/115936922.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.0732108383° N, and the longitude is 118.2287381218° W.", + "Answer Choices": [ + "(A) Mimus polyglottos", + "(B) Lanius collaris", + "(C) Arthroleptella lightfooti", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0971", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/126603221.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 60.1828332511° N, and the longitude is 24.9557241478° E.", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0972", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/22971009.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 34.4267° N, and the longitude is 117.8697° W.", + "Answer Choices": [ + "(A) Cacosternum platys", + "(B) Lanius collaris", + "(C) Neduba castanea", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0973", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/201280251.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.4072971847° N, and the longitude is 122.1512308439° W.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Corvus corax", + "(C) Cacosternum platys", + "(D) Arthroleptella lightfooti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0974", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/92961927.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.5339616667° N, and the longitude is 95.77983° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Orchelimum erythrocephalum", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0975", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/159805401.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.5754593393° N, and the longitude is 105.0860105082° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Anaxyrus woodhousii", + "(D) Lanius collaris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0976", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/44247791.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 23.0011790634° N, and the longitude is 121.3149385867° E.", + "Answer Choices": [ + "(A) Lanius collaris", + "(B) Arthroleptella lightfooti", + "(C) Polypedates braueri", + "(D) Cacosternum platys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0977", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/59898267.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.9722683333° N, and the longitude is 44.3448533333° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Nyctalus noctula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0978", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/46522958.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.3411951169° N, and the longitude is 12.3520397851° E.", + "Answer Choices": [ + "(A) Turdus merula", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Anthornis melanura melanura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0979", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/168039518.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 6.3529263316° N, and the longitude is 75.5201639313° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Synallaxis albescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0980", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/191059877.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.3730130003° N, and the longitude is 80.3120144784° W.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Lasiurus borealis", + "(C) Anthornis melanura melanura", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0981", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/188896902.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 59.8942159572° N, and the longitude is 30.4297766089° E.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Bombycilla garrulus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0982", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/170515826.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 51.33361526° N, and the longitude is 12.34922328° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Fringilla coelebs gengleri", + "(D) Fringilla coelebs", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0983", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/189264346.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 40.7750548097° N, and the longitude is 74.1869911552° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Mimus polyglottos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0984", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/124388582.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 47.8947569° N, and the longitude is 2.4133687° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Corvus monedula", + "(C) Fringilla coelebs gengleri", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0985", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/29355920.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 42.2659733825° N, and the longitude is 83.0777533208° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Fringilla coelebs gengleri", + "(C) Anthornis melanura melanura", + "(D) Myiarchus crinitus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0986", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/27356770.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 31.234298° N, and the longitude is 92.6090544° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Hyla chrysoscelis", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0987", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/206438501.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 55.6892490273° N, and the longitude is 37.7974279225° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Acridotheres tristis tristis", + "(C) Turdus merula", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0988", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/108939648.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 37.199888538° N, and the longitude is 78.4502209425° W.", + "Answer Choices": [ + "(A) Lithobates sphenocephalus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0989", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/24944313.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 43.119416° N, and the longitude is 79.239421° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Hirundo rustica", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0990", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/204997322.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 39.3546520535° N, and the longitude is 84.2014866285° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Turdus migratorius", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0991", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/181612638.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 46.6485924663° N, and the longitude is 13.3973849126° E.", + "Answer Choices": [ + "(A) Psophus stridulus", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Fringilla coelebs gengleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0992", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/77243452.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 41.3225634262° N, and the longitude is 8.6669028301° W.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Sylvia atricapilla", + "(D) Acridotheres tristis tristis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0993", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/48735404.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.7704718988° N, and the longitude is 60.0015581399° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Anthornis melanura melanura", + "(C) Acridotheres tristis tristis", + "(D) Carpodacus erythrinus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0994", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/84997848.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 52.6685139232° N, and the longitude is 1.9413415311° W.", + "Answer Choices": [ + "(A) Acridotheres tristis tristis", + "(B) Anthornis melanura melanura", + "(C) Fringilla coelebs gengleri", + "(D) Turdus philomelos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0995", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/18995029.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 30.3502953975° S, and the longitude is 153.0776222689° E.", + "Answer Choices": [ + "(A) Morus bassanus", + "(B) Rissa tridactyla", + "(C) Phylloscopus collybita", + "(D) Dicrurus bracteatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0996", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/116360553.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 48.5801003594° N, and the longitude is 123.3707015311° W.", + "Answer Choices": [ + "(A) Arthroleptella lightfooti", + "(B) Cacosternum platys", + "(C) Lanius collaris", + "(D) Agelaius phoeniceus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0997", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/199659422.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 50.0133972167° N, and the longitude is 36.1635278333° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Corvus corax", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0998", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/182498518.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 57.3188633333° N, and the longitude is 64.954405° E.", + "Answer Choices": [ + "(A) Anthornis melanura melanura", + "(B) Fringilla coelebs gengleri", + "(C) Acridotheres tristis tristis", + "(D) Caragana arborescens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + }, + { + "Question_id": "Species Distribution Prediction/0999", + "Images": [ + "raw/Biosphere/Species_Distribution_Prediction/TaxaBench8k/sat_images/sentinel/120966143.jpeg" + ], + "Text": "Which species is most likely to live in the region shown at the image? The latitude is 64.713074171° N, and the longitude is 24.5178922975° E.", + "Answer Choices": [ + "(A) Fringilla coelebs gengleri", + "(B) Acridotheres tristis tristis", + "(C) Anthornis melanura melanura", + "(D) Curruca curruca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Biosphere", + "L2-task": "Species Distribution Prediction", + "L3-task": "Reasoning", + "L4-task": "Species Distribution Prediction", + "Dataset": "TaxaBench8k", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Vegetation_monitoring/Reasoning/Fractional_vegetation_cover_estimation.json b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Fractional_vegetation_cover_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..6692f4f69a6efb90a1493e39be6d0917e9e0ba7e --- /dev/null +++ b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Fractional_vegetation_cover_estimation.json @@ -0,0 +1,8102 @@ +[ + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0000", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0001", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0002", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0003", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0004", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0005", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0006", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0007", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0008", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0009", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0010", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0011", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0012", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0013", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0014", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0015", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0016", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0017", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0018", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0019", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0020", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0021", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0022", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0023", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0024", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0025", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0026", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0027", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0028", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0029", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0030", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0031", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0032", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0033", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0034", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0035", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0036", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0037", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0038", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0039", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0040", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0041", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0042", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0043", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0044", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0045", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0046", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0047", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0048", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0049", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0050", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0051", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0052", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0053", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0054", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0055", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0056", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0057", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0058", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0059", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0060", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0061", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0062", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0063", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0064", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0065", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0066", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0067", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0068", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0069", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0070", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0071", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0072", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0073", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0074", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0075", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0076", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0077", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0078", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0079", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0080", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0081", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0082", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0083", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0084", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0085", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0086", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0087", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0088", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0089", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0090", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0091", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0092", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0093", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0094", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0095", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0096", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0097", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0098", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0099", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0100", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0101", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0102", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0103", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0104", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0105", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0106", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0107", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0108", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0109", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0110", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0111", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0112", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0113", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0114", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0115", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0116", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0117", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0118", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0119", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0120", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0121", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0122", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0123", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0124", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0125", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0126", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0127", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0128", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0129", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0130", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0131", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0132", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0133", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0134", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0135", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0136", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0137", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0138", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0139", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0140", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0141", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0142", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0143", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0144", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0145", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0146", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0147", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0148", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0149", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0150", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0151", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0152", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0153", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0154", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0155", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0156", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0157", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0158", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0159", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0160", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0161", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0162", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0163", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0164", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0165", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0166", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0167", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0168", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0169", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0170", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0171", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0172", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0173", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0174", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0175", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0176", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0177", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0178", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0179", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0180", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0181", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0182", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0183", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0184", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0185", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0186", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0187", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0188", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0189", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0190", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0191", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0192", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0193", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0194", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0195", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0196", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0197", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0198", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0199", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0200", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0201", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0202", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0203", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0204", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0205", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0206", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0207", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0208", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0209", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0210", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0211", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0212", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0213", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0214", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0215", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0216", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0217", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0218", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0219", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0220", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0221", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0222", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0223", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0224", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0225", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0226", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0227", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0228", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0229", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0230", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0231", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0232", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0233", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0234", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0235", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0236", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0237", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0238", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0239", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0240", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0241", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0242", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0243", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0244", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0245", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0246", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0247", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0248", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0249", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0250", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0251", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0252", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0253", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0254", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0255", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0256", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0257", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0258", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0259", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0260", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0261", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0262", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0263", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0264", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0265", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0266", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0267", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0268", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0269", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0270", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0271", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0272", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0273", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0274", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0275", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0276", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0277", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0278", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0279", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0280", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0281", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0282", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0283", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0284", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0285", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0286", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0287", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0288", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0289", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0290", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0291", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0292", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0293", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0294", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0295", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0296", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0297", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0298", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Fractional vegetation cover estimation/0299", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Fractional vegetation cover in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Fractional vegetation cover estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.25", + "(B) 0.25-0.5", + "(C) 0.5-0.75", + "(D) 0.75-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band07.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Vegetation_monitoring/Reasoning/Leaf_area_index_estimation.json b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Leaf_area_index_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..ba93ab28c961c3e6c3c3a892ed89a2d607dd4e51 --- /dev/null +++ b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Leaf_area_index_estimation.json @@ -0,0 +1,8102 @@ +[ + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0000", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0001", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0002", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0003", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0004", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0005", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0006", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0007", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0008", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0009", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0010", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0011", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0012", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0013", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0014", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0015", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0016", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0017", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0018", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0019", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0020", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0021", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0022", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0023", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0024", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0025", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0026", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0027", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0028", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0029", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0030", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0031", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0032", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0033", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0034", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0035", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0036", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0037", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0038", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0039", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0040", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0041", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0042", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0043", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0044", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0045", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0046", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0047", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0048", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0049", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0050", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0051", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0052", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0053", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0054", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0055", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0056", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0057", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0058", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0059", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0060", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0061", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0062", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0063", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0064", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0065", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0066", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0067", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0068", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0069", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0070", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0071", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0072", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0073", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0074", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0075", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0076", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0077", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0078", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0079", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0080", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0081", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0082", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0083", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0084", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0085", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0086", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0087", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0088", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0089", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0090", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0091", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0092", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0093", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0094", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0095", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0096", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0097", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0098", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0099", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0100", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0101", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0102", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0103", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0104", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0105", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0106", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0107", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0108", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0109", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0110", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0111", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0112", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0113", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0114", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0115", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0116", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0117", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0118", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0119", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0120", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0121", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0122", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0123", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0124", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0125", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0126", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0127", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0128", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0129", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0130", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0131", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0132", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0133", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0134", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0135", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0136", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0137", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0138", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0139", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0140", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0141", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0142", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0143", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0144", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0145", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0146", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0147", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0148", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0149", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0150", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0151", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0152", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0153", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0154", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0155", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0156", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0157", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0158", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0159", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0160", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0161", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0162", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0163", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0164", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0165", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0166", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0167", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0168", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0169", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0170", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0171", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0172", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0173", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0174", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0175", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0176", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0177", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0178", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0179", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0180", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0181", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0182", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0183", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0184", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0185", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0186", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0187", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0188", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0189", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0190", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0191", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0192", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0193", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0194", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0195", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0196", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0197", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0198", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0199", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0200", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0201", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0202", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0203", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0204", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0205", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0206", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0207", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0208", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0209", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0210", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0211", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0212", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0213", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0214", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0215", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0216", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0217", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0218", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0219", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0220", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0221", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0222", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0223", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0224", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0225", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0226", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0227", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0228", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0229", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0230", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0231", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0232", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0233", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0234", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0235", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0236", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0237", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0238", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0239", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0240", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0241", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0242", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0243", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0244", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0245", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0246", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0247", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0248", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0249", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0250", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0251", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0252", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0253", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0254", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0255", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0256", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0257", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0258", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0259", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0260", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0261", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0262", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0263", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0264", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0265", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0266", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0267", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0268", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0269", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0270", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0271", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0272", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0273", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0274", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0275", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0276", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0277", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0278", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0279", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0280", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0281", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0282", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0283", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0284", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0285", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0286", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0287", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0288", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0289", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0290", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0291", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0292", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0293", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0294", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0295", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0296", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0297", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0298", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Leaf area index estimation/0299", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. How is the Leaf Area Index in this area?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Leaf area index estimation", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) 0-0.5", + "(B) 0.5-1", + "(C) 1-2", + "(D) 2-10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band07.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Biosphere/Vegetation_monitoring/Reasoning/Peak_vegetation_coverage_area_grounding.json b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Peak_vegetation_coverage_area_grounding.json new file mode 100644 index 0000000000000000000000000000000000000000..3cc74d1171663cee7a0f3d9a76819e59bd36b7b7 --- /dev/null +++ b/jsons/Biosphere/Vegetation_monitoring/Reasoning/Peak_vegetation_coverage_area_grounding.json @@ -0,0 +1,8102 @@ +[ + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0000", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_1_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0001", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_2_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0002", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_3_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0003", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_4_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0004", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_5_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0005", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_6_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0006", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_7_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0007", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_8_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0008", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_9_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0009", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_10_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0010", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_11_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0011", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_12_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0012", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_13_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0013", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_14_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0014", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_15_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0015", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_16_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0016", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_17_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0017", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_18_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0018", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_19_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0019", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_20_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0020", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_21_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0021", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_22_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0022", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_23_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0023", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_24_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0024", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_25_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0025", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_26_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0026", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_27_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0027", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_28_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0028", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_29_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0029", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_30_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0030", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_31_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0031", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_32_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0032", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_33_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0033", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_34_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0034", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_35_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0035", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_36_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0036", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_37_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0037", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_38_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0038", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_39_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0039", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_40_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0040", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_41_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0041", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_42_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0042", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_43_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0043", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_44_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0044", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_45_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0045", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_46_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0046", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_47_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0047", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_48_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0048", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_49_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0049", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_50_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0050", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_51_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0051", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_52_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0052", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_53_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0053", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_54_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0054", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_55_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0055", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_56_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0056", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_57_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0057", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_58_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0058", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_59_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0059", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_60_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0060", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_61_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0061", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_62_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0062", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_63_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0063", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_64_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0064", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_65_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0065", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_66_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0066", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_67_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0067", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_68_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0068", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_69_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0069", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_70_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0070", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_71_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0071", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_72_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0072", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_73_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0073", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_74_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0074", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_75_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0075", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_76_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0076", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_77_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0077", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_78_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0078", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_79_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0079", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_80_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0080", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_81_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0081", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_82_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0082", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_83_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0083", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_84_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0084", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_85_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0085", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_86_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0086", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_87_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0087", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_88_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0088", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_89_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0089", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_90_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0090", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_91_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0091", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_92_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0092", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_93_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0093", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_94_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0094", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_95_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0095", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_96_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0096", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_97_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0097", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_98_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0098", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_99_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0099", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_100_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0100", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_101_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0101", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_102_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0102", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_103_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0103", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_104_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0104", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_105_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0105", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_106_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0106", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_107_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0107", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_108_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0108", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_109_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0109", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_110_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0110", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_111_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0111", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_112_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0112", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_113_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0113", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_114_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0114", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_115_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0115", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_116_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0116", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_117_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0117", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_118_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0118", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_119_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0119", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_120_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0120", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_121_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0121", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_122_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0122", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_123_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0123", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_124_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0124", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_125_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0125", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_126_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0126", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_127_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0127", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_128_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0128", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_129_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0129", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_130_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0130", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_131_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0131", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_132_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0132", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_133_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0133", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_134_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0134", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_135_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0135", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_136_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0136", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_137_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0137", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_138_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0138", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_139_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0139", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_140_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0140", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_141_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0141", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_142_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0142", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_143_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0143", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_144_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0144", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_145_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0145", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_146_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0146", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_147_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0147", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_148_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0148", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_149_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0149", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_150_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0150", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_151_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0151", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_152_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0152", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_153_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0153", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_154_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0154", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_155_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0155", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_156_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0156", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_157_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0157", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_158_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0158", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_159_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0159", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_160_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0160", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_161_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0161", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_162_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0162", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_163_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0163", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_164_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0164", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_165_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0165", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_166_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0166", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_167_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0167", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_168_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0168", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_169_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0169", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_170_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0170", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_171_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0171", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_172_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0172", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_173_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0173", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_174_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0174", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_175_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0175", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_176_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0176", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_177_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0177", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_178_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0178", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_179_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0179", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_180_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0180", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_181_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0181", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_182_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0182", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_183_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0183", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_184_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0184", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_185_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0185", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_186_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0186", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_187_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0187", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_188_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0188", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_189_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0189", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_190_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0190", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_191_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0191", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_192_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0192", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_193_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0193", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_194_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0194", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_195_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0195", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_196_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0196", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_197_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0197", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_198_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0198", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_199_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0199", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_200_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0200", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_201_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0201", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_202_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0202", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_203_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0203", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_204_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0204", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_205_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0205", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_206_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0206", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_207_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0207", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_208_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0208", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_209_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0209", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_210_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0210", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_211_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0211", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_212_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0212", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_213_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0213", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_214_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0214", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_215_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0215", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_216_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0216", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_217_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0217", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_218_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0218", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_219_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0219", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_220_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0220", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_221_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0221", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_222_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0222", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_223_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0223", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_224_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0224", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_225_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0225", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_226_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0226", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_227_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0227", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_228_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0228", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_229_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0229", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_230_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0230", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_231_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0231", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_232_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0232", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_233_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0233", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_234_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0234", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_235_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0235", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_236_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0236", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_237_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0237", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_238_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0238", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_239_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0239", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_240_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0240", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_241_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0241", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_242_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0242", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_243_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0243", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_244_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0244", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_245_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0245", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_246_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0246", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_247_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0247", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_248_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0248", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_249_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0249", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_250_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0250", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_251_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0251", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_252_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0252", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_253_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0253", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_254_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0254", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_255_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0255", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_256_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0256", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_257_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0257", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_258_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0258", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_259_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0259", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_260_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0260", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_261_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0261", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_262_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0262", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_263_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0263", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_264_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0264", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_265_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0265", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_266_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0266", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_267_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0267", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_268_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0268", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_269_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0269", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_270_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0270", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_271_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0271", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_272_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0272", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_273_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0273", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_274_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0274", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_275_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0275", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_276_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0276", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_277_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0277", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_278_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0278", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_279_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0279", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_280_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0280", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_281_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0281", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_282_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0282", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_283_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0283", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_284_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0284", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_285_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0285", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_286_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0286", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_287_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0287", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_288_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0288", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_289_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0289", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_290_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0290", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_291_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0291", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_292_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0292", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_293_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0293", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_294_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0294", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_295_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0295", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_296_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0296", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_297_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0297", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_298_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0298", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_299_band07.jpg" + ] + }, + { + "Question_id": "Biosphere/Vegetation monitoring/Reasoning/Peak vegetation coverage area grounding/0299", + "Question Type": "Single Choice", + "Text": "The input 7 images are the band 1-7 images of the MODIS satellite. The pixel values are the reflectance multiplied by 255. Which region within the image has the highest Fractional vegetation cover?", + "L1-task": "Biosphere", + "L2-task": "Vegetation monitoring", + "L3-task": "Reasoning", + "L4-task": "Peak vegetation coverage area grounding", + "Dataset": "GLASS", + "Answer Choices": [ + "(A) Top Left", + "(B) Top Right", + "(C) Bottom Left", + "(D) Bottom Right", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band01.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band02.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band03.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band04.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band05.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band06.jpg", + "raw/Biosphere/Vegetation monitoring/MODIS/GEE_patches_300_band07.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Most_likely_species_to_occur.json b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Most_likely_species_to_occur.json new file mode 100644 index 0000000000000000000000000000000000000000..4ff81f4b6a80621940c162d7b3a9aa243aa7ce49 --- /dev/null +++ b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Most_likely_species_to_occur.json @@ -0,0 +1,18902 @@ +[ + { + "Question_id": "Most likely species to occur/0000", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.216366 and latitude -0.418769 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tockus deckeni", + "(B) Mirafra africana", + "(C) Alopochen aegyptiaca", + "(D) Batis minor", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791999_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0001", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.591984 and latitude -0.251026 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.80 degrees. The mean diurnal range is 11.81 degrees. The isothermality is 79.31. The temperature seasonality (100 times the standard deviation) is 73.89. The max temperature of the warmest month is 18.69 degrees. The min temperature of the coldest month is 3.80 degrees. The temperature annual range is 14.89 degrees. The mean temperature of the wettest quarter is 11.73 degrees. The mean temperature of the driest quarter is 10.85 degrees. The mean temperature of the warmest quarter is 11.73 degrees. The mean temperature of the coldest quarter is 9.91 degrees. The annual precipitation is 1282.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 37.0 mm. The precipitation seasonality (coefficient of variation) is 35.95. The precipitation of the wettest quarter is 424.0 mm. The precipitation of the driest quarter is 175.0 mm. The precipitation of the warmest quarter is 424.0 mm. The precipitation of the coldest quarter is 325.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Ceryle rudis", + "(C) Nilaus afer", + "(D) Strix woodfordii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264913_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0002", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724232 and latitude -0.477635 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chrysococcyx cupreus", + "(B) Laniarius funebris", + "(C) Pternistis jacksoni", + "(D) Cisticola hunteri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10216638_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0003", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084390 and latitude -0.308472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Creatophora cinerea", + "(B) Spilopelia senegalensis", + "(C) Numenius phaeopus", + "(D) Riparia riparia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8216888_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0004", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.734492 and latitude -3.991614 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Poicephalus gulielmi", + "(B) Ploceus heuglini", + "(C) Treron calvus", + "(D) Upupa epops", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16837097_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0005", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.112115 and latitude -0.510023 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus castaneiceps", + "(B) Nigrita canicapillus", + "(C) Actitis hypoleucos", + "(D) Falco biarmicus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19033567_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0006", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.392700 and latitude -0.635840 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circaetus pectoralis", + "(B) Burhinus vermiculatus", + "(C) Balearica regulorum", + "(D) Chlidonias hybrida", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120392_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0007", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.077993 and latitude -0.299696 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Saxicola torquatus", + "(C) Falco rupicoloides", + "(D) Myrmecocichla nigra", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7852020_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0008", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375457 and latitude 0.607683 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sula dactylatra", + "(B) Ciconia nigra", + "(C) Numida meleagris", + "(D) Glareola nuchalis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15843032_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0009", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.525207 and latitude -0.617251 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthreptes rectirostris", + "(B) Argya rubiginosa", + "(C) Vanellus melanopterus", + "(D) Oenanthe cypriaca", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294819_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0010", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.374544 and latitude 0.606404 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cichladusa guttata", + "(B) Crithagra reichenowi", + "(C) Centropus monachus", + "(D) Poeoptera stuhlmanni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13962733_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0011", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.245280 and latitude 2.563797 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.31 degrees. The mean diurnal range is 14.24 degrees. The isothermality is 88.89. The temperature seasonality (100 times the standard deviation) is 62.26. The max temperature of the warmest month is 36.33 degrees. The min temperature of the coldest month is 20.31 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 29.02 degrees. The mean temperature of the driest quarter is 28.06 degrees. The mean temperature of the warmest quarter is 29.08 degrees. The mean temperature of the coldest quarter is 27.57 degrees. The annual precipitation is 246.0 mm. The precipitation of the wettest month is 56.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 70.66. The precipitation of the wettest quarter is 121.0 mm. The precipitation of the driest quarter is 28.0 mm. The precipitation of the warmest quarter is 92.0 mm. The precipitation of the coldest quarter is 40.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis fischeri", + "(B) Treron calvus", + "(C) Columba guinea", + "(D) Buteo oreophilus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1317903_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0012", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.529492 and latitude -0.552789 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tchagra jamesi", + "(B) Ciconia nigra", + "(C) Anthoscopus caroli", + "(D) Nicator gularis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462312_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0013", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.280240 and latitude -0.456203 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus crassirostris", + "(B) Psittacus erithacus", + "(C) Nectarinia kilimensis", + "(D) Turdoides jardineii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290905_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0014", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.934569 and latitude 0.040166 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tricholaema diademata", + "(B) Halcyon chelicuti", + "(C) Vanellus lugubris", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23281957_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0015", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.949176 and latitude -0.231627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chroicocephalus cirrocephalus", + "(B) Crithagra mozambica", + "(C) Buteo augur", + "(D) Merops revoilii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20132459_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0016", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495022 and latitude -0.586243 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus cerviniventris", + "(B) Colius striatus", + "(C) Malimbus rubricollis", + "(D) Corvus rhipidurus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16218182_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0017", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.668869 and latitude -4.064917 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vidua funerea", + "(B) Lamprotornis albicapillus", + "(C) Ardea melanocephala", + "(D) Chalcomitra rubescens", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18133972_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0018", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.321445 and latitude -0.749309 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Porphyrio alleni", + "(B) Poicephalus meyeri", + "(C) Scopus umbretta", + "(D) Phyllolais pulchella", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449320_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0019", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.609671 and latitude -0.515350 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Podica senegalensis", + "(B) Apus niansae", + "(C) Illadopsis rufipennis", + "(D) Elanus caeruleus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18745097_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0020", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.272520 and latitude -0.827416 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracias caudatus", + "(B) Lamprotornis shelleyi", + "(C) Agapornis fischeri", + "(D) Dryoscopus cubla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467884_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0021", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.723547 and latitude -3.625617 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Urocolius macrourus", + "(C) Euodice cantans", + "(D) Burhinus capensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16057973_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0022", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429442 and latitude -0.703606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eurystomus glaucurus", + "(B) Milvus migrans", + "(C) Bradypterus centralis", + "(D) Passer domesticus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16189252_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0023", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429360 and latitude -0.703113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Neocossyphus poensis", + "(B) Motacilla aguimp", + "(C) Struthio camelus", + "(D) Laniarius ruficeps", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10284497_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0024", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309831 and latitude -0.707895 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo smithii", + "(B) Alopochen aegyptiaca", + "(C) Arenaria interpres", + "(D) Pterocles lichtensteinii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12116683_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0025", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489479 and latitude -0.625293 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius humeralis", + "(B) Dryoscopus angolensis", + "(C) Anhinga rufa", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12955644_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0026", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.135577 and latitude -0.676287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus insignis", + "(B) Aquila rapax", + "(C) Tauraco schalowi", + "(D) Oxyura maccoa", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10501648_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0027", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.866303 and latitude 1.071369 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes franciscanus", + "(B) Balearica regulorum", + "(C) Vidua macroura", + "(D) Batis perkeo", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9061441_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0028", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560670 and latitude -0.553776 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas sparsa", + "(B) Turtur afer", + "(C) Lissotis hartlaubii", + "(D) Aquila heliaca", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21033789_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0029", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309482 and latitude -0.143795 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Mirafra collaris", + "(C) Cinnyris tsavoensis", + "(D) Cecropis semirufa", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214628_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0030", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.336645 and latitude -0.649582 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nigrita canicapillus", + "(B) Muscicapa adusta", + "(C) Vanellus lugubris", + "(D) Apus niansae", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16553147_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0031", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.813115 and latitude -0.299148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.62 degrees. The mean diurnal range is 12.85 degrees. The isothermality is 82.28. The temperature seasonality (100 times the standard deviation) is 66.45. The max temperature of the warmest month is 23.10 degrees. The min temperature of the coldest month is 7.49 degrees. The temperature annual range is 15.61 degrees. The mean temperature of the wettest quarter is 14.87 degrees. The mean temperature of the driest quarter is 14.98 degrees. The mean temperature of the warmest quarter is 15.47 degrees. The mean temperature of the coldest quarter is 13.79 degrees. The annual precipitation is 1119.0 mm. The precipitation of the wettest month is 167.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 44.48. The precipitation of the wettest quarter is 386.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 289.0 mm. The precipitation of the coldest quarter is 357.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chloropicus poecilolaemus", + "(B) Columba livia", + "(C) Cinnyris pulchellus", + "(D) Anthus cinnamomeus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16581772_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0032", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.506728 and latitude -0.565488 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychoprion fuscatus", + "(B) Vanellus coronatus", + "(C) Eminia lepida", + "(D) Saxicola torquatus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16785945_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0033", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.226784 and latitude -0.482796 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cyanomitra olivacea", + "(B) Falco subbuteo", + "(C) Tricholaema diademata", + "(D) Falco cherrug", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020900_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0034", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.053010 and latitude -0.427459 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Plocepasser mahali", + "(B) Columba guinea", + "(C) Speculipastor bicolor", + "(D) Sarothrura pulchra", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22969685_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0035", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369008 and latitude -0.852497 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Brunhilda charmosyna", + "(B) Aquila verreauxii", + "(C) Lybius guifsobalito", + "(D) Chroicocephalus cirrocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20971407_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0036", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.637739 and latitude -0.483904 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris reichenowi", + "(B) Pternistis jacksoni", + "(C) Bostrychia hagedash", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4154933_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0037", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.679613 and latitude -4.062863 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradypterus cinnamomeus", + "(B) Columba livia", + "(C) Cuculus solitarius", + "(D) Cinnyris nectarinioides", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9419646_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0038", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.472359 and latitude -0.627016 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Scleroptila shelleyi", + "(B) Scopus umbretta", + "(C) Lanius phoenicuroides", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15073030_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0039", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.520126 and latitude -0.558900 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Illadopsis rufipennis", + "(B) Euplectes progne", + "(C) Lamprotornis albicapillus", + "(D) Buphagus erythrorynchus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17683552_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0040", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.445448 and latitude -0.713535 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Telophorus nigrifrons", + "(B) Tringa ochropus", + "(C) Elanus caeruleus", + "(D) Cisticola aberdare", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17578070_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0041", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.704891 and latitude -0.448206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.31 degrees. The mean diurnal range is 11.79 degrees. The isothermality is 81.32. The temperature seasonality (100 times the standard deviation) is 71.36. The max temperature of the warmest month is 20.27 degrees. The min temperature of the coldest month is 5.77 degrees. The temperature annual range is 14.50 degrees. The mean temperature of the wettest quarter is 11.42 degrees. The mean temperature of the driest quarter is 12.71 degrees. The mean temperature of the warmest quarter is 13.20 degrees. The mean temperature of the coldest quarter is 11.42 degrees. The annual precipitation is 1210.0 mm. The precipitation of the wettest month is 174.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 42.21. The precipitation of the wettest quarter is 408.0 mm. The precipitation of the driest quarter is 157.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 408.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra reichardi", + "(B) Bradypterus centralis", + "(C) Sylvietta brachyura", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16285046_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0042", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.073127 and latitude -0.304779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus clarus", + "(B) Anthreptes neglectus", + "(C) Numida meleagris", + "(D) Sterna dougallii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8664033_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0043", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.139337 and latitude -0.676059 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis squamatus", + "(B) Cisticola eximius", + "(C) Milvus migrans", + "(D) Apus berliozi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5159521_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0044", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.662399 and latitude -3.024547 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Falco ardosiaceus", + "(C) Agapornis fischeri", + "(D) Chlorocichla flaviventris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18000924_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0045", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.507893 and latitude -0.564606 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthoscopus musculus", + "(B) Plocepasser donaldsoni", + "(C) Anas undulata", + "(D) Columba delegorguei", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462333_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0046", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.560444 and latitude 0.293821 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra mozambica", + "(B) Streptopelia capicola", + "(C) Vidua hypocherina", + "(D) Vidua fischeri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12826528_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0047", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.530309 and latitude -0.553023 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platalea alba", + "(B) Cuculus canorus", + "(C) Treron waalia", + "(D) Lamprotornis regius", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22174073_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0048", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.740358 and latitude -3.986573 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus melanopterus", + "(B) Cuculus canorus", + "(C) Acrocephalus palustris", + "(D) Microcarbo africanus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22033151_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0049", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.068174 and latitude -3.745175 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.10 degrees. The mean diurnal range is 9.47 degrees. The isothermality is 67.84. The temperature seasonality (100 times the standard deviation) is 147.05. The max temperature of the warmest month is 31.33 degrees. The min temperature of the coldest month is 17.38 degrees. The temperature annual range is 13.95 degrees. The mean temperature of the wettest quarter is 24.55 degrees. The mean temperature of the driest quarter is 22.25 degrees. The mean temperature of the warmest quarter is 25.70 degrees. The mean temperature of the coldest quarter is 22.21 degrees. The annual precipitation is 704.0 mm. The precipitation of the wettest month is 105.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 49.88. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 100.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Apalis flavida", + "(C) Glareola nuchalis", + "(D) Riparia paludicola", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17070362_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0050", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375622 and latitude 0.607860 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ptilopsis granti", + "(B) Sylvia abyssinica", + "(C) Vanellus senegallus", + "(D) Motacilla alba", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498960_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0051", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.516404 and latitude -0.621530 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gallinago nigripennis", + "(B) Fulica cristata", + "(C) Cisticola hunteri", + "(D) Ploceus spekei", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15773403_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0052", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419660 and latitude -0.693710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Balearica pavonina", + "(C) Hedydipna pallidigaster", + "(D) Anastomus lamelligerus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235554_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0053", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116420 and latitude -0.209350 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus horus", + "(B) Cisticola chiniana", + "(C) Streptopelia capicola", + "(D) Cisticola carruthersi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076102_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0054", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.012428 and latitude -3.712565 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.10 degrees. The mean diurnal range is 9.47 degrees. The isothermality is 67.84. The temperature seasonality (100 times the standard deviation) is 147.05. The max temperature of the warmest month is 31.33 degrees. The min temperature of the coldest month is 17.38 degrees. The temperature annual range is 13.95 degrees. The mean temperature of the wettest quarter is 24.55 degrees. The mean temperature of the driest quarter is 22.25 degrees. The mean temperature of the warmest quarter is 25.70 degrees. The mean temperature of the coldest quarter is 22.21 degrees. The annual precipitation is 704.0 mm. The precipitation of the wettest month is 105.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 49.88. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 100.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradornis microrhynchus", + "(B) Hirundo aethiopica", + "(C) Apus affinis", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17434837_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0055", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221035 and latitude -0.483580 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Accipiter ovampensis", + "(B) Anas platyrhynchos", + "(C) Cisticola ayresii", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020897_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0056", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471970 and latitude -0.829753 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus melindae", + "(B) Turtur chalcospilos", + "(C) Ciconia microscelis", + "(D) Oceanites oceanicus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10348524_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0057", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572807 and latitude -0.608167 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Balearica regulorum", + "(B) Gyps rueppelli", + "(C) Spermestes cucullata", + "(D) Caprimulgus poliocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12544941_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0058", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456695 and latitude -0.735810 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Turtur chalcospilos", + "(C) Polyboroides typus", + "(D) Euplectes gierowii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17688211_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0059", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.409981 and latitude -0.688443 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus morio", + "(B) Pandion haliaetus", + "(C) Calidris falcinellus", + "(D) Cisticola woosnami", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21100134_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0060", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368079 and latitude -0.486409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circaetus cinerascens", + "(B) Guttera pucherani", + "(C) Colius striatus", + "(D) Trachyphonus erythrocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21193393_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0061", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.182879 and latitude -1.486376 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dicrurus modestus", + "(B) Indicator variegatus", + "(C) Acrocephalus rufescens", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16920068_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0062", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308691 and latitude -0.144970 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus nubicus", + "(B) Porphyrio madagascariensis", + "(C) Acryllium vulturinum", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689355_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0063", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368525 and latitude -0.850262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sylvia abyssinica", + "(B) Scopus umbretta", + "(C) Lymnocryptes minimus", + "(D) Burhinus senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467384_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0064", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308605 and latitude -0.143869 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Plegadis falcinellus", + "(B) Cossypha heuglini", + "(C) Pogoniulus simplex", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9083281_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0065", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306360 and latitude -0.886671 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cursorius temminckii", + "(B) Streptopelia lugens", + "(C) Apus niansae", + "(D) Coracias naevius", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9772879_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0066", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.475232 and latitude -0.626622 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubulcus ibis", + "(B) Accipiter melanoleucus", + "(C) Elminia nigromitrata", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294840_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0067", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.563548 and latitude -0.562090 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sporopipes frontalis", + "(B) Columba guinea", + "(C) Tricholaema melanocephala", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6253157_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0068", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419903 and latitude -0.693012 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crinifer zonurus", + "(B) Apus caffer", + "(C) Gyps africanus", + "(D) Apus affinis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284267_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0069", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.319829 and latitude -0.895510 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis flavida", + "(B) Thalasseus bengalensis", + "(C) Lamprotornis chalcurus", + "(D) Anaplectes jubaensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674637_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0070", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663894 and latitude -0.524886 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris falcinellus", + "(B) Paragallinula angulata", + "(C) Oreolais pulcher", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106454_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0071", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117296 and latitude -0.315254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bleda syndactylus", + "(B) Anas capensis", + "(C) Plocepasser superciliosus", + "(D) Turnix nanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16745560_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0072", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435363 and latitude -0.759531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chroicocephalus ridibundus", + "(B) Mirafra gilletti", + "(C) Corythornis cristatus", + "(D) Streptopelia reichenowi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21141544_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0073", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.422322 and latitude -0.769772 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastes undosus", + "(B) Ploceus intermedius", + "(C) Lophoceros nasutus", + "(D) Dicrurus divaricatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16775941_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0074", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.602851 and latitude -4.022932 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lophoceros alboterminatus", + "(B) Ploceus heuglini", + "(C) Merops nubicus", + "(D) Gallinula chloropus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5398395_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0075", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.088557 and latitude 1.765971 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.29 degrees. The mean diurnal range is 11.01 degrees. The isothermality is 73.01. The temperature seasonality (100 times the standard deviation) is 112.08. The max temperature of the warmest month is 36.63 degrees. The min temperature of the coldest month is 21.55 degrees. The temperature annual range is 15.08 degrees. The mean temperature of the wettest quarter is 29.15 degrees. The mean temperature of the driest quarter is 27.01 degrees. The mean temperature of the warmest quarter is 29.79 degrees. The mean temperature of the coldest quarter is 27.01 degrees. The annual precipitation is 344.0 mm. The precipitation of the wettest month is 102.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 105.81. The precipitation of the wettest quarter is 172.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 52.0 mm. The precipitation of the coldest quarter is 8.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia decipiens", + "(B) Tricholaema lacrymosa", + "(C) Campephaga petiti", + "(D) Pholia sharpii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12546876_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0076", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.259475 and latitude -0.810887 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera cailliautii", + "(B) Cisticola aberrans", + "(C) Columba guinea", + "(D) Chroicocephalus genei", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294170_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0077", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564123 and latitude -0.561994 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubalornis niger", + "(B) Alopochen aegyptiaca", + "(C) Oriolus percivali", + "(D) Acrocephalus rufescens", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264897_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0078", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.826378 and latitude -1.698618 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.23 degrees. The mean diurnal range is 12.21 degrees. The isothermality is 78.96. The temperature seasonality (100 times the standard deviation) is 100.59. The max temperature of the warmest month is 25.18 degrees. The min temperature of the coldest month is 9.72 degrees. The temperature annual range is 15.47 degrees. The mean temperature of the wettest quarter is 17.70 degrees. The mean temperature of the driest quarter is 16.14 degrees. The mean temperature of the warmest quarter is 18.23 degrees. The mean temperature of the coldest quarter is 15.83 degrees. The annual precipitation is 886.0 mm. The precipitation of the wettest month is 185.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 65.99. The precipitation of the wettest quarter is 402.0 mm. The precipitation of the driest quarter is 65.0 mm. The precipitation of the warmest quarter is 389.0 mm. The precipitation of the coldest quarter is 70.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phoeniculus purpureus", + "(B) Argya aylmeri", + "(C) Vanellus melanopterus", + "(D) Cinnyricinclus leucogaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19588647_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0079", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.123014 and latitude -0.392039 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circus macrourus", + "(B) Psittacus erithacus", + "(C) Gelochelidon nilotica", + "(D) Coturnix coturnix", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21172815_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0080", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.529719 and latitude -2.547062 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corythaixoides leucogaster", + "(B) Vidua purpurascens", + "(C) Puffinus bailloni", + "(D) Hedydipna platura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7938762_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0081", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.679873 and latitude -0.523808 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.27 degrees. The mean diurnal range is 10.87 degrees. The isothermality is 78.19. The temperature seasonality (100 times the standard deviation) is 91.18. The max temperature of the warmest month is 18.77 degrees. The min temperature of the coldest month is 4.87 degrees. The temperature annual range is 13.90 degrees. The mean temperature of the wettest quarter is 12.17 degrees. The mean temperature of the driest quarter is 11.55 degrees. The mean temperature of the warmest quarter is 12.27 degrees. The mean temperature of the coldest quarter is 10.03 degrees. The annual precipitation is 1546.0 mm. The precipitation of the wettest month is 260.0 mm. The precipitation of the driest month is 53.0 mm. The precipitation seasonality (coefficient of variation) is 49.75. The precipitation of the wettest quarter is 618.0 mm. The precipitation of the driest quarter is 226.0 mm. The precipitation of the warmest quarter is 464.0 mm. The precipitation of the coldest quarter is 275.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola aberdare", + "(B) Apus barbatus", + "(C) Cisticola tinniens", + "(D) Rostratula benghalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21214949_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0082", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486100 and latitude -0.635759 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acrocephalus scirpaceus", + "(B) Galerida cristata", + "(C) Streptopelia lugens", + "(D) Bradypterus lopezi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17772247_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0083", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718255 and latitude -4.018984 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Scopus umbretta", + "(B) Crithagra mozambica", + "(C) Cisticola lais", + "(D) Pelecanus onocrotalus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6495825_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0084", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323675 and latitude -0.499642 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tringa ochropus", + "(B) Cecropis senegalensis", + "(C) Columba guinea", + "(D) Hieraaetus ayresii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20336553_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0085", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250000 and latitude -0.433000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ptilopsis leucotis", + "(B) Streptopelia semitorquata", + "(C) Histurgops ruficauda", + "(D) Melierax poliopterus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11222927_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0086", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.531022 and latitude -3.156209 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Poeoptera stuhlmanni", + "(B) Lanius humeralis", + "(C) Tockus deckeni", + "(D) Burhinus capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104171_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0087", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420049 and latitude -0.692290 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthreptes rectirostris", + "(B) Cursorius temminckii", + "(C) Oenanthe oenanthe", + "(D) Turdoides sharpei", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638675_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0088", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.566844 and latitude -0.541457 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Jynx ruficollis", + "(B) Apalis alticola", + "(C) Sheppardia aequatorialis", + "(D) Apus melba", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21241794_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0089", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486637 and latitude -0.634412 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola woosnami", + "(B) Drepanorhynchus reichenowi", + "(C) Turdus abyssinicus", + "(D) Nectarinia tacazze", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919920_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0090", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.729963 and latitude -0.481095 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes macroura", + "(B) Asio abyssinicus", + "(C) Pternistis jacksoni", + "(D) Hedydipna pallidigaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283074_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0091", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.957191 and latitude -0.226942 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Podica senegalensis", + "(B) Trachyphonus darnaudii", + "(C) Otus senegalensis", + "(D) Sarkidiornis melanotos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16110022_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0092", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.373469 and latitude 0.605834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gallinago gallinago", + "(B) Ortygospiza atricollis", + "(C) Corvus albus", + "(D) Chloropicus xantholophus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874347_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0093", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.375773 and latitude -0.596951 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Myrmecocichla aethiops", + "(B) Anastomus lamelligerus", + "(C) Gypohierax angolensis", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10343013_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0094", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.143364 and latitude -0.317675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bias musicus", + "(B) Columba guinea", + "(C) Euplectes jacksoni", + "(D) Pternistis castaneicollis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20990360_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0095", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663925 and latitude -0.525000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oriolus larvatus", + "(B) Pternistis jacksoni", + "(C) Jynx torquilla", + "(D) Gyps africanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952181_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0096", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117793 and latitude -0.311317 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cossypha natalensis", + "(B) Tauraco schalowi", + "(C) Phyllastrephus cabanisi", + "(D) Apus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214625_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0097", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.868821 and latitude -0.991104 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.10 degrees. The mean diurnal range is 12.02 degrees. The isothermality is 81.24. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 25.91 degrees. The min temperature of the coldest month is 11.12 degrees. The temperature annual range is 14.79 degrees. The mean temperature of the wettest quarter is 18.57 degrees. The mean temperature of the driest quarter is 17.21 degrees. The mean temperature of the warmest quarter is 19.06 degrees. The mean temperature of the coldest quarter is 17.17 degrees. The annual precipitation is 1634.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 81.0 mm. The precipitation seasonality (coefficient of variation) is 33.85. The precipitation of the wettest quarter is 594.0 mm. The precipitation of the driest quarter is 321.0 mm. The precipitation of the warmest quarter is 352.0 mm. The precipitation of the coldest quarter is 324.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campephaga phoenicea", + "(B) Batis erlangeri", + "(C) Cinnyris chalcomelas", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16111596_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0098", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564186 and latitude -0.562208 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Argya rubiginosa", + "(B) Apus caffer", + "(C) Sylvia atricapilla", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10057230_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0099", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.561898 and latitude -0.545246 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco tinnunculus", + "(B) Dryoscopus angolensis", + "(C) Crithagra hyposticta", + "(D) Balearica regulorum", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17600308_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0100", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492688 and latitude -0.574404 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius somalicus", + "(B) Cisticola hunteri", + "(C) Cisticola tinniens", + "(D) Plectropterus gambensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6196854_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0101", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321573 and latitude -0.815879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Pterocles quadricinctus", + "(C) Cuculus clamosus", + "(D) Threskiornis aethiopicus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2674368_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0102", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.134727 and latitude -3.283860 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.99 degrees. The mean diurnal range is 11.08 degrees. The isothermality is 68.93. The temperature seasonality (100 times the standard deviation) is 157.66. The max temperature of the warmest month is 30.57 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 16.08 degrees. The mean temperature of the wettest quarter is 22.82 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 23.75 degrees. The mean temperature of the coldest quarter is 19.88 degrees. The annual precipitation is 681.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 8.0 mm. The precipitation seasonality (coefficient of variation) is 86.43. The precipitation of the wettest quarter is 311.0 mm. The precipitation of the driest quarter is 28.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 28.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prinia fluviatilis", + "(B) Corythaixoides leucogaster", + "(C) Coturnix coturnix", + "(D) Apalis cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23139548_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0103", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.596143 and latitude -0.635631 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Pternistis afer", + "(C) Hippolais olivetorum", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18748852_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0104", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.799840 and latitude -3.590762 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Batis orientalis", + "(B) Passer griseus", + "(C) Laniarius ruficeps", + "(D) Apus berliozi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22761538_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0105", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.528470 and latitude -0.928910 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.66 degrees. The mean diurnal range is 12.70 degrees. The isothermality is 74.72. The temperature seasonality (100 times the standard deviation) is 128.32. The max temperature of the warmest month is 24.01 degrees. The min temperature of the coldest month is 7.01 degrees. The temperature annual range is 17.00 degrees. The mean temperature of the wettest quarter is 15.53 degrees. The mean temperature of the driest quarter is 13.00 degrees. The mean temperature of the warmest quarter is 15.98 degrees. The mean temperature of the coldest quarter is 12.82 degrees. The annual precipitation is 1201.0 mm. The precipitation of the wettest month is 254.0 mm. The precipitation of the driest month is 44.0 mm. The precipitation seasonality (coefficient of variation) is 65.40. The precipitation of the wettest quarter is 556.0 mm. The precipitation of the driest quarter is 139.0 mm. The precipitation of the warmest quarter is 423.0 mm. The precipitation of the coldest quarter is 152.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus affinis", + "(B) Circaetus pectoralis", + "(C) Hirundo atrocaerulea", + "(D) Dryoscopus cubla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235556_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0106", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.160548 and latitude -1.041073 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.59 degrees. The mean diurnal range is 12.44 degrees. The isothermality is 82.37. The temperature seasonality (100 times the standard deviation) is 75.98. The max temperature of the warmest month is 26.40 degrees. The min temperature of the coldest month is 11.30 degrees. The temperature annual range is 15.10 degrees. The mean temperature of the wettest quarter is 19.15 degrees. The mean temperature of the driest quarter is 17.65 degrees. The mean temperature of the warmest quarter is 19.50 degrees. The mean temperature of the coldest quarter is 17.60 degrees. The annual precipitation is 1284.0 mm. The precipitation of the wettest month is 202.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 37.26. The precipitation of the wettest quarter is 473.0 mm. The precipitation of the driest quarter is 211.0 mm. The precipitation of the warmest quarter is 316.0 mm. The precipitation of the coldest quarter is 217.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sylvietta virens", + "(B) Microparra capensis", + "(C) Bubulcus ibis", + "(D) Circaetus cinerascens", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17183115_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0107", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095495 and latitude -0.226743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Aquila verreauxii", + "(B) Apalis chariessa", + "(C) Ploceus heuglini", + "(D) Aquila rapax", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17442753_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0108", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726778 and latitude -4.008682 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pluvialis squatarola", + "(B) Oenanthe isabellina", + "(C) Chlidonias hybrida", + "(D) Aquila rapax", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15592344_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0109", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.665287 and latitude -4.045377 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Phoeniconaias minor", + "(C) Camaroptera brachyura", + "(D) Turdus helleri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4669718_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0110", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129303 and latitude -0.423863 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phalaropus lobatus", + "(B) Lissotis melanogaster", + "(C) Columba guinea", + "(D) Dicrurus adsimilis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6501085_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0111", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.867358 and latitude 3.140660 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.29 degrees. The mean diurnal range is 13.95 degrees. The isothermality is 89.71. The temperature seasonality (100 times the standard deviation) is 59.09. The max temperature of the warmest month is 37.04 degrees. The min temperature of the coldest month is 21.49 degrees. The temperature annual range is 15.55 degrees. The mean temperature of the wettest quarter is 29.87 degrees. The mean temperature of the driest quarter is 29.28 degrees. The mean temperature of the warmest quarter is 29.93 degrees. The mean temperature of the coldest quarter is 28.63 degrees. The annual precipitation is 221.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 71.28. The precipitation of the wettest quarter is 109.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 86.0 mm. The precipitation of the coldest quarter is 37.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus nigricollis", + "(B) Clamator glandarius", + "(C) Vanellus senegallus", + "(D) Chloropicus spodocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14796653_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0112", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129259 and latitude -0.423819 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Elminia longicauda", + "(C) Ispidina picta", + "(D) Ploceus bicolor", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498976_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0113", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.391011 and latitude 0.591302 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris superbus", + "(B) Clanga clanga", + "(C) Halcyon albiventris", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22761827_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0114", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.238076 and latitude -0.406703 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cichladusa arquata", + "(B) Sagittarius serpentarius", + "(C) Anas capensis", + "(D) Streptopelia decipiens", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7023051_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0115", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.091412 and latitude -0.270824 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tauraco hartlaubi", + "(B) Rhodophoneus cruentus", + "(C) Nectarinia kilimensis", + "(D) Arizelocichla nigriceps", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17518972_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0116", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.701800 and latitude -4.050448 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius alexandrinus", + "(B) Micronisus gabar", + "(C) Cryptospiza salvadorii", + "(D) Bycanistes brevis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2125380_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0117", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420072 and latitude -0.692664 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Butorides striata", + "(B) Crithagra hyposticta", + "(C) Chrysococcyx caprius", + "(D) Vanellus spinosus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3853026_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0118", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308716 and latitude -0.144961 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus nigricollis", + "(B) Crithagra citrinelloides", + "(C) Anthus campestris", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689305_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0119", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.598020 and latitude -4.035845 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Actophilornis africanus", + "(B) Hippolais olivetorum", + "(C) Caprimulgus europaeus", + "(D) Corvus splendens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9944576_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0120", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.732938 and latitude -0.394370 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Calidris pugnax", + "(C) Anthoscopus caroli", + "(D) Malimbus rubricollis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778815_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0121", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.301285 and latitude 0.541854 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Guttera verreauxi", + "(B) Columba guinea", + "(C) Ardea cinerea", + "(D) Pseudhirundo griseopyga", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21894496_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0122", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.192613 and latitude -0.397264 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mycteria ibis", + "(B) Dromas ardeola", + "(C) Caprimulgus fraenatus", + "(D) Arizelocichla nigriceps", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6814199_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0123", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249344 and latitude -0.433839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Arizelocichla nigriceps", + "(B) Struthio camelus", + "(C) Anthus lineiventris", + "(D) Campethera nivosa", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7843659_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0124", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.049866 and latitude -0.292842 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Myrmecocichla aethiops", + "(C) Zosterops kikuyuensis", + "(D) Cossypha semirufa", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16405041_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0125", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.615962 and latitude -0.492373 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Merops oreobates", + "(B) Turdoides hypoleuca", + "(C) Estrilda kandti", + "(D) Melaenornis edolioides", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12920048_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0126", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.338270 and latitude -0.876449 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris cupreus", + "(B) Motacilla flava", + "(C) Ardeotis kori", + "(D) Pterocles lichtensteinii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10037320_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0127", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491996 and latitude -0.575862 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campephaga flava", + "(B) Merops oreobates", + "(C) Anas capensis", + "(D) Gallinago nigripennis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18942222_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0128", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.351698 and latitude 0.585445 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra buchanani", + "(B) Hirundo aethiopica", + "(C) Lanius humeralis", + "(D) Agapornis canus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5150400_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0129", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.630098 and latitude -0.486990 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Thalassornis leuconotus", + "(B) Monticola rufocinereus", + "(C) Pternistis jacksoni", + "(D) Oriolus chlorocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462321_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0130", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.817400 and latitude -2.251600 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 9.55 degrees. The isothermality is 68.11. The temperature seasonality (100 times the standard deviation) is 141.43. The max temperature of the warmest month is 32.76 degrees. The min temperature of the coldest month is 18.74 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 25.98 degrees. The mean temperature of the driest quarter is 23.52 degrees. The mean temperature of the warmest quarter is 27.06 degrees. The mean temperature of the coldest quarter is 23.52 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 165.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 93.00. The precipitation of the wettest quarter is 353.0 mm. The precipitation of the driest quarter is 32.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 32.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mirafra gilletti", + "(B) Saxicola rubetra", + "(C) Acryllium vulturinum", + "(D) Telophorus bocagei", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10628807_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0131", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492179 and latitude -0.572649 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pogoniulus simplex", + "(B) Charadrius pecuarius", + "(C) Apus apus", + "(D) Cuculus canorus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264892_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0132", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.625373 and latitude -4.005898 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Calidris minuta", + "(C) Lanius cabanisi", + "(D) Phaethon lepturus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21072125_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0133", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.881431 and latitude -1.713421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ortyxelos meiffrenii", + "(B) Scleroptila shelleyi", + "(C) Cossypha heuglini", + "(D) Coracias caudatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16916219_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0134", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.195626 and latitude -0.470653 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circaetus pectoralis", + "(B) Ixobrychus sturmii", + "(C) Stephanoaetus coronatus", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4295706_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0135", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.543559 and latitude -0.545766 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Telophorus bocagei", + "(B) Glareola ocularis", + "(C) Plocepasser mahali", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4499224_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0136", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.496572 and latitude 0.131243 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.15 degrees. The mean diurnal range is 10.59 degrees. The isothermality is 76.13. The temperature seasonality (100 times the standard deviation) is 104.18. The max temperature of the warmest month is 32.45 degrees. The min temperature of the coldest month is 18.54 degrees. The temperature annual range is 13.91 degrees. The mean temperature of the wettest quarter is 25.48 degrees. The mean temperature of the driest quarter is 23.74 degrees. The mean temperature of the warmest quarter is 26.34 degrees. The mean temperature of the coldest quarter is 23.74 degrees. The annual precipitation is 429.0 mm. The precipitation of the wettest month is 141.0 mm. The precipitation of the driest month is 0.0 mm. The precipitation seasonality (coefficient of variation) is 128.46. The precipitation of the wettest quarter is 239.0 mm. The precipitation of the driest quarter is 0.0 mm. The precipitation of the warmest quarter is 155.0 mm. The precipitation of the coldest quarter is 0.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus leucophrys", + "(B) Eupodotis gindiana", + "(C) Lamprotornis superbus", + "(D) Apus affinis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13475065_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0137", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.205101 and latitude -0.361860 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Leptoptilos crumenifer", + "(B) Pseudhirundo griseopyga", + "(C) Laniarius mufumbiri", + "(D) Oenanthe familiaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2128014_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0138", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.558097 and latitude -0.546847 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes laticauda", + "(B) Cisticola marginatus", + "(C) Cisticola nana", + "(D) Curruca communis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106357_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0139", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308797 and latitude -0.144997 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bycanistes bucinator", + "(B) Anthus campestris", + "(C) Polihierax semitorquatus", + "(D) Microparra capensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689310_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0140", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307505 and latitude -0.821283 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla alba", + "(B) Melaenornis edolioides", + "(C) Anthoscopus caroli", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020759_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0141", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635711 and latitude -3.166800 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.21 degrees. The mean diurnal range is 8.43 degrees. The isothermality is 67.81. The temperature seasonality (100 times the standard deviation) is 127.80. The max temperature of the warmest month is 31.70 degrees. The min temperature of the coldest month is 19.26 degrees. The temperature annual range is 12.44 degrees. The mean temperature of the wettest quarter is 25.58 degrees. The mean temperature of the driest quarter is 26.49 degrees. The mean temperature of the warmest quarter is 26.66 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 772.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 52.07. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 104.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 128.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chalcomitra hunteri", + "(B) Anthus melindae", + "(C) Pogoniulus pusillus", + "(D) Asio capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176915_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0142", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237815 and latitude -0.399852 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Telophorus bocagei", + "(B) Alopochen aegyptiaca", + "(C) Leptoptilos crumenifer", + "(D) Ciconia abdimii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16702750_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0143", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.325837 and latitude -0.880693 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus niansae", + "(B) Pholia sharpii", + "(C) Anthus melindae", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674644_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0144", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.773967 and latitude -3.909285 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dicrurus adsimilis", + "(B) Dendrocygna viduata", + "(C) Porphyrio madagascariensis", + "(D) Coracina caesia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13849712_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0145", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.601902 and latitude -3.165657 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Granatina ianthinogaster", + "(B) Burhinus senegalensis", + "(C) Bocagia minuta", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104219_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0146", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425782 and latitude -0.734198 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Iduna similis", + "(B) Chroicocephalus ridibundus", + "(C) Scopus umbretta", + "(D) Cisticola robustus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19074709_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0147", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309128 and latitude -0.497812 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo augur", + "(B) Coracias caudatus", + "(C) Eremomela scotops", + "(D) Sarothrura affinis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284270_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0148", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229283 and latitude -0.396912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nettapus auritus", + "(B) Mirafra albicauda", + "(C) Alopochen aegyptiaca", + "(D) Crithagra canicapilla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4209333_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0149", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431405 and latitude -0.844088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradypterus lopezi", + "(B) Bostrychia hagedash", + "(C) Emberiza striolata", + "(D) Ficedula semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12492683_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0150", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428331 and latitude -0.769065 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius major", + "(B) Caprimulgus clarus", + "(C) Amandava subflava", + "(D) Buteo buteo", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21686523_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0151", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.276834 and latitude -0.740666 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prionops poliolophus", + "(B) Lybius bidentatus", + "(C) Vanellus tectus", + "(D) Cryptospiza salvadorii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10689321_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0152", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461521 and latitude -0.737663 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola hunteri", + "(B) Ficedula semitorquata", + "(C) Corythaeola cristata", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12955574_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0153", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.514038 and latitude -2.533392 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia decipiens", + "(B) Eremomela scotops", + "(C) Egretta garzetta", + "(D) Caprimulgus stellatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2665890_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0154", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.373344 and latitude -0.588738 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ixobrychus minutus", + "(B) Muscicapa adusta", + "(C) Histurgops ruficauda", + "(D) Ardea melanocephala", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20990188_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0155", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.485871 and latitude -1.365101 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.45 degrees. The mean diurnal range is 10.99 degrees. The isothermality is 71.90. The temperature seasonality (100 times the standard deviation) is 129.04. The max temperature of the warmest month is 28.41 degrees. The min temperature of the coldest month is 13.12 degrees. The temperature annual range is 15.29 degrees. The mean temperature of the wettest quarter is 20.95 degrees. The mean temperature of the driest quarter is 18.89 degrees. The mean temperature of the warmest quarter is 21.79 degrees. The mean temperature of the coldest quarter is 18.56 degrees. The annual precipitation is 727.0 mm. The precipitation of the wettest month is 190.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 100.50. The precipitation of the wettest quarter is 338.0 mm. The precipitation of the driest quarter is 9.0 mm. The precipitation of the warmest quarter is 286.0 mm. The precipitation of the coldest quarter is 12.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eupodotis senegalensis", + "(B) Merops apiaster", + "(C) Sylvia atricapilla", + "(D) Motacilla capensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12533990_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0156", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433333 and latitude -0.716667 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Indicator exilis", + "(B) Ardeotis kori", + "(C) Agapornis fischeri", + "(D) Nectarinia famosa", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2247792_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0157", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.234154 and latitude -0.390933 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Thalasseus bergii", + "(C) Alaudala somalica", + "(D) Phyllastrephus hypochloris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12512272_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0158", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.276000 and latitude -0.769000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buphagus erythrorynchus", + "(B) Crithagra burtoni", + "(C) Phylloscopus collybita", + "(D) Myrmecocichla aethiops", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2372252_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0159", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.412310 and latitude -0.773144 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tringa glareola", + "(B) Cisticola aridulus", + "(C) Haliaeetus vocifer", + "(D) Campethera abingoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9338447_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0160", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.596548 and latitude -3.165534 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Argya rubiginosa", + "(C) Dicrurus adsimilis", + "(D) Agapornis personatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22696998_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0161", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.091499 and latitude -0.492793 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Myrmecocichla nigra", + "(B) Oenanthe lugubris", + "(C) Polyboroides typus", + "(D) Clytospiza monteiri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17769544_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0162", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.582512 and latitude 0.350273 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pinarochroa sordida", + "(B) Oreolais pulcher", + "(C) Treron calvus", + "(D) Bubulcus ibis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1233059_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0163", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465225 and latitude -0.736990 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Tauraco schalowi", + "(C) Dendrocygna bicolor", + "(D) Lagonosticta larvata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23190870_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0164", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.320935 and latitude -1.256069 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.94 degrees. The mean diurnal range is 11.66 degrees. The isothermality is 73.58. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 28.34 degrees. The min temperature of the coldest month is 12.49 degrees. The temperature annual range is 15.84 degrees. The mean temperature of the wettest quarter is 20.91 degrees. The mean temperature of the driest quarter is 18.46 degrees. The mean temperature of the warmest quarter is 21.24 degrees. The mean temperature of the coldest quarter is 18.16 degrees. The annual precipitation is 753.0 mm. The precipitation of the wettest month is 180.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 95.06. The precipitation of the wettest quarter is 331.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 301.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Asio abyssinicus", + "(B) Streptopelia semitorquata", + "(C) Sarothrura boehmi", + "(D) Cuculus gularis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17198500_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0165", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262911 and latitude -0.816015 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Centropus grillii", + "(B) Brunhilda erythronotos", + "(C) Cisticola haematocephalus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151424_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0166", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095710 and latitude -0.281802 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Ploceus cucullatus", + "(C) Streptopelia decipiens", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18086660_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0167", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.800089 and latitude -3.590644 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anous stolidus", + "(B) Buphagus africanus", + "(C) Ardea alba", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14840328_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0168", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260102 and latitude -0.814364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Burhinus vermiculatus", + "(B) Alopochen aegyptiaca", + "(C) Falco tinnunculus", + "(D) Cisticola lais", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20004655_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0169", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217298 and latitude 0.159901 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platysteira concreta", + "(B) Gymnobucco bonapartei", + "(C) Bubo africanus", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13087824_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0170", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.863908 and latitude 3.140709 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.29 degrees. The mean diurnal range is 13.95 degrees. The isothermality is 89.71. The temperature seasonality (100 times the standard deviation) is 59.09. The max temperature of the warmest month is 37.04 degrees. The min temperature of the coldest month is 21.49 degrees. The temperature annual range is 15.55 degrees. The mean temperature of the wettest quarter is 29.87 degrees. The mean temperature of the driest quarter is 29.28 degrees. The mean temperature of the warmest quarter is 29.93 degrees. The mean temperature of the coldest quarter is 28.63 degrees. The annual precipitation is 221.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 71.28. The precipitation of the wettest quarter is 109.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 86.0 mm. The precipitation of the coldest quarter is 37.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Puffinus bailloni", + "(B) Ortygornis sephaena", + "(C) Oena capensis", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19793047_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0171", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.863567 and latitude -1.669264 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hyliota australis", + "(B) Dicrurus sharpei", + "(C) Anthus melindae", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22960416_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0172", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.503816 and latitude -0.565360 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus senegallus", + "(B) Vanellus armatus", + "(C) Caprimulgus fossii", + "(D) Cuculus solitarius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232902_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0173", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334140 and latitude -0.891610 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Acrocephalus gracilirostris", + "(C) Numida meleagris", + "(D) Mareca strepera", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700359_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0174", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411111 and latitude -0.775306 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platalea leucorodia", + "(B) Merops revoilii", + "(C) Caprimulgus nubicus", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5650271_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0175", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.077002 and latitude -0.319021 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Phoenicopterus roseus", + "(C) Creatophora cinerea", + "(D) Ardea purpurea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16098203_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0176", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.772937 and latitude -3.944691 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phylloscopus trochilus", + "(B) Numenius phaeopus", + "(C) Halcyon leucocephala", + "(D) Aythya nyroca", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16237233_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0177", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.305355 and latitude 0.440158 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Aythya fuligula", + "(B) Xenus cinereus", + "(C) Thalassornis leuconotus", + "(D) Aviceda cuculoides", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8123311_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0178", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.959969 and latitude -0.040555 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis melanocephala", + "(B) Corythaixoides leucogaster", + "(C) Locustella fluviatilis", + "(D) Anas platyrhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11469923_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0179", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.462258 and latitude -0.903389 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campephaga phoenicea", + "(B) Locustella fluviatilis", + "(C) Batis molitor", + "(D) Apus berliozi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674581_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0180", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444232 and latitude -0.916354 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris ferruginea", + "(B) Laniarius mufumbiri", + "(C) Cyanomitra verticalis", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17671545_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0181", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375000 and latitude 0.606944 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla clara", + "(B) Anaplectes jubaensis", + "(C) Bycanistes bucinator", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10171402_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0182", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.434971 and latitude -0.766284 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracina caesia", + "(B) Bostrychia hagedash", + "(C) Crithagra buchanani", + "(D) Indicator minor", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15027674_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0183", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.333929 and latitude -0.650472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus niansae", + "(B) Cisticola erythrops", + "(C) Pterocles exustus", + "(D) Pholia sharpii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207483_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0184", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429051 and latitude -0.703422 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bostrychia hagedash", + "(B) Guttera pucherani", + "(C) Lamprotornis hildebrandti", + "(D) Cecropis abyssinica", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20290756_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0185", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237024 and latitude -0.397715 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastes simplex", + "(B) Scotopelia peli", + "(C) Ptilostomus afer", + "(D) Agricola pallidus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20792007_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0186", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.725290 and latitude -0.391729 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Stephanoaetus coronatus", + "(B) Spilopelia senegalensis", + "(C) Cinnyris chalcomelas", + "(D) Ketupa lacteus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283134_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0187", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.504741 and latitude -3.146385 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus spinosus", + "(B) Calendulauda poecilosterna", + "(C) Crithagra striolata", + "(D) Merops revoilii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176924_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0188", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464045 and latitude -0.738076 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra sulphurata", + "(B) Macheiramphus alcinus", + "(C) Circaetus cinereus", + "(D) Emberiza tahapisi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16432755_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0189", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.112499 and latitude -0.511699 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes progne", + "(B) Chelictinia riocourii", + "(C) Monticola rufocinereus", + "(D) Apalis melanocephala", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9929386_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0190", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438832 and latitude -0.696724 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platalea alba", + "(B) Oena capensis", + "(C) Threskiornis aethiopicus", + "(D) Xenus cinereus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16273454_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0191", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.155370 and latitude -0.327273 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius somalicus", + "(B) Numida meleagris", + "(C) Anthus melindae", + "(D) Gallinago gallinago", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20955511_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0192", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.666655 and latitude -0.416597 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Accipiter minullus", + "(B) Oriolus chlorocephalus", + "(C) Cisticola robustus", + "(D) Cisticola aberdare", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15780478_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0193", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.607773 and latitude -4.033453 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis shelleyi", + "(B) Rhinoptilus chalcopterus", + "(C) Rhinopomastus cyanomelas", + "(D) Ardea melanocephala", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070470_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0194", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.127913 and latitude -0.425033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pachycoccyx audeberti", + "(B) Charadrius leschenaultii", + "(C) Dendrocygna bicolor", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446678_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0195", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438343 and latitude -0.728957 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Stelgidillas gracilirostris", + "(B) Falco dickinsoni", + "(C) Spilopelia senegalensis", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3111177_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0196", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308737 and latitude -0.144019 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Saxicola torquatus", + "(B) Anthoscopus musculus", + "(C) Micronisus gabar", + "(D) Thalassornis leuconotus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21584322_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0197", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435471 and latitude -0.730914 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo augur", + "(B) Quelea erythrops", + "(C) Bradypterus lopezi", + "(D) Arizelocichla milanjensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284268_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0198", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321058 and latitude -0.512058 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris superbus", + "(B) Dryoscopus cubla", + "(C) Bucorvus leadbeateri", + "(D) Pternistis jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5541002_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0199", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.356469 and latitude -0.738459 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pitta angolensis", + "(B) Amadina fasciata", + "(C) Streptopelia semitorquata", + "(D) Spatula querquedula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563397_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0200", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.667486 and latitude -1.245196 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.46 degrees. The mean diurnal range is 11.48 degrees. The isothermality is 73.55. The temperature seasonality (100 times the standard deviation) is 122.66. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 14.09 degrees. The temperature annual range is 15.61 degrees. The mean temperature of the wettest quarter is 21.93 degrees. The mean temperature of the driest quarter is 19.68 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.68 degrees. The annual precipitation is 724.0 mm. The precipitation of the wettest month is 225.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 113.52. The precipitation of the wettest quarter is 383.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 8.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdus tephronotus", + "(B) Vidua macroura", + "(C) Coracias abyssinicus", + "(D) Pternistis leucoscepus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12595326_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0201", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.613438 and latitude 3.772566 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.53 degrees. The mean diurnal range is 13.60 degrees. The isothermality is 83.55. The temperature seasonality (100 times the standard deviation) is 82.45. The max temperature of the warmest month is 35.21 degrees. The min temperature of the coldest month is 18.93 degrees. The temperature annual range is 16.27 degrees. The mean temperature of the wettest quarter is 26.97 degrees. The mean temperature of the driest quarter is 27.18 degrees. The mean temperature of the warmest quarter is 27.66 degrees. The mean temperature of the coldest quarter is 25.54 degrees. The annual precipitation is 448.0 mm. The precipitation of the wettest month is 81.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 51.57. The precipitation of the wettest quarter is 181.0 mm. The precipitation of the driest quarter is 50.0 mm. The precipitation of the warmest quarter is 77.0 mm. The precipitation of the coldest quarter is 118.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eremopterix signatus", + "(B) Macronyx ameliae", + "(C) Bubalornis albirostris", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18792294_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0202", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.630898 and latitude -2.885577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Ploceus dichrocephalus", + "(C) Cisticola eximius", + "(D) Lanius cabanisi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10986333_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0203", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308702 and latitude -0.144940 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Macheiramphus alcinus", + "(B) Malaconotus blanchoti", + "(C) Anas undulata", + "(D) Apus apus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17693303_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0204", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431025 and latitude -0.717178 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Microcarbo africanus", + "(B) Uraeginthus bengalus", + "(C) Anhinga rufa", + "(D) Melaenornis semipartitus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10777816_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0205", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.711628 and latitude -4.045739 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla alba", + "(B) Aquila nipalensis", + "(C) Bycanistes bucinator", + "(D) Charadrius hiaticula", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2125379_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0206", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.184491 and latitude -3.567496 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdoides hindei", + "(B) Onychoprion fuscatus", + "(C) Macronyx aurantiigula", + "(D) Hirundo atrocaerulea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20640190_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0207", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724500 and latitude -0.498620 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rhinoptilus chalcopterus", + "(B) Cisticola lateralis", + "(C) Anas undulata", + "(D) Tricholaema hirsuta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844377_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0208", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059661 and latitude 3.685803 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.60 degrees. The mean diurnal range is 9.46 degrees. The isothermality is 80.33. The temperature seasonality (100 times the standard deviation) is 76.16. The max temperature of the warmest month is 34.84 degrees. The min temperature of the coldest month is 23.06 degrees. The temperature annual range is 11.78 degrees. The mean temperature of the wettest quarter is 28.96 degrees. The mean temperature of the driest quarter is 28.27 degrees. The mean temperature of the warmest quarter is 29.56 degrees. The mean temperature of the coldest quarter is 27.64 degrees. The annual precipitation is 203.0 mm. The precipitation of the wettest month is 46.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 80.02. The precipitation of the wettest quarter is 100.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 53.0 mm. The precipitation of the coldest quarter is 19.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Salpornis salvadori", + "(C) Melierax metabates", + "(D) Acrocephalus arundinaceus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6286237_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0209", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.934120 and latitude -0.234038 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Histurgops ruficauda", + "(B) Thalasseus bergii", + "(C) Ptilostomus afer", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9078674_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0210", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.155125 and latitude 0.734127 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.31 degrees. The mean diurnal range is 13.08 degrees. The isothermality is 82.01. The temperature seasonality (100 times the standard deviation) is 78.19. The max temperature of the warmest month is 27.02 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.95 degrees. The mean temperature of the wettest quarter is 17.32 degrees. The mean temperature of the driest quarter is 18.80 degrees. The mean temperature of the warmest quarter is 19.29 degrees. The mean temperature of the coldest quarter is 17.32 degrees. The annual precipitation is 1160.0 mm. The precipitation of the wettest month is 188.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 56.08. The precipitation of the wettest quarter is 474.0 mm. The precipitation of the driest quarter is 103.0 mm. The precipitation of the warmest quarter is 250.0 mm. The precipitation of the coldest quarter is 474.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ciconia ciconia", + "(B) Sarothrura elegans", + "(C) Tyto alba", + "(D) Anaplectes jubaensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8677517_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0211", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.146769 and latitude -0.421919 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia reichenowi", + "(B) Ardeola rufiventris", + "(C) Pternistis jacksoni", + "(D) Merops bullockoides", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16582092_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0212", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117312 and latitude -0.315226 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pterocles decoratus", + "(B) Ptilopsis granti", + "(C) Streptopelia capicola", + "(D) Phoeniculus somaliensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794204_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0213", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.949903 and latitude -0.246765 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola ayresii", + "(B) Muscicapa gambagae", + "(C) Bostrychia hagedash", + "(D) Cisticola lais", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23261461_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0214", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.388264 and latitude -0.668392 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hedydipna platura", + "(B) Mycteria ibis", + "(C) Clanga pomarina", + "(D) Elminia albonotata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7839188_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0215", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088550 and latitude -0.281778 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Amandava subflava", + "(B) Cinnyris bifasciatus", + "(C) Apus affinis", + "(D) Cyanomitra veroxii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16772590_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0216", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115849 and latitude -0.437562 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Melaniparus albiventris", + "(B) Apalis jacksoni", + "(C) Thalassornis leuconotus", + "(D) Sylvietta whytii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214619_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0217", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.679827 and latitude -4.062661 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Actitis hypoleucos", + "(B) Clamator levaillantii", + "(C) Euplectes hordeaceus", + "(D) Lamprotornis purpuroptera", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5130641_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0218", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120639 and latitude -0.423215 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oenanthe lugens", + "(B) Buteo buteo", + "(C) Anthus campestris", + "(D) Lamprotornis chalybaeus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446569_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0219", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217522 and latitude 0.159924 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pterocles quadricinctus", + "(B) Ploceus jacksoni", + "(C) Apus affinis", + "(D) Bycanistes subcylindricus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14292511_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0220", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451164 and latitude -0.732254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Psalidoprocne pristoptera", + "(B) Quelea erythrops", + "(C) Cisticola aberdare", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14087358_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0221", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.570883 and latitude 0.318314 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tachybaptus ruficollis", + "(B) Passer castanopterus", + "(C) Caprimulgus tristigma", + "(D) Aquila nipalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6107052_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0222", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.617328 and latitude -0.493218 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bostrychia hagedash", + "(B) Spizocorys fremantlii", + "(C) Apalis thoracica", + "(D) Rhinoptilus cinctus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22470138_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0223", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.670429 and latitude -4.094411 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco ardosiaceus", + "(B) Calandrella cinerea", + "(C) Oenanthe heuglini", + "(D) Plectropterus gambensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2939352_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0224", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453195 and latitude -0.740835 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mirafra hypermetra", + "(B) Dicrurus adsimilis", + "(C) Lanius cabanisi", + "(D) Bubo capensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12937401_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0225", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450963 and latitude -0.498124 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus walleri", + "(B) Cecropis daurica", + "(C) Tyto alba", + "(D) Laniarius mufumbiri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6303604_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0226", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.133619 and latitude -0.418663 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracias naevius", + "(B) Anthus caffer", + "(C) Ardea goliath", + "(D) Crex egregia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13413391_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0227", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.742377 and latitude -3.953980 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Treron waalia", + "(C) Asio abyssinicus", + "(D) Threskiornis aethiopicus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259761_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0228", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442316 and latitude -0.734910 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo augur", + "(B) Passer rufocinctus", + "(C) Eremopterix leucopareia", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12913249_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0229", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.658327 and latitude -4.085605 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Zosterops poliogastrus", + "(C) Euplectes albonotatus", + "(D) Ptilopsis granti", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952141_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0230", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337747 and latitude -2.249538 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus castanops", + "(B) Turtur tympanistria", + "(C) Struthio camelus", + "(D) Emberiza flaviventris", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21230539_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0231", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429984 and latitude -0.814253 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia lugens", + "(B) Agapornis canus", + "(C) Falco subbuteo", + "(D) Prodotiscus insignis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6985066_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0232", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450823 and latitude -0.739571 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastides gracilirostris", + "(B) Phylloscopus ruficapilla", + "(C) Coracias naevius", + "(D) Amandava subflava", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17505776_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0233", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125623 and latitude -0.177259 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis splendidus", + "(B) Hedydipna platura", + "(C) Apaloderma narina", + "(D) Vanellus coronatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22179103_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0234", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.638608 and latitude -4.052072 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turnix nanus", + "(B) Ichthyaetus hemprichii", + "(C) Brunhilda erythronotos", + "(D) Ploceus dichrocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20718767_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0235", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419616 and latitude -0.693378 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Agapornis pullarius", + "(B) Numida meleagris", + "(C) Columba guinea", + "(D) Fraseria caerulescens", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9680706_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0236", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495962 and latitude -0.568284 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alcedo quadribrachys", + "(B) Vanellus melanopterus", + "(C) Oenanthe pleschanka", + "(D) Prodotiscus zambesiae", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17683548_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0237", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564208 and latitude -0.562112 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis purpuroptera", + "(B) Buteo augur", + "(C) Ciconia ciconia", + "(D) Thalassornis leuconotus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16788493_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0238", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724827 and latitude -0.476804 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Quelea quelea", + "(B) Pternistis jacksoni", + "(C) Pholia sharpii", + "(D) Bleda syndactylus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15073057_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0239", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.261411 and latitude -1.398081 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus coronatus", + "(B) Muscicapa gambagae", + "(C) Eurillas virens", + "(D) Emberiza tahapisi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12139266_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0240", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.744654 and latitude -3.935367 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Merops oreobates", + "(B) Bubulcus ibis", + "(C) Cuculus rochii", + "(D) Ardea melanocephala", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6209488_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0241", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.579518 and latitude -2.995523 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubo africanus", + "(B) Salpornis salvadori", + "(C) Schoutedenapus myoptilus", + "(D) Calamonastes simplex", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16308585_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0242", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.109989 and latitude -0.307528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Hirundo smithii", + "(C) Tchagra jamesi", + "(D) Pogoniulus chrysoconus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3189156_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0243", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.573481 and latitude -2.962016 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acryllium vulturinum", + "(B) Dryoscopus angolensis", + "(C) Nigrita bicolor", + "(D) Merops bullockoides", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18498363_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0244", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473665 and latitude -0.594187 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius senator", + "(B) Mirafra javanica", + "(C) Balearica regulorum", + "(D) Ploceus melanogaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16089193_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0245", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125643 and latitude -0.477135 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lissotis melanogaster", + "(B) Corythaixoides leucogaster", + "(C) Chroicocephalus cirrocephalus", + "(D) Erythrocercus holochlorus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7776635_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0246", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.977112 and latitude -0.177386 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris chloropygius", + "(B) Columba guinea", + "(C) Agapornis pullarius", + "(D) Cisticola brachypterus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16897456_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0247", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362561 and latitude -0.858995 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Gallinago media", + "(C) Mirafra hypermetra", + "(D) Ortygornis sephaena", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18075784_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0248", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.448680 and latitude -0.717081 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Polyboroides typus", + "(B) Circaetus cinereus", + "(C) Glareola nuchalis", + "(D) Anaplectes rubriceps", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16028041_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0249", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.964847 and latitude -0.002364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Elanus caeruleus", + "(B) Melaenornis semipartitus", + "(C) Dicrurus adsimilis", + "(D) Rhinoptilus cinctus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6108684_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0250", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477656 and latitude -0.711947 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sula dactylatra", + "(B) Anthus melindae", + "(C) Corvus albus", + "(D) Falco rupicoloides", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4016734_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0251", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.257458 and latitude -0.482749 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Plocepasser superciliosus", + "(C) Scleroptila shelleyi", + "(D) Dicrurus divaricatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284276_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0252", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731725 and latitude -3.989566 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platysteira peltata", + "(B) Indicator minor", + "(C) Ardea intermedia", + "(D) Apalis cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16824651_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0253", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.578744 and latitude 0.337288 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Polyboroides typus", + "(B) Calidris temminckii", + "(C) Ceuthmochares aereus", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17092563_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0254", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.470140 and latitude -0.627299 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis porphyrolaema", + "(B) Lamprotornis fischeri", + "(C) Poicephalus gulielmi", + "(D) Vanellus melanopterus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9240243_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0255", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.956106 and latitude -0.021973 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis purpuroptera", + "(B) Sarothrura affinis", + "(C) Riparia paludicola", + "(D) Gallinago media", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18789323_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0256", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.218005 and latitude -0.411473 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus fraenatus", + "(B) Balearica regulorum", + "(C) Telophorus sulfureopectus", + "(D) Cisticola nana", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17946602_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0257", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298029 and latitude -0.819797 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bleda syndactylus", + "(B) Pinarochroa sordida", + "(C) Cuculus solitarius", + "(D) Curruca communis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17540739_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0258", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090603 and latitude -0.191745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Aquila verreauxii", + "(B) Melaniparus thruppi", + "(C) Terpsiphone rufiventer", + "(D) Motacilla flava", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487379_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0259", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.787467 and latitude -3.860947 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus intermedius", + "(B) Chalcomitra amethystina", + "(C) Columba livia", + "(D) Pternistis leucoscepus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511369_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0260", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.255731 and latitude -0.437468 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla flava", + "(B) Haematopus ostralegus", + "(C) Phoeniconaias minor", + "(D) Oenanthe oenanthe", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7725585_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0261", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263032 and latitude -0.815839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Ciconia nigra", + "(C) Clanga clanga", + "(D) Prionops poliolophus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5007944_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0262", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458876 and latitude -0.737428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pterocles gutturalis", + "(B) Coracias naevius", + "(C) Cisticola aberdare", + "(D) Merops pusillus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17640008_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0263", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451609 and latitude -0.741804 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis fuscigularis", + "(B) Oenanthe familiaris", + "(C) Cinnyris mariquensis", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15304037_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0264", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.144315 and latitude -0.419699 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hieraaetus ayresii", + "(B) Anaplectes rubriceps", + "(C) Oriolus larvatus", + "(D) Bycanistes subcylindricus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22402553_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0265", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.874158 and latitude -1.662879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Charadrius tricollaris", + "(C) Poeoptera stuhlmanni", + "(D) Circaetus fasciolatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18585100_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0266", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.383148 and latitude -0.624033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus affinis", + "(B) Hyliota flavigaster", + "(C) Anthreptes reichenowi", + "(D) Accipiter ovampensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207487_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0267", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249900 and latitude -0.482300 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris pugnax", + "(B) Cisticola chiniana", + "(C) Oenanthe oenanthe", + "(D) Cyanomitra olivacea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025947_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0268", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.388683 and latitude -0.692627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Batis erlangeri", + "(B) Bradypterus lopezi", + "(C) Falco fasciinucha", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21912123_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0269", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.603307 and latitude -4.033056 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Crithagra mozambica", + "(C) Streptopelia decipiens", + "(D) Lamprotornis superbus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20066812_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0270", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.528911 and latitude -2.523347 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prinia subflava", + "(B) Ploceus intermedius", + "(C) Corvus albus", + "(D) Corythaixoides leucogaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6312722_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0271", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.062115 and latitude -0.385601 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris ferruginea", + "(B) Prinia subflava", + "(C) Vanellus lugubris", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21471819_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0272", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328129 and latitude -0.745161 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tyto capensis", + "(B) Polyboroides typus", + "(C) Spatula querquedula", + "(D) Anthreptes rectirostris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2344413_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0273", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421400 and latitude -0.763900 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mirafra williamsi", + "(B) Anthreptes rectirostris", + "(C) Alopochen aegyptiaca", + "(D) Zapornia pusilla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9216894_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0274", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.294833 and latitude 0.494287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cecropis daurica", + "(B) Streptopelia capicola", + "(C) Euplectes nigroventris", + "(D) Cisticola tinniens", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21147101_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0275", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444426 and latitude -0.713927 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius aethiopicus", + "(B) Podiceps cristatus", + "(C) Caprimulgus tristigma", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21640695_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0276", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.200337 and latitude -0.887067 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius major", + "(B) Plocepasser superciliosus", + "(C) Apus melba", + "(D) Scotopelia peli", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22018381_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0277", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.053008 and latitude -0.427117 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Accipiter rufiventris", + "(C) Estrilda troglodytes", + "(D) Eupodotis senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22969367_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0278", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217477 and latitude 0.159772 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Trigonoceps occipitalis", + "(B) Coturnix coturnix", + "(C) Glareola nuchalis", + "(D) Trachyphonus darnaudii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14801976_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0279", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.575960 and latitude -3.166687 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.21 degrees. The mean diurnal range is 8.43 degrees. The isothermality is 67.81. The temperature seasonality (100 times the standard deviation) is 127.80. The max temperature of the warmest month is 31.70 degrees. The min temperature of the coldest month is 19.26 degrees. The temperature annual range is 12.44 degrees. The mean temperature of the wettest quarter is 25.58 degrees. The mean temperature of the driest quarter is 26.49 degrees. The mean temperature of the warmest quarter is 26.66 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 772.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 52.07. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 104.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 128.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pluvialis fulva", + "(B) Oena capensis", + "(C) Jynx torquilla", + "(D) Cisticola robustus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22546889_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0280", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115430 and latitude -0.291496 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oenanthe isabellina", + "(B) Columba livia", + "(C) Sylvia abyssinica", + "(D) Treron waalia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10108533_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0281", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.168400 and latitude -0.313138 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.18 degrees. The mean diurnal range is 13.35 degrees. The isothermality is 79.94. The temperature seasonality (100 times the standard deviation) is 76.39. The max temperature of the warmest month is 23.24 degrees. The min temperature of the coldest month is 6.53 degrees. The temperature annual range is 16.70 degrees. The mean temperature of the wettest quarter is 14.47 degrees. The mean temperature of the driest quarter is 14.51 degrees. The mean temperature of the warmest quarter is 15.19 degrees. The mean temperature of the coldest quarter is 13.26 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 141.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 43.82. The precipitation of the wettest quarter is 361.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 236.0 mm. The precipitation of the coldest quarter is 314.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius mufumbiri", + "(B) Pachyphantes superciliosus", + "(C) Oxyura maccoa", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7852021_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0282", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.213000 and latitude -0.418000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Recurvirostra avosetta", + "(B) Zosterops flavilateralis", + "(C) Bradypterus carpalis", + "(D) Bradypterus baboecala", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16177177_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0283", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.600571 and latitude -4.029169 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Erythrocercus holochlorus", + "(B) Milvus migrans", + "(C) Hedydipna pallidigaster", + "(D) Micronisus gabar", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21137855_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0284", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.771232 and latitude -3.944620 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Poicephalus gulielmi", + "(B) Hippolais olivetorum", + "(C) Malaconotus blanchoti", + "(D) Burhinus vermiculatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6755433_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0285", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.402762 and latitude -0.767880 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta larvata", + "(B) Fulica cristata", + "(C) Bradypterus baboecala", + "(D) Columba delegorguei", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5411827_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0286", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.219587 and latitude -0.507804 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis chalcurus", + "(B) Numida meleagris", + "(C) Quelea cardinalis", + "(D) Threskiornis aethiopicus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16110678_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0287", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429457 and latitude -0.629157 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rhinoptilus chalcopterus", + "(B) Dryoscopus cubla", + "(C) Alopochen aegyptiaca", + "(D) Euplectes capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520360_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0288", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.384439 and latitude -0.625925 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chloropicus spodocephalus", + "(B) Apalis flavida", + "(C) Prinia bairdii", + "(D) Ardea cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5731711_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0289", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.795485 and latitude -3.816549 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Merops nubicus", + "(B) Sula leucogaster", + "(C) Prodotiscus zambesiae", + "(D) Prionops scopifrons", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6691956_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0290", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.916514 and latitude -0.239331 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis flavida", + "(B) Streptopelia capicola", + "(C) Laniarius major", + "(D) Synoicus adansonii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14119738_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0291", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.275253 and latitude -0.827148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius nigerrimus", + "(B) Alopochen aegyptiaca", + "(C) Calidris minuta", + "(D) Pternistis afer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22718838_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0292", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635757 and latitude -3.166420 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola angusticauda", + "(B) Fraseria plumbea", + "(C) Dryoscopus gambensis", + "(D) Tockus deckeni", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104263_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0293", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428538 and latitude -0.709808 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla aguimp", + "(B) Columba guinea", + "(C) Falco dickinsoni", + "(D) Lophoceros nasutus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20882646_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0294", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.259398 and latitude -0.809206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Cisticola aridulus", + "(C) Larus fuscus", + "(D) Turdoides jardineii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260053_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0295", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.559850 and latitude -3.165834 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus tectus", + "(B) Hirundo angolensis", + "(C) Eminia lepida", + "(D) Zosterops poliogastrus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22860349_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0296", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.434216 and latitude -0.629440 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis purpuroptera", + "(B) Prinia bairdii", + "(C) Aquila nipalensis", + "(D) Circaetus fasciolatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23521015_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0297", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.726790 and latitude -0.433400 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Neophron percnopterus", + "(B) Sterna repressa", + "(C) Gallinago gallinago", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844387_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0298", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334770 and latitude -0.824762 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hippolais olivetorum", + "(B) Alopochen aegyptiaca", + "(C) Guttera verreauxi", + "(D) Tringa erythropus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3448162_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0299", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493359 and latitude -0.573695 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Lanius humeralis", + "(C) Arenaria interpres", + "(D) Laniarius funebris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919982_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0300", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.219629 and latitude -0.479424 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Podica senegalensis", + "(B) Podiceps nigricollis", + "(C) Motacilla flava", + "(D) Tyto alba", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237310_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0301", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.390540 and latitude -0.800126 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Haliaeetus vocifer", + "(B) Anas undulata", + "(C) Tauraco schalowi", + "(D) Podica senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12907483_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0302", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.107865 and latitude -0.257710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradypterus lopezi", + "(B) Crithagra hyposticta", + "(C) Euplectes ardens", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12620886_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0303", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263226 and latitude -0.820533 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta larvata", + "(B) Podica senegalensis", + "(C) Turnix nanus", + "(D) Streptopelia lugens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4137246_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0304", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.295821 and latitude -0.667481 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turnix nanus", + "(B) Pycnonotus barbatus", + "(C) Lanius humeralis", + "(D) Sheppardia aequatorialis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8623062_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0305", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458126 and latitude -0.527085 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus fossii", + "(B) Crithagra mozambica", + "(C) Streptopelia lugens", + "(D) Phoeniculus purpureus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13033573_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0306", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221382 and latitude -0.494197 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chlorocichla flaviventris", + "(B) Nigrita fusconotus", + "(C) Ptyonoprogne fuligula", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4116722_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0307", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418361 and latitude -0.720639 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Limosa lapponica", + "(B) Charadrius leschenaultii", + "(C) Alopochen aegyptiaca", + "(D) Crex crex", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23122367_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0308", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.676052 and latitude -0.482208 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Clamator glandarius", + "(C) Bucorvus leadbeateri", + "(D) Paragallinula angulata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22520447_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0309", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495133 and latitude -0.569162 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola hunteri", + "(B) Eminia lepida", + "(C) Mirafra rufocinnamomea", + "(D) Indicator variegatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21216721_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0310", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451943 and latitude -0.565885 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra donaldsoni", + "(B) Onychoprion anaethetus", + "(C) Sarothrura pulchra", + "(D) Coturnix coturnix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6499619_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0311", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.661374 and latitude -4.051145 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phylloscopus trochilus", + "(B) Passer domesticus", + "(C) Corvus splendens", + "(D) Lanius mackinnoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259740_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0312", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.427978 and latitude -0.629969 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus xanthops", + "(B) Melaenornis fischeri", + "(C) Lamprotornis purpureus", + "(D) Prinia fluviatilis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5650316_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0313", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.681488 and latitude -4.049599 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pluvialis squatarola", + "(B) Cinnyris habessinicus", + "(C) Ptilopachus petrosus", + "(D) Neocossyphus rufus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5398498_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0314", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471611 and latitude -0.894685 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Myrmecocichla nigra", + "(C) Anous stolidus", + "(D) Campethera cailliautii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674569_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0315", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087657 and latitude -0.462113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Batis perkeo", + "(B) Alopochen aegyptiaca", + "(C) Gorsachius leuconotus", + "(D) Tringa glareola", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794460_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0316", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.617162 and latitude -0.492412 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bostrychia hagedash", + "(B) Rynchops flavirostris", + "(C) Oriolus chlorocephalus", + "(D) Egretta garzetta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12019208_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0317", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.022308 and latitude -0.070060 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Quelea erythrops", + "(B) Melaniparus guineensis", + "(C) Guttera edouardi", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12901835_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0318", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421957 and latitude -0.778190 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sternula saundersi", + "(B) Alopochen aegyptiaca", + "(C) Sarothrura elegans", + "(D) Irania gutturalis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7864240_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0319", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.808845 and latitude 0.249657 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.38 degrees. The mean diurnal range is 15.42 degrees. The isothermality is 79.55. The temperature seasonality (100 times the standard deviation) is 56.98. The max temperature of the warmest month is 27.08 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 19.39 degrees. The mean temperature of the wettest quarter is 18.16 degrees. The mean temperature of the driest quarter is 17.19 degrees. The mean temperature of the warmest quarter is 18.16 degrees. The mean temperature of the coldest quarter is 16.83 degrees. The annual precipitation is 709.0 mm. The precipitation of the wettest month is 126.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 49.31. The precipitation of the wettest quarter is 259.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 259.0 mm. The precipitation of the coldest quarter is 176.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubulcus ibis", + "(B) Cinnyris chloropygius", + "(C) Cisticola tinniens", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8193671_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0320", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486027 and latitude -0.645036 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Xenus cinereus", + "(B) Euplectes progne", + "(C) Colius striatus", + "(D) Gypaetus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17730556_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0321", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477997 and latitude -0.633960 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius alexandrinus", + "(B) Streptopelia lugens", + "(C) Tringa nebularia", + "(D) Accipiter badius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10223584_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0322", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.086655 and latitude -0.314825 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra atrogularis", + "(B) Lamprotornis fischeri", + "(C) Centropus superciliosus", + "(D) Caprimulgus fossii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2863798_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0323", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.122900 and latitude -0.194700 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris mediocris", + "(B) Turdus abyssinicus", + "(C) Spatula querquedula", + "(D) Eremomela turneri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7775990_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0324", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.470818 and latitude -0.596602 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Sarkidiornis melanotos", + "(C) Lamprotornis chloropterus", + "(D) Motacilla cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23191175_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0325", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.601035 and latitude -4.030511 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Passer domesticus", + "(B) Macrosphenus kretschmeri", + "(C) Euplectes capensis", + "(D) Corvus splendens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5404977_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0326", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473812 and latitude -0.589608 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis fischeri", + "(B) Ephippiorhynchus senegalensis", + "(C) Anas undulata", + "(D) Prodotiscus regulus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952019_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0327", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.446179 and latitude -0.755743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Pterocles decoratus", + "(C) Lamprotornis albicapillus", + "(D) Campethera caroli", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23122301_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0328", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.810734 and latitude -3.817182 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Egretta ardesiaca", + "(B) Dendrocygna viduata", + "(C) Oenanthe lugens", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7940307_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0329", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.940865 and latitude -1.097290 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.63 degrees. The mean diurnal range is 9.45 degrees. The isothermality is 69.39. The temperature seasonality (100 times the standard deviation) is 135.63. The max temperature of the warmest month is 34.78 degrees. The min temperature of the coldest month is 21.16 degrees. The temperature annual range is 13.62 degrees. The mean temperature of the wettest quarter is 28.10 degrees. The mean temperature of the driest quarter is 25.77 degrees. The mean temperature of the warmest quarter is 29.16 degrees. The mean temperature of the coldest quarter is 25.77 degrees. The annual precipitation is 425.0 mm. The precipitation of the wettest month is 100.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 95.08. The precipitation of the wettest quarter is 194.0 mm. The precipitation of the driest quarter is 24.0 mm. The precipitation of the warmest quarter is 152.0 mm. The precipitation of the coldest quarter is 24.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius tricollaris", + "(B) Charadrius pallidus", + "(C) Acryllium vulturinum", + "(D) Elminia nigromitrata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12753463_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0330", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.391834 and latitude 0.644891 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bostrychia hagedash", + "(B) Mirafra williamsi", + "(C) Agricola pallidus", + "(D) Cinnyris tsavoensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6277844_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0331", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.381939 and latitude -0.762206 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cercococcyx montanus", + "(B) Streptopelia semitorquata", + "(C) Phyllolais pulchella", + "(D) Centropus senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449300_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0332", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116309 and latitude -0.410675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spatula clypeata", + "(B) Sylvietta brachyura", + "(C) Ispidina picta", + "(D) Erythrocercus holochlorus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683921_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0333", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.301178 and latitude 0.472054 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Schistolais leucopogon", + "(B) Rostratula benghalensis", + "(C) Streptopelia lugens", + "(D) Pycnonotus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5190089_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0334", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.353146 and latitude 0.471720 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.07 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 81.77. The temperature seasonality (100 times the standard deviation) is 79.91. The max temperature of the warmest month is 24.33 degrees. The min temperature of the coldest month is 9.18 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 15.02 degrees. The mean temperature of the driest quarter is 16.53 degrees. The mean temperature of the warmest quarter is 17.04 degrees. The mean temperature of the coldest quarter is 15.02 degrees. The annual precipitation is 1155.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 49.05. The precipitation of the wettest quarter is 405.0 mm. The precipitation of the driest quarter is 131.0 mm. The precipitation of the warmest quarter is 294.0 mm. The precipitation of the coldest quarter is 405.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Atimastillas flavicollis", + "(C) Threskiornis aethiopicus", + "(D) Ardea cinerea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3539626_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0335", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.657404 and latitude -4.070000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Luscinia luscinia", + "(B) Polihierax semitorquatus", + "(C) Platalea alba", + "(D) Apus affinis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21659195_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0336", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.191342 and latitude -1.465708 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anomalospiza imberbis", + "(B) Corvus albus", + "(C) Oriolus larvatus", + "(D) Crithagra koliensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22054860_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0337", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491733 and latitude -0.573341 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo augur", + "(B) Lanius dorsalis", + "(C) Turnix sylvaticus", + "(D) Cisticola marginatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874268_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0338", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.530113 and latitude -2.546254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oena capensis", + "(B) Corythaixoides leucogaster", + "(C) Motacilla aguimp", + "(D) Cyanomitra cyanolaema", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12171795_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0339", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.764946 and latitude -0.471575 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.64 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 75.78. The temperature seasonality (100 times the standard deviation) is 110.82. The max temperature of the warmest month is 29.44 degrees. The min temperature of the coldest month is 14.75 degrees. The temperature annual range is 14.69 degrees. The mean temperature of the wettest quarter is 22.13 degrees. The mean temperature of the driest quarter is 20.09 degrees. The mean temperature of the warmest quarter is 22.81 degrees. The mean temperature of the coldest quarter is 20.09 degrees. The annual precipitation is 921.0 mm. The precipitation of the wettest month is 231.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.70. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 18.0 mm. The precipitation of the warmest quarter is 351.0 mm. The precipitation of the coldest quarter is 18.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta rhodopareia", + "(B) Chroicocephalus ridibundus", + "(C) Streptopelia semitorquata", + "(D) Merops albicollis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22973092_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0340", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.494308 and latitude -0.574789 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Egretta garzetta", + "(B) Halcyon leucocephala", + "(C) Crithagra citrinelloides", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22251379_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0341", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.497309 and latitude -0.575281 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdus helleri", + "(B) Sylvietta brachyura", + "(C) Telophorus bocagei", + "(D) Caprimulgus poliocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21034667_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0342", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.374162 and latitude 0.606630 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bleda syndactylus", + "(B) Anas erythrorhyncha", + "(C) Zosterops kikuyuensis", + "(D) Spermophaga ruficapilla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16017828_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0343", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.664000 and latitude -0.525000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cyanomitra olivacea", + "(B) Pternistis jacksoni", + "(C) Ploceus heuglini", + "(D) Aplopelia larvata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17120138_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0344", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.448282 and latitude -0.727571 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eremopterix leucopareia", + "(B) Vanellus tectus", + "(C) Cisticola ruficeps", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511060_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0345", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.406424 and latitude -0.794164 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Anas capensis", + "(C) Charadrius alexandrinus", + "(D) Cisticola ruficeps", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15033982_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0346", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418797 and latitude -0.720689 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Euplectes diadematus", + "(C) Oceanites oceanicus", + "(D) Geokichla piaggiae", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18137410_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0347", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419966 and latitude -0.692488 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bostrychia hagedash", + "(B) Crithagra striolata", + "(C) Oenanthe pileata", + "(D) Anas sparsa", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17894349_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0348", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260664 and latitude -0.451287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdus abyssinicus", + "(B) Gyps africanus", + "(C) Anas capensis", + "(D) Muscicapa striata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22454762_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0349", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537651 and latitude -0.548722 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eremomela flavicrissalis", + "(B) Hieraaetus pennatus", + "(C) Vanellus armatus", + "(D) Passer gongonensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11217739_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0350", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.527843 and latitude -0.553853 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phalaropus lobatus", + "(B) Pycnonotus barbatus", + "(C) Alopochen aegyptiaca", + "(D) Lamprotornis hildebrandti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3837423_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0351", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.174772 and latitude 0.745997 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.45 degrees. The mean diurnal range is 13.17 degrees. The isothermality is 82.23. The temperature seasonality (100 times the standard deviation) is 77.96. The max temperature of the warmest month is 26.16 degrees. The min temperature of the coldest month is 10.14 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 16.45 degrees. The mean temperature of the driest quarter is 17.86 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.45 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 160.0 mm. The precipitation of the driest month is 24.0 mm. The precipitation seasonality (coefficient of variation) is 52.76. The precipitation of the wettest quarter is 398.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 380.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nilaus afer", + "(B) Spilopelia senegalensis", + "(C) Pelecanus rufescens", + "(D) Crithagra koliensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15852185_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0352", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.621668 and latitude -0.492862 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra hyposticta", + "(B) Passer rufocinctus", + "(C) Turdus abyssinicus", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970656_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0353", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.594228 and latitude -0.520317 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lissotis hartlaubii", + "(B) Corvus capensis", + "(C) Scopus umbretta", + "(D) Scleroptila levaillantii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970890_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0354", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323997 and latitude -0.815719 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardeola idae", + "(B) Alopochen aegyptiaca", + "(C) Apus barbatus", + "(D) Sylvietta whytii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260914_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0355", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.389996 and latitude -0.846563 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus fossii", + "(B) Tauraco leucolophus", + "(C) Streptopelia semitorquata", + "(D) Sarothrura boehmi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614321_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0356", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.403337 and latitude -0.689528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Turnix nanus", + "(C) Circus macrourus", + "(D) Lamprotornis superbus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20882710_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0357", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.299127 and latitude 0.750025 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.45 degrees. The mean diurnal range is 13.17 degrees. The isothermality is 82.23. The temperature seasonality (100 times the standard deviation) is 77.96. The max temperature of the warmest month is 26.16 degrees. The min temperature of the coldest month is 10.14 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 16.45 degrees. The mean temperature of the driest quarter is 17.86 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.45 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 160.0 mm. The precipitation of the driest month is 24.0 mm. The precipitation seasonality (coefficient of variation) is 52.76. The precipitation of the wettest quarter is 398.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 380.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus bicolor", + "(B) Spilopelia senegalensis", + "(C) Euplectes ardens", + "(D) Lanius mackinnoni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18568633_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0358", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.445636 and latitude -0.521177 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus morio", + "(B) Tachybaptus ruficollis", + "(C) Spermestes griseicapilla", + "(D) Amandava subflava", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21193685_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0359", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.723508 and latitude -3.625630 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prinia somalica", + "(B) Gyps africanus", + "(C) Turdus helleri", + "(D) Ortygornis sephaena", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16058252_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0360", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.300407 and latitude -0.818526 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sarkidiornis melanotos", + "(B) Ceuthmochares aereus", + "(C) Ploceus vitellinus", + "(D) Centropus superciliosus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304185_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0361", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.426550 and latitude -0.700406 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calendulauda africanoides", + "(B) Microparra capensis", + "(C) Bostrychia hagedash", + "(D) Dicrurus adsimilis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436289_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0362", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.763536 and latitude -0.385051 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Coccopygia quartinia", + "(C) Campephaga flava", + "(D) Campethera tullbergi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10216632_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0363", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.314601 and latitude -0.814606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus natalensis", + "(B) Geokichla piaggiae", + "(C) Oriolus brachyrynchus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5635215_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0364", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.277937 and latitude -0.467145 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Cisticola chiniana", + "(C) Corvus albus", + "(D) Treron waalia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3136844_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0365", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.099495 and latitude -0.421912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Cisticola galactotes", + "(C) Scleroptila streptophora", + "(D) Laniarius funebris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15414258_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0366", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.373900 and latitude 0.606011 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gallinago gallinago", + "(B) Curruca communis", + "(C) Podica senegalensis", + "(D) Centropus monachus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14384250_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0367", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492206 and latitude -0.572734 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oriolus auratus", + "(B) Ploceus subaureus", + "(C) Streptopelia lugens", + "(D) Chrysococcyx cupreus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23191397_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0368", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369111 and latitude -0.852654 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Burhinus vermiculatus", + "(B) Rhaphidura sabini", + "(C) Ardeotis kori", + "(D) Cisticola ayresii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18272761_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0369", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.393146 and latitude -0.809223 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardeola idae", + "(B) Alopochen aegyptiaca", + "(C) Platysteira cyanea", + "(D) Estrilda paludicola", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9850797_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0370", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189833 and latitude -0.808010 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Centropus superciliosus", + "(B) Cinnyris usambaricus", + "(C) Pachycoccyx audeberti", + "(D) Scleroptila psilolaema", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21155579_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0371", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.637396 and latitude 0.414141 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.73 degrees. The mean diurnal range is 15.52 degrees. The isothermality is 81.38. The temperature seasonality (100 times the standard deviation) is 60.58. The max temperature of the warmest month is 27.31 degrees. The min temperature of the coldest month is 8.23 degrees. The temperature annual range is 19.08 degrees. The mean temperature of the wettest quarter is 18.18 degrees. The mean temperature of the driest quarter is 17.70 degrees. The mean temperature of the warmest quarter is 18.54 degrees. The mean temperature of the coldest quarter is 17.02 degrees. The annual precipitation is 679.0 mm. The precipitation of the wettest month is 113.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 48.55. The precipitation of the wettest quarter is 245.0 mm. The precipitation of the driest quarter is 78.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 189.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Phyllastrephus terrestris", + "(C) Melaenornis edolioides", + "(D) Terathopius ecaudatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18372057_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0372", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.315994 and latitude -0.505364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco tinnunculus", + "(B) Cossypha semirufa", + "(C) Streptopelia capicola", + "(D) Tachybaptus ruficollis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1966451_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0373", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.413886 and latitude -0.714329 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus fossii", + "(B) Ptyonoprogne fuligula", + "(C) Dicrurus adsimilis", + "(D) Fulica cristata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526554_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0374", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.587900 and latitude -0.527418 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis fischeri", + "(B) Falco dickinsoni", + "(C) Pternistis jacksoni", + "(D) Locustella fluviatilis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14838352_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0375", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492998 and latitude -0.573957 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus barbatus", + "(B) Cypsiurus parvus", + "(C) Dendrocygna bicolor", + "(D) Zosterops flavilateralis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258666_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0376", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189847 and latitude -0.499457 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chrysococcyx klaas", + "(B) Cossypha heuglini", + "(C) Ploceus taeniopterus", + "(D) Ploceus baglafecht", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4192719_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0377", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.630851 and latitude -1.414689 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.42 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 72.41. The temperature seasonality (100 times the standard deviation) is 126.48. The max temperature of the warmest month is 29.39 degrees. The min temperature of the coldest month is 14.02 degrees. The temperature annual range is 15.37 degrees. The mean temperature of the wettest quarter is 21.91 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.57 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 204.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 105.97. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 270.0 mm. The precipitation of the coldest quarter is 10.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eurillas gracilis", + "(B) Anthus caffer", + "(C) Streptopelia capicola", + "(D) Corvus capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3810527_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0378", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391354 and latitude -0.810172 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Ploceus baglafecht", + "(C) Anhinga rufa", + "(D) Puffinus bailloni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076203_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0379", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.783590 and latitude 3.395485 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.48 degrees. The mean diurnal range is 13.65 degrees. The isothermality is 89.33. The temperature seasonality (100 times the standard deviation) is 58.34. The max temperature of the warmest month is 37.24 degrees. The min temperature of the coldest month is 21.96 degrees. The temperature annual range is 15.28 degrees. The mean temperature of the wettest quarter is 29.93 degrees. The mean temperature of the driest quarter is 29.42 degrees. The mean temperature of the warmest quarter is 30.09 degrees. The mean temperature of the coldest quarter is 28.80 degrees. The annual precipitation is 216.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 73.14. The precipitation of the wettest quarter is 108.0 mm. The precipitation of the driest quarter is 20.0 mm. The precipitation of the warmest quarter is 90.0 mm. The precipitation of the coldest quarter is 32.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Gallinula chloropus", + "(C) Zapornia flavirostra", + "(D) Vanellus tectus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18766494_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0380", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477413 and latitude -0.548408 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chrysococcyx caprius", + "(B) Lophaetus occipitalis", + "(C) Phoeniculus damarensis", + "(D) Prinia somalica", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952041_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0381", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.292430 and latitude -0.474668 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Schistolais leucopogon", + "(B) Cursorius temminckii", + "(C) Agapornis canus", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10016562_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0382", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.750250 and latitude -0.385840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis cinerea", + "(B) Pternistis jacksoni", + "(C) Lagonosticta larvata", + "(D) Estrilda kandti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844397_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0383", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.553340 and latitude -0.544870 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coturnix coturnix", + "(B) Circus ranivorus", + "(C) Falco eleonorae", + "(D) Euplectes gierowii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12677036_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0384", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469705 and latitude -0.596839 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cyanomitra cyanolaema", + "(B) Falco rupicolus", + "(C) Milvus migrans", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264886_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0385", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.109073 and latitude -0.625061 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Otus ireneae", + "(B) Centropus superciliosus", + "(C) Mirafra collaris", + "(D) Caprimulgus poliocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5053497_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0386", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.666660 and latitude -0.416660 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis hildebrandti", + "(B) Pternistis jacksoni", + "(C) Nectarinia tacazze", + "(D) Accipiter ovampensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700354_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0387", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.787022 and latitude -3.611775 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circus ranivorus", + "(B) Alopochen aegyptiaca", + "(C) Vanellus tectus", + "(D) Phyllastrephus debilis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12512160_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0388", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428950 and latitude -0.631089 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta rara", + "(B) Eurillas gracilis", + "(C) Lamprotornis chalybaeus", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520123_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0389", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.309540 and latitude 0.480940 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sylvietta whytii", + "(B) Lanius senator", + "(C) Streptopelia semitorquata", + "(D) Laniarius mufumbiri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025079_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0390", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.449158 and latitude -0.736882 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prinia somalica", + "(B) Numida meleagris", + "(C) Lanius dorsalis", + "(D) Circaetus pectoralis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17715489_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0391", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117551 and latitude -0.423970 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Campethera caroli", + "(C) Ispidina picta", + "(D) Merops bullockoides", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20175100_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0392", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.318789 and latitude -0.686781 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla clara", + "(B) Alopochen aegyptiaca", + "(C) Hedydipna pallidigaster", + "(D) Lanius cabanisi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20542245_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0393", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.994504 and latitude -0.243940 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus cucullatus", + "(B) Cisticola brunnescens", + "(C) Anastomus lamelligerus", + "(D) Irania gutturalis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19362935_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0394", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308906 and latitude -0.144131 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Merops oreobates", + "(B) Merops albicollis", + "(C) Dendrocygna viduata", + "(D) Plocepasser superciliosus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18512495_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0395", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493108 and latitude -0.574312 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Mirafra pulpa", + "(C) Crithagra mozambica", + "(D) Lanius phoenicuroides", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13649793_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0396", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.212121 and latitude -1.750867 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.31 degrees. The mean diurnal range is 8.45 degrees. The isothermality is 67.30. The temperature seasonality (100 times the standard deviation) is 129.89. The max temperature of the warmest month is 34.03 degrees. The min temperature of the coldest month is 21.48 degrees. The temperature annual range is 12.56 degrees. The mean temperature of the wettest quarter is 27.30 degrees. The mean temperature of the driest quarter is 28.77 degrees. The mean temperature of the warmest quarter is 28.81 degrees. The mean temperature of the coldest quarter is 25.64 degrees. The annual precipitation is 602.0 mm. The precipitation of the wettest month is 96.0 mm. The precipitation of the driest month is 9.0 mm. The precipitation seasonality (coefficient of variation) is 52.37. The precipitation of the wettest quarter is 237.0 mm. The precipitation of the driest quarter is 68.0 mm. The precipitation of the warmest quarter is 134.0 mm. The precipitation of the coldest quarter is 113.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acryllium vulturinum", + "(B) Lophaetus occipitalis", + "(C) Bradypterus carpalis", + "(D) Apaloderma vittatum", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21815233_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0397", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464309 and latitude -0.711496 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Apalis rufogularis", + "(C) Cercotrichas leucophrys", + "(D) Charadrius pecuarius", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7793665_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0398", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.258316 and latitude -0.472450 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius major", + "(B) Pterocles lichtensteinii", + "(C) Ardea alba", + "(D) Estrilda nonnula", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5375564_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0399", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.248391 and latitude -0.463011 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sarothrura pulchra", + "(B) Pternistis castaneicollis", + "(C) Anas capensis", + "(D) Anas erythrorhyncha", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17889591_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0400", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554389 and latitude -0.545723 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardeola ralloides", + "(B) Crithagra reichenowi", + "(C) Streptopelia semitorquata", + "(D) Ploceus castanops", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4897237_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0401", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323909 and latitude -0.716962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra atrogularis", + "(B) Passer griseus", + "(C) Alopochen aegyptiaca", + "(D) Phoenicopterus roseus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14451311_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0402", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306295 and latitude -0.888119 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Microcarbo africanus", + "(B) Falco vespertinus", + "(C) Lamprotornis albicapillus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21760935_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0403", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450996 and latitude -0.742628 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Oriolus oriolus", + "(C) Lanius humeralis", + "(D) Calamonastides gracilirostris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14709637_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0404", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.627259 and latitude -0.491738 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Estrilda nonnula", + "(C) Hippolais olivetorum", + "(D) Curruca nisoria", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4897193_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0405", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572693 and latitude -0.608155 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anhinga rufa", + "(B) Centropus monachus", + "(C) Streptopelia capicola", + "(D) Batis mixta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14188081_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0406", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.439377 and latitude -0.736368 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Poicephalus cryptoxanthus", + "(B) Butastur rufipennis", + "(C) Columba guinea", + "(D) Cossypha semirufa", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17074113_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0407", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469185 and latitude -0.596552 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo rufinus", + "(B) Fulica cristata", + "(C) Eurillas curvirostris", + "(D) Ciconia nigra", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20163417_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0408", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438713 and latitude -0.728692 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Merops variegatus", + "(B) Euplectes axillaris", + "(C) Streptopelia semitorquata", + "(D) Hippolais icterina", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7239787_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0409", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.732674 and latitude -3.996109 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius corvinus", + "(B) Oriolus oriolus", + "(C) Microcarbo africanus", + "(D) Laniarius ruficeps", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8781358_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0410", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.581564 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardea intermedia", + "(B) Coturnix delegorguei", + "(C) Dromas ardeola", + "(D) Neophedina cincta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462486_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0411", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.745582 and latitude -3.935211 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eupodotis gindiana", + "(B) Centropus superciliosus", + "(C) Tachybaptus ruficollis", + "(D) Zosterops silvanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6368285_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0412", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421976 and latitude -0.767518 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chroicocephalus cirrocephalus", + "(B) Macheiramphus alcinus", + "(C) Streptopelia lugens", + "(D) Phalacrocorax carbo", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21690200_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0413", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087024 and latitude -0.272079 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nectarinia kilimensis", + "(B) Amblyospiza albifrons", + "(C) Granatina ianthinogaster", + "(D) Dendrocygna bicolor", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15579688_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0414", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401497 and latitude -0.775472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradypterus centralis", + "(B) Hirundo aethiopica", + "(C) Anas capensis", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17279003_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0415", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437870 and latitude -0.712380 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chloropicus obsoletus", + "(B) Cisticola troglodytes", + "(C) Alopochen aegyptiaca", + "(D) Ploceus intermedius", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235555_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0416", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084155 and latitude -0.310158 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Todiramphus chloris", + "(B) Ploceus baglafecht", + "(C) Scleroptila elgonensis", + "(D) Ploceus intermedius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22149720_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0417", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.987358 and latitude -0.065888 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis superbus", + "(B) Pycnonotus barbatus", + "(C) Streptopelia semitorquata", + "(D) Cuculus rochii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020893_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0418", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.653233 and latitude -0.520653 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Macheiramphus alcinus", + "(C) Chalcomitra rubescens", + "(D) Campethera abingoni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12922521_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0419", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309504 and latitude -0.144840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus jacksoni", + "(B) Anas undulata", + "(C) Crex crex", + "(D) Sarothrura affinis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17105797_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0420", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.563720 and latitude 0.302911 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oriolus oriolus", + "(B) Mirafra africana", + "(C) Lagonosticta rubricata", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22403601_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0421", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420348 and latitude -0.693444 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola aberrans", + "(B) Tringa glareola", + "(C) Locustella fluviatilis", + "(D) Halcyon senegaloides", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8291585_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0422", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.751548 and latitude -3.972793 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circus pygargus", + "(B) Cinnyris erythrocercus", + "(C) Cypsiurus parvus", + "(D) Cossypha natalensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15271561_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0423", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.698753 and latitude -4.050234 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Pseudonigrita cabanisi", + "(C) Oceanites oceanicus", + "(D) Illadopsis albipectus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2843164_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0424", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.025098 and latitude -0.272587 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra citrinelloides", + "(B) Phoeniculus somaliensis", + "(C) Bostrychia hagedash", + "(D) Saxicola torquatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487314_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0425", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663763 and latitude -0.524993 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Drepanorhynchus reichenowi", + "(B) Anas undulata", + "(C) Campethera tullbergi", + "(D) Turdus abyssinicus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20233097_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0426", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453301 and latitude -0.727955 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris chloropygius", + "(B) Cisticola woosnami", + "(C) Asio abyssinicus", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17028883_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0427", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.866695 and latitude -1.696835 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris venustus", + "(B) Lamprotornis regius", + "(C) Scopus umbretta", + "(D) Prinia subflava", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21108844_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0428", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.789200 and latitude -3.793600 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Luscinia megarhynchos", + "(B) Telacanthura ussheri", + "(C) Motacilla aguimp", + "(D) Hirundo aethiopica", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16527480_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0429", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731682 and latitude -3.989279 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Haliaeetus vocifer", + "(C) Galerida theklae", + "(D) Notopholia corusca", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19738874_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0430", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425833 and latitude -0.633080 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Riparia paludicola", + "(B) Lamprotornis chalcurus", + "(C) Alopochen aegyptiaca", + "(D) Andropadus importunus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18595306_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0431", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.755890 and latitude 0.551423 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.52 degrees. The mean diurnal range is 12.84 degrees. The isothermality is 83.19. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 16.30 degrees. The temperature annual range is 15.43 degrees. The mean temperature of the wettest quarter is 23.34 degrees. The mean temperature of the driest quarter is 22.72 degrees. The mean temperature of the warmest quarter is 24.38 degrees. The mean temperature of the coldest quarter is 22.72 degrees. The annual precipitation is 533.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.08. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis leucoscepus", + "(B) Calamonastes simplex", + "(C) Vidua funerea", + "(D) Schoutedenapus myoptilus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2262871_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0432", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.633362 and latitude -0.206337 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.24 degrees. The mean diurnal range is 10.34 degrees. The isothermality is 73.35. The temperature seasonality (100 times the standard deviation) is 120.47. The max temperature of the warmest month is 35.74 degrees. The min temperature of the coldest month is 21.65 degrees. The temperature annual range is 14.10 degrees. The mean temperature of the wettest quarter is 28.40 degrees. The mean temperature of the driest quarter is 26.66 degrees. The mean temperature of the warmest quarter is 29.73 degrees. The mean temperature of the coldest quarter is 26.66 degrees. The annual precipitation is 333.0 mm. The precipitation of the wettest month is 93.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.95. The precipitation of the wettest quarter is 176.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 116.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius dorsalis", + "(B) Ploceus dichrocephalus", + "(C) Streptopelia capicola", + "(D) Brunhilda charmosyna", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734557_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0433", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.283353 and latitude -0.757635 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Pyrenestes ostrinus", + "(C) Vanellus tectus", + "(D) Curruca lugens", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449207_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0434", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.584468 and latitude -0.349529 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.23 degrees. The mean diurnal range is 12.53 degrees. The isothermality is 82.31. The temperature seasonality (100 times the standard deviation) is 70.01. The max temperature of the warmest month is 22.62 degrees. The min temperature of the coldest month is 7.39 degrees. The temperature annual range is 15.23 degrees. The mean temperature of the wettest quarter is 14.39 degrees. The mean temperature of the driest quarter is 14.68 degrees. The mean temperature of the warmest quarter is 15.10 degrees. The mean temperature of the coldest quarter is 13.35 degrees. The annual precipitation is 1397.0 mm. The precipitation of the wettest month is 193.0 mm. The precipitation of the driest month is 47.0 mm. The precipitation seasonality (coefficient of variation) is 43.71. The precipitation of the wettest quarter is 492.0 mm. The precipitation of the driest quarter is 171.0 mm. The precipitation of the warmest quarter is 331.0 mm. The precipitation of the coldest quarter is 460.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Amadina fasciata", + "(B) Alopochen aegyptiaca", + "(C) Lophaetus occipitalis", + "(D) Nigrita fusconotus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20352553_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0435", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.301660 and latitude -0.819634 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracias abyssinicus", + "(B) Streptopelia semitorquata", + "(C) Rhinoptilus chalcopterus", + "(D) Cisticola robustus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12259577_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0436", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.192333 and latitude -0.483834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Ardea intermedia", + "(C) Circaetus cinereus", + "(D) Batis orientalis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20782442_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0437", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461087 and latitude -0.740838 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Monticola saxatilis", + "(B) Egretta gularis", + "(C) Terpsiphone viridis", + "(D) Chrysococcyx klaas", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15448089_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0438", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095954 and latitude -0.458151 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola marginatus", + "(B) Alopochen aegyptiaca", + "(C) Cinnyris pulchellus", + "(D) Poeoptera stuhlmanni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21362294_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0439", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.747138 and latitude -3.955569 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cypsiurus parvus", + "(B) Ketupa lacteus", + "(C) Illadopsis rufipennis", + "(D) Haliaeetus vocifer", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7340242_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0440", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108043 and latitude -0.295206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus canorus", + "(B) Charadrius mongolus", + "(C) Cecropis semirufa", + "(D) Struthio camelus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4259135_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0441", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.283472 and latitude -0.732351 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis regius", + "(B) Alopochen aegyptiaca", + "(C) Mareca penelope", + "(D) Treron waalia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21002856_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0442", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.957074 and latitude -0.224339 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prodotiscus zambesiae", + "(B) Ardea melanocephala", + "(C) Ixobrychus sturmii", + "(D) Cisticola angusticauda", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8213719_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0443", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456529 and latitude -0.738829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sarothrura elegans", + "(B) Streptopelia semitorquata", + "(C) Arizelocichla nigriceps", + "(D) Chrysococcyx caprius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20255070_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0444", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.741623 and latitude -3.608959 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastides gracilirostris", + "(B) Spilopelia senegalensis", + "(C) Chloropicus fuscescens", + "(D) Estrilda kandti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1461598_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0445", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307068 and latitude -0.719586 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lissotis hartlaubii", + "(B) Alopochen aegyptiaca", + "(C) Mirafra africana", + "(D) Cisticola ruficeps", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2126423_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0446", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428964 and latitude -0.629723 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Milvus migrans", + "(B) Cinnyris reichenowi", + "(C) Anas crecca", + "(D) Camaroptera brachyura", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6998556_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0447", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.494656 and latitude -0.575474 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris mariquensis", + "(B) Bubulcus ibis", + "(C) Hippolais languida", + "(D) Prionops scopifrons", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025970_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0448", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.416637 and latitude -0.725118 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zapornia flavirostra", + "(B) Lamprotornis splendidus", + "(C) Cichladusa guttata", + "(D) Oenanthe heuglini", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10009116_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0449", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.877869 and latitude -3.632665 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.32 degrees. The mean diurnal range is 10.16 degrees. The isothermality is 69.34. The temperature seasonality (100 times the standard deviation) is 150.42. The max temperature of the warmest month is 31.94 degrees. The min temperature of the coldest month is 17.29 degrees. The temperature annual range is 14.65 degrees. The mean temperature of the wettest quarter is 24.78 degrees. The mean temperature of the driest quarter is 22.40 degrees. The mean temperature of the warmest quarter is 25.97 degrees. The mean temperature of the coldest quarter is 22.36 degrees. The annual precipitation is 730.0 mm. The precipitation of the wettest month is 117.0 mm. The precipitation of the driest month is 21.0 mm. The precipitation seasonality (coefficient of variation) is 58.42. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 72.0 mm. The precipitation of the warmest quarter is 226.0 mm. The precipitation of the coldest quarter is 85.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Ploceus vitellinus", + "(C) Trachyphonus darnaudii", + "(D) Micronisus gabar", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1875249_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0450", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.126686 and latitude -0.361053 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthreptes longuemarei", + "(B) Alopochen aegyptiaca", + "(C) Clytospiza monteiri", + "(D) Macheiramphus alcinus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6525805_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0451", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461958 and latitude -0.739721 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circaetus pectoralis", + "(B) Calamonastides gracilirostris", + "(C) Streptopelia semitorquata", + "(D) Bycanistes subcylindricus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16981110_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0452", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.481020 and latitude -0.629872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Fraseria caerulescens", + "(B) Catriscus brevirostris", + "(C) Apus horus", + "(D) Coturnix coturnix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11533438_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0453", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.215680 and latitude -0.504725 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hippolais icterina", + "(B) Pogoniulus chrysoconus", + "(C) Laniarius sublacteus", + "(D) Pternistis hildebrandti", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10084302_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0454", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.256105 and latitude -0.817704 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris chalcomelas", + "(B) Ploceus pelzelni", + "(C) Actitis hypoleucos", + "(D) Hirundo rustica", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22415482_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0455", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.607782 and latitude -2.975250 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Macronyx ameliae", + "(B) Pogoniulus bilineatus", + "(C) Pogoniulus leucomystax", + "(D) Ketupa lacteus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4921609_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0456", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.472665 and latitude -0.629135 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Circaetus fasciolatus", + "(C) Melaniparus fringillinus", + "(D) Cercotrichas leucophrys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11371034_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0457", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492129 and latitude -0.572573 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spatula hottentota", + "(B) Scleroptila shelleyi", + "(C) Columba delegorguei", + "(D) Streptopelia lugens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778240_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0458", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.472955 and latitude 0.000007 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.41 degrees. The mean diurnal range is 10.47 degrees. The isothermality is 74.66. The temperature seasonality (100 times the standard deviation) is 111.40. The max temperature of the warmest month is 34.82 degrees. The min temperature of the coldest month is 20.80 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 27.52 degrees. The mean temperature of the driest quarter is 25.94 degrees. The mean temperature of the warmest quarter is 28.79 degrees. The mean temperature of the coldest quarter is 25.94 degrees. The annual precipitation is 318.0 mm. The precipitation of the wettest month is 96.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 121.15. The precipitation of the wettest quarter is 175.0 mm. The precipitation of the driest quarter is 4.0 mm. The precipitation of the warmest quarter is 118.0 mm. The precipitation of the coldest quarter is 4.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius mongolus", + "(B) Laniarius luehderi", + "(C) Acryllium vulturinum", + "(D) Sheppardia polioptera", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13474964_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0459", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.893886 and latitude -1.640236 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Glareola ocularis", + "(B) Illadopsis pyrrhoptera", + "(C) Arizelocichla masukuensis", + "(D) Pternistis leucoscepus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17524706_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0460", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.105425 and latitude -0.279641 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Macrosphenus kretschmeri", + "(C) Crex crex", + "(D) Cisticola cinereolus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14796716_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0461", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120032 and latitude -0.395452 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdus abyssinicus", + "(B) Eurillas curvirostris", + "(C) Campethera mombassica", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17011328_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0462", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120495 and latitude -0.366381 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco peregrinus", + "(B) Iduna natalensis", + "(C) Fulica cristata", + "(D) Anas sparsa", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17705838_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0463", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469800 and latitude -0.597199 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola carruthersi", + "(B) Lagonosticta senegala", + "(C) Alopochen aegyptiaca", + "(D) Stactolaema olivacea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22469746_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0464", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.740000 and latitude -3.928000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Malaconotus blanchoti", + "(B) Accipiter ovampensis", + "(C) Dendrocygna viduata", + "(D) Oriolus auratus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6200626_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0465", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.113897 and latitude -0.415413 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes nigroventris", + "(B) Struthio camelus", + "(C) Sylvia borin", + "(D) Coracias naevius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214606_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0466", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.089000 and latitude -0.307217 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Halcyon chelicuti", + "(B) Alopochen aegyptiaca", + "(C) Onychognathus walleri", + "(D) Chroicocephalus cirrocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10206039_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0467", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309045 and latitude -0.144258 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Lagonosticta rufopicta", + "(C) Bradypterus baboecala", + "(D) Apaloderma narina", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13918587_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0468", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450073 and latitude -0.742200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numenius arquata", + "(B) Lanius humeralis", + "(C) Hieraaetus wahlbergi", + "(D) Onychognathus morio", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20973630_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0469", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.403588 and latitude -0.760829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zosterops senegalensis", + "(B) Synoicus adansonii", + "(C) Cisticola galactotes", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1770518_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0470", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.961799 and latitude -0.234116 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spermestes cucullata", + "(B) Limosa limosa", + "(C) Streptopelia capicola", + "(D) Tricholaema lacrymosa", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19362992_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0471", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.160199 and latitude -0.584321 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius humeralis", + "(B) Pogoniulus pusillus", + "(C) Chrysococcyx cupreus", + "(D) Telophorus sulfureopectus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5656068_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0472", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307308 and latitude -0.142926 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Estrilda kandti", + "(B) Riparia paludicola", + "(C) Passer domesticus", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12832036_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0473", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.460528 and latitude -0.739498 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Crex crex", + "(C) Oriolus percivali", + "(D) Laniarius aethiopicus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21640693_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0474", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.603889 and latitude -0.673041 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.91 degrees. The mean diurnal range is 10.14 degrees. The isothermality is 71.62. The temperature seasonality (100 times the standard deviation) is 130.14. The max temperature of the warmest month is 35.39 degrees. The min temperature of the coldest month is 21.24 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 28.23 degrees. The mean temperature of the driest quarter is 26.16 degrees. The mean temperature of the warmest quarter is 29.46 degrees. The mean temperature of the coldest quarter is 26.16 degrees. The annual precipitation is 417.0 mm. The precipitation of the wettest month is 110.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 103.09. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 145.0 mm. The precipitation of the coldest quarter is 16.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cryptospiza salvadorii", + "(B) Guttera pucherani", + "(C) Streptopelia capicola", + "(D) Anthus sokokensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974502_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0475", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.313000 and latitude -2.304400 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.09 degrees. The mean diurnal range is 7.52 degrees. The isothermality is 66.86. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 33.17 degrees. The min temperature of the coldest month is 21.92 degrees. The temperature annual range is 11.25 degrees. The mean temperature of the wettest quarter is 27.14 degrees. The mean temperature of the driest quarter is 28.26 degrees. The mean temperature of the warmest quarter is 28.48 degrees. The mean temperature of the coldest quarter is 25.50 degrees. The annual precipitation is 806.0 mm. The precipitation of the wettest month is 149.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 56.60. The precipitation of the wettest quarter is 348.0 mm. The precipitation of the driest quarter is 81.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 160.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Indicator minor", + "(B) Calidris pugnax", + "(C) Apus affinis", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3059463_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0476", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.032930 and latitude 0.718093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Glaucidium perlatum", + "(B) Crithagra striolata", + "(C) Streptopelia decipiens", + "(D) Melierax metabates", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10504169_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0477", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.513280 and latitude -0.193907 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Oena capensis", + "(C) Mirafra collaris", + "(D) Anthus cervinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462536_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0478", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.615017 and latitude -2.982955 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Lanius excubitoroides", + "(C) Balearica regulorum", + "(D) Sylvietta brachyura", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12065665_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0479", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.026337 and latitude -2.514263 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.85 degrees. The mean diurnal range is 12.31 degrees. The isothermality is 72.62. The temperature seasonality (100 times the standard deviation) is 142.97. The max temperature of the warmest month is 30.87 degrees. The min temperature of the coldest month is 13.92 degrees. The temperature annual range is 16.95 degrees. The mean temperature of the wettest quarter is 22.68 degrees. The mean temperature of the driest quarter is 20.07 degrees. The mean temperature of the warmest quarter is 23.33 degrees. The mean temperature of the coldest quarter is 19.80 degrees. The annual precipitation is 587.0 mm. The precipitation of the wettest month is 125.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 81.83. The precipitation of the wettest quarter is 262.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 177.0 mm. The precipitation of the coldest quarter is 15.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Gelochelidon nilotica", + "(C) Motacilla aguimp", + "(D) Hyliota australis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7148979_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0480", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946283 and latitude -0.063598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chlorocichla flaviventris", + "(B) Dendrocygna viduata", + "(C) Oreolais pulcher", + "(D) Phaethon lepturus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22563197_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0481", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250000 and latitude -0.432800 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas capensis", + "(B) Indicator variegatus", + "(C) Anthreptes longuemarei", + "(D) Coracina caesia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11221555_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0482", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.463341 and latitude 0.424458 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.07 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 81.77. The temperature seasonality (100 times the standard deviation) is 79.91. The max temperature of the warmest month is 24.33 degrees. The min temperature of the coldest month is 9.18 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 15.02 degrees. The mean temperature of the driest quarter is 16.53 degrees. The mean temperature of the warmest quarter is 17.04 degrees. The mean temperature of the coldest quarter is 15.02 degrees. The annual precipitation is 1155.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 49.05. The precipitation of the wettest quarter is 405.0 mm. The precipitation of the driest quarter is 131.0 mm. The precipitation of the warmest quarter is 294.0 mm. The precipitation of the coldest quarter is 405.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus castaneiceps", + "(B) Columba arquatrix", + "(C) Hieraaetus ayresii", + "(D) Apus caffer", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290835_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0483", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326134 and latitude -0.717464 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spilopelia senegalensis", + "(B) Phoenicurus phoenicurus", + "(C) Apalis flavida", + "(D) Cecropis daurica", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17291269_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0484", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.684506 and latitude -4.058453 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nycticorax nycticorax", + "(B) Terpsiphone rufiventer", + "(C) Columba livia", + "(D) Chalcomitra senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20451066_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0485", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453735 and latitude -0.729773 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oenanthe pileata", + "(B) Myrmecocichla aethiops", + "(C) Buteo augur", + "(D) Caprimulgus stellatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15873929_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0486", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.878873 and latitude 1.048376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Euplectes diadematus", + "(C) Tachybaptus ruficollis", + "(D) Macronyx ameliae", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8685118_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0487", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.083000 and latitude -0.366000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Xenus cinereus", + "(C) Polihierax semitorquatus", + "(D) Estrilda rhodopyga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11222896_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0488", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.487602 and latitude -0.699514 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Andropadus importunus", + "(B) Streptopelia semitorquata", + "(C) Falco biarmicus", + "(D) Cisticola lateralis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436304_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0489", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.628074 and latitude -0.490381 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus strepitans", + "(B) Caprimulgus europaeus", + "(C) Colius striatus", + "(D) Lanius somalicus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778305_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0490", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.665400 and latitude -4.078700 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Plocepasser donaldsoni", + "(B) Corvus splendens", + "(C) Scleroptila elgonensis", + "(D) Uraeginthus bengalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3061002_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0491", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.496000 and latitude -0.574000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus splendens", + "(B) Alopochen aegyptiaca", + "(C) Dicrurus adsimilis", + "(D) Treron waalia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17120227_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0492", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420364 and latitude -0.772920 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ortyxelos meiffrenii", + "(B) Alopochen aegyptiaca", + "(C) Onychoprion fuscatus", + "(D) Euplectes franciscanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10746405_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0493", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.003179 and latitude -1.382342 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vidua hypocherina", + "(B) Tauraco schalowi", + "(C) Circaetus cinerascens", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17063854_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0494", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.723417 and latitude -4.025348 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chalcomitra amethystina", + "(B) Strix woodfordii", + "(C) Merops revoilii", + "(D) Columba livia", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10702920_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0495", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.358615 and latitude -0.746634 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Melierax poliopterus", + "(B) Streptopelia semitorquata", + "(C) Circaetus pectoralis", + "(D) Hippolais icterina", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563404_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0496", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474561 and latitude -0.889059 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hippolais languida", + "(B) Columba guinea", + "(C) Hirundo rustica", + "(D) Nicator gularis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8149007_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0497", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.205574 and latitude -0.523311 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Jynx ruficollis", + "(C) Circus pygargus", + "(D) Corvus rhipidurus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16126491_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0498", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.719954 and latitude -4.018641 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Trachyphonus darnaudii", + "(B) Apus affinis", + "(C) Phaethon lepturus", + "(D) Lamprotornis purpuroptera", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070702_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0499", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421278 and latitude -0.675163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mycteria ibis", + "(B) Calidris minuta", + "(C) Eurillas latirostris", + "(D) Dicrurus adsimilis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18607968_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0500", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493883 and latitude -0.573706 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardea melanocephala", + "(B) Cisticola bodessa", + "(C) Buphagus erythrorynchus", + "(D) Eremopterix leucopareia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19693753_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0501", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.686870 and latitude -0.489771 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Hirundo angolensis", + "(C) Asio abyssinicus", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16889770_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0502", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492103 and latitude -0.572615 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus barbatus", + "(B) Burhinus senegalensis", + "(C) Acrocephalus arundinaceus", + "(D) Anomalospiza imberbis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18099519_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0503", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.382245 and latitude -0.719936 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chloropicus goertae", + "(B) Bubalornis albirostris", + "(C) Streptopelia semitorquata", + "(D) Colius leucocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563225_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0504", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.087110 and latitude 2.708801 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.00 degrees. The mean diurnal range is 10.50 degrees. The isothermality is 73.28. The temperature seasonality (100 times the standard deviation) is 119.24. The max temperature of the warmest month is 33.35 degrees. The min temperature of the coldest month is 19.02 degrees. The temperature annual range is 14.33 degrees. The mean temperature of the wettest quarter is 26.83 degrees. The mean temperature of the driest quarter is 24.45 degrees. The mean temperature of the warmest quarter is 27.49 degrees. The mean temperature of the coldest quarter is 24.45 degrees. The annual precipitation is 270.0 mm. The precipitation of the wettest month is 80.0 mm. The precipitation of the driest month is 0.0 mm. The precipitation seasonality (coefficient of variation) is 109.07. The precipitation of the wettest quarter is 132.0 mm. The precipitation of the driest quarter is 2.0 mm. The precipitation of the warmest quarter is 56.0 mm. The precipitation of the coldest quarter is 2.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Halcyon senegaloides", + "(B) Vanellus coronatus", + "(C) Aquila rapax", + "(D) Lybius leucocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22790390_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0505", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471482 and latitude -0.828351 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris venustus", + "(B) Alopochen aegyptiaca", + "(C) Corvus capensis", + "(D) Ploceus castaneiceps", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10343530_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0506", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.217718 and latitude -0.407208 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Passer castanopterus", + "(C) Glaucidium capense", + "(D) Torgos tracheliotos", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791987_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0507", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117899 and latitude -0.380129 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus neumanni", + "(B) Cercococcyx montanus", + "(C) Linurgus olivaceus", + "(D) Struthio camelus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10746561_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0508", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493826 and latitude -0.574831 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Cisticola galactotes", + "(C) Columba guinea", + "(D) Tricholaema lacrymosa", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232869_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0509", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.207549 and latitude -0.387451 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Aquila rapax", + "(B) Turtur chalcospilos", + "(C) Apus horus", + "(D) Cichladusa arquata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791984_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0510", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444822 and latitude -0.724114 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Glareola ocularis", + "(C) Hydroprogne caspia", + "(D) Neotis heuglinii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16776594_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0511", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.261919 and latitude -0.448123 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracina pectoralis", + "(B) Stactolaema olivacea", + "(C) Anas erythrorhyncha", + "(D) Euplectes macroura", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8442955_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0512", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419407 and latitude -0.591604 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Terpsiphone viridis", + "(B) Haliaeetus vocifer", + "(C) Prionops retzii", + "(D) Eremomela turneri", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6864111_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0513", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452536 and latitude -0.737041 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Neocossyphus poensis", + "(B) Anous stolidus", + "(C) Streptopelia capicola", + "(D) Hippolais icterina", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20290844_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0514", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.410863 and latitude -0.767313 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alcedo quadribrachys", + "(B) Falco naumanni", + "(C) Alopochen aegyptiaca", + "(D) Tringa stagnatilis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7725548_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0515", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.928646 and latitude 2.241613 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.99 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 81.08. The temperature seasonality (100 times the standard deviation) is 79.21. The max temperature of the warmest month is 30.29 degrees. The min temperature of the coldest month is 15.88 degrees. The temperature annual range is 14.40 degrees. The mean temperature of the wettest quarter is 23.83 degrees. The mean temperature of the driest quarter is 22.08 degrees. The mean temperature of the warmest quarter is 24.02 degrees. The mean temperature of the coldest quarter is 22.01 degrees. The annual precipitation is 347.0 mm. The precipitation of the wettest month is 81.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 78.03. The precipitation of the wettest quarter is 164.0 mm. The precipitation of the driest quarter is 27.0 mm. The precipitation of the warmest quarter is 139.0 mm. The precipitation of the coldest quarter is 31.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gymnoris pyrgita", + "(B) Ptilopachus petrosus", + "(C) Cursorius temminckii", + "(D) Amandava subflava", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15234248_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0516", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.465658 and latitude -0.693972 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus longipennis", + "(B) Melaenornis edolioides", + "(C) Streptopelia semitorquata", + "(D) Oena capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436290_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0517", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425885 and latitude -0.750477 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Anas capensis", + "(C) Rallus caerulescens", + "(D) Mycteria ibis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5289638_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0518", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.758317 and latitude -3.569227 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gallinula chloropus", + "(B) Streptopelia capicola", + "(C) Thalasseus bengalensis", + "(D) Platalea alba", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12511852_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0519", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298536 and latitude -0.666360 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastes simplex", + "(B) Gymnoris pyrgita", + "(C) Streptopelia capicola", + "(D) Charadrius pallidus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15283938_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0520", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125347 and latitude -0.311612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calamonastes simplex", + "(B) Thamnolaea cinnamomeiventris", + "(C) Centropus superciliosus", + "(D) Mirafra gilletti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21097299_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0521", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952315 and latitude 0.009791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anaplectes jubaensis", + "(B) Prinia rufifrons", + "(C) Bubalornis niger", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925707_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0522", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298562 and latitude -0.665901 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cercotrichas leucophrys", + "(B) Streptopelia semitorquata", + "(C) Prionops retzii", + "(D) Crithagra buchanani", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15145101_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0523", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.187452 and latitude -0.499206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Pternistis hildebrandti", + "(C) Lamprotornis purpuroptera", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284271_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0524", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.396730 and latitude -0.803697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ptilostomus afer", + "(B) Asio abyssinicus", + "(C) Anthus cervinus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12596376_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0525", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.377389 and latitude -0.820922 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Charadrius tricollaris", + "(C) Hirundo aethiopica", + "(D) Halcyon albiventris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17374004_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0526", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111946 and latitude -0.402734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ficedula semitorquata", + "(B) Porphyrio alleni", + "(C) Alopochen aegyptiaca", + "(D) Brunhilda erythronotos", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20726818_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0527", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.131025 and latitude -0.310532 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco peregrinus", + "(B) Anaplectes jubaensis", + "(C) Phoeniconaias minor", + "(D) Macronyx ameliae", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874277_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0528", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.449460 and latitude -0.717641 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Illadopsis rufipennis", + "(B) Alopochen aegyptiaca", + "(C) Polemaetus bellicosus", + "(D) Cinnyris chalcomelas", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19317171_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0529", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988431 and latitude -0.219000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Vanellus superciliosus", + "(C) Lanius cabanisi", + "(D) Oenanthe pleschanka", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119851_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0530", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444690 and latitude -0.716908 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus campestris", + "(B) Caprimulgus vexillarius", + "(C) Spilopelia senegalensis", + "(D) Cyanomitra veroxii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15474902_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0531", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.577802 and latitude 0.334909 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Apus affinis", + "(C) Hieraaetus pennatus", + "(D) Cecropis senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5120073_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0532", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465083 and latitude -0.595619 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Chrysococcyx caprius", + "(C) Eurystomus glaucurus", + "(D) Oenanthe scotocerca", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21686375_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0533", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.616972 and latitude -0.559458 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola aridulus", + "(B) Streptopelia capicola", + "(C) Platysteira concreta", + "(D) Colius leucocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15208954_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0534", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.400280 and latitude -0.772281 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Amadina fasciata", + "(B) Egretta garzetta", + "(C) Numenius phaeopus", + "(D) Phoeniconaias minor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17539501_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0535", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.113925 and latitude -0.438052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Arizelocichla nigriceps", + "(B) Bradornis microrhynchus", + "(C) Zosterops mbuluensis", + "(D) Campocolinus coqui", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819665_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0536", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.333855 and latitude -0.830245 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nectarinia kilimensis", + "(B) Lagonosticta rufopicta", + "(C) Merops variegatus", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3754839_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0537", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.736928 and latitude -3.980726 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus hypochloris", + "(B) Cossypha caffra", + "(C) Streptopelia capicola", + "(D) Tringa ochropus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14765490_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0538", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108072 and latitude -0.309220 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba livia", + "(B) Sarkidiornis melanotos", + "(C) Spatula hottentota", + "(D) Nectarinia johnstoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304151_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0539", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.919813 and latitude 2.097865 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.41 degrees. The mean diurnal range is 10.92 degrees. The isothermality is 80.29. The temperature seasonality (100 times the standard deviation) is 79.33. The max temperature of the warmest month is 27.37 degrees. The min temperature of the coldest month is 13.77 degrees. The temperature annual range is 13.60 degrees. The mean temperature of the wettest quarter is 21.29 degrees. The mean temperature of the driest quarter is 19.51 degrees. The mean temperature of the warmest quarter is 21.46 degrees. The mean temperature of the coldest quarter is 19.45 degrees. The annual precipitation is 473.0 mm. The precipitation of the wettest month is 106.0 mm. The precipitation of the driest month is 9.0 mm. The precipitation seasonality (coefficient of variation) is 70.90. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 51.0 mm. The precipitation of the warmest quarter is 178.0 mm. The precipitation of the coldest quarter is 58.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus dichrocephalus", + "(B) Lagonosticta rufopicta", + "(C) Prionops plumatus", + "(D) Clamator jacobinus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3633236_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0540", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.354062 and latitude -0.563343 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Histurgops ruficauda", + "(B) Alopochen aegyptiaca", + "(C) Cinnyris pulchellus", + "(D) Geokichla gurneyi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22693049_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0541", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.522774 and latitude -0.671358 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.88 degrees. The mean diurnal range is 12.63 degrees. The isothermality is 77.21. The temperature seasonality (100 times the standard deviation) is 104.78. The max temperature of the warmest month is 21.80 degrees. The min temperature of the coldest month is 5.44 degrees. The temperature annual range is 16.36 degrees. The mean temperature of the wettest quarter is 13.82 degrees. The mean temperature of the driest quarter is 11.49 degrees. The mean temperature of the warmest quarter is 14.03 degrees. The mean temperature of the coldest quarter is 11.42 degrees. The annual precipitation is 1179.0 mm. The precipitation of the wettest month is 219.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 53.00. The precipitation of the wettest quarter is 500.0 mm. The precipitation of the driest quarter is 174.0 mm. The precipitation of the warmest quarter is 392.0 mm. The precipitation of the coldest quarter is 179.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hedydipna pallidigaster", + "(B) Pyrenestes ostrinus", + "(C) Streptopelia lugens", + "(D) Argya aylmeri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22529478_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0542", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.398854 and latitude -0.801637 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Creatophora cinerea", + "(B) Alopochen aegyptiaca", + "(C) Smutsornis africanus", + "(D) Cisticola galactotes", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19019798_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0543", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.798427 and latitude -3.808263 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Catriscus brevirostris", + "(B) Ploceus cucullatus", + "(C) Bradypterus cinnamomeus", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7049464_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0544", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323368 and latitude -0.815791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bleda syndactylus", + "(B) Gypaetus barbatus", + "(C) Alopochen aegyptiaca", + "(D) Urocolius macrourus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925737_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0545", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450879 and latitude -0.739549 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus leucophrys", + "(B) Ardeola ralloides", + "(C) Buteo rufinus", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21073073_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0546", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.656872 and latitude -0.297796 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turtur afer", + "(B) Prionops plumatus", + "(C) Spatula hottentota", + "(D) Passer griseus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20348961_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0547", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285811 and latitude 0.491439 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chalcomitra senegalensis", + "(B) Corvus albus", + "(C) Iduna natalensis", + "(D) Ortygospiza atricollis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4272139_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0548", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.964990 and latitude -0.167455 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas crecca", + "(B) Nilaus afer", + "(C) Columba guinea", + "(D) Pternistis castaneicollis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12096559_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0549", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.320640 and latitude -0.669453 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Chalcomitra amethystina", + "(C) Ploceus spekei", + "(D) Falco rupicolus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3224252_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0550", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428400 and latitude -0.725289 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus cinnamomeus", + "(B) Platysteira castanea", + "(C) Alopochen aegyptiaca", + "(D) Pachycoccyx audeberti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025953_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0551", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.852259 and latitude 1.065839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phylloscopus budongoensis", + "(B) Terathopius ecaudatus", + "(C) Sheppardia gunningi", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6540695_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0552", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424205 and latitude -0.769019 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Curruca boehmi", + "(B) Rhaphidura sabini", + "(C) Accipiter ovampensis", + "(D) Microcarbo africanus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8279615_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0553", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.720935 and latitude -2.257880 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.40 degrees. The mean diurnal range is 11.22 degrees. The isothermality is 69.37. The temperature seasonality (100 times the standard deviation) is 144.94. The max temperature of the warmest month is 30.83 degrees. The min temperature of the coldest month is 14.66 degrees. The temperature annual range is 16.17 degrees. The mean temperature of the wettest quarter is 22.92 degrees. The mean temperature of the driest quarter is 20.33 degrees. The mean temperature of the warmest quarter is 23.99 degrees. The mean temperature of the coldest quarter is 20.33 degrees. The annual precipitation is 604.0 mm. The precipitation of the wettest month is 165.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 104.51. The precipitation of the wettest quarter is 316.0 mm. The precipitation of the driest quarter is 7.0 mm. The precipitation of the warmest quarter is 217.0 mm. The precipitation of the coldest quarter is 7.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera caroli", + "(B) Turtur chalcospilos", + "(C) Bradypterus cinnamomeus", + "(D) Spiloptila clamans", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7302297_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0554", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.281625 and latitude -0.758971 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus caffer", + "(B) Cuculus poliocephalus", + "(C) Cossypha heuglini", + "(D) Cursorius temminckii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563280_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0555", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.085625 and latitude -0.315834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spatula hottentota", + "(B) Melierax poliopterus", + "(C) Sterna hirundo", + "(D) Phyllolais pulchella", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6610312_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0556", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084123 and latitude -0.310148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus morio", + "(B) Euplectes hordeaceus", + "(C) Struthio camelus", + "(D) Phyllolais pulchella", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12667989_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0557", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952508 and latitude 0.009905 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychoprion anaethetus", + "(B) Ortygornis sephaena", + "(C) Estrilda troglodytes", + "(D) Egretta ardesiaca", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925726_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0558", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.730919 and latitude -3.989027 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Jynx torquilla", + "(B) Alopochen aegyptiaca", + "(C) Falco peregrinus", + "(D) Chelictinia riocourii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17760266_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0559", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.576116 and latitude -3.166533 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Argya rubiginosa", + "(B) Zosterops silvanus", + "(C) Oena capensis", + "(D) Alcedo semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22550133_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0560", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120505 and latitude -0.313568 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Uraeginthus bengalus", + "(B) Numida meleagris", + "(C) Acrocephalus schoenobaenus", + "(D) Ploceus pelzelni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683607_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0561", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250511 and latitude -0.406276 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola brunnescens", + "(B) Tricholaema hirsuta", + "(C) Alopochen aegyptiaca", + "(D) Bycanistes bucinator", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10900737_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0562", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285800 and latitude 0.491500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Motacilla flava", + "(B) Milvus migrans", + "(C) Pternistis squamatus", + "(D) Ardeotis kori", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9205333_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0563", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.582116 and latitude 0.349416 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus berliozi", + "(B) Columba livia", + "(C) Crithagra atrogularis", + "(D) Lagonosticta rufopicta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10223384_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0564", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.270378 and latitude -0.816443 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spatula hottentota", + "(B) Zosterops kikuyuensis", + "(C) Pternistis hildebrandti", + "(D) Crithagra dorsostriata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1770521_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0565", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.903004 and latitude -3.083243 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.19 degrees. The mean diurnal range is 7.97 degrees. The isothermality is 67.30. The temperature seasonality (100 times the standard deviation) is 123.33. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 19.64 degrees. The temperature annual range is 11.84 degrees. The mean temperature of the wettest quarter is 25.21 degrees. The mean temperature of the driest quarter is 26.43 degrees. The mean temperature of the warmest quarter is 26.64 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 884.0 mm. The precipitation of the wettest month is 187.0 mm. The precipitation of the driest month is 12.0 mm. The precipitation seasonality (coefficient of variation) is 61.39. The precipitation of the wettest quarter is 385.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 183.0 mm. The precipitation of the coldest quarter is 188.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hyliota flavigaster", + "(B) Prinia subflava", + "(C) Tchagra senegalus", + "(D) Turnix nanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18990924_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0566", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.848626 and latitude -1.687800 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco dickinsoni", + "(B) Sula leucogaster", + "(C) Scleroptila shelleyi", + "(D) Saxicola torquatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17121786_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0567", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.755376 and latitude 0.568924 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.52 degrees. The mean diurnal range is 12.84 degrees. The isothermality is 83.19. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 16.30 degrees. The temperature annual range is 15.43 degrees. The mean temperature of the wettest quarter is 23.34 degrees. The mean temperature of the driest quarter is 22.72 degrees. The mean temperature of the warmest quarter is 24.38 degrees. The mean temperature of the coldest quarter is 22.72 degrees. The annual precipitation is 533.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.08. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Illadopsis pyrrhoptera", + "(B) Struthio molybdophanes", + "(C) Lamprotornis hildebrandti", + "(D) Lamprotornis purpuroptera", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22414217_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0568", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432900 and latitude -0.714300 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zosterops silvanus", + "(B) Phoeniculus damarensis", + "(C) Caprimulgus tristigma", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10608444_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0569", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492268 and latitude -0.572895 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius somalicus", + "(B) Guttera pucherani", + "(C) Scopus umbretta", + "(D) Lanius mackinnoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10494075_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0570", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.291267 and latitude 0.498667 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Scopus umbretta", + "(B) Chloropicus spodocephalus", + "(C) Streptopelia semitorquata", + "(D) Phoenicopterus roseus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7716763_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0571", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469527 and latitude -0.596445 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Mirafra collaris", + "(C) Laniarius mufumbiri", + "(D) Lanius minor", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258662_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0572", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.781843 and latitude -3.596470 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus insignis", + "(B) Otus scops", + "(C) Eupodotis gindiana", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12531865_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0573", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.060133 and latitude -0.354307 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Neotis heuglinii", + "(B) Clamator glandarius", + "(C) Poeoptera stuhlmanni", + "(D) Chlidonias hybrida", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864288_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0574", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.114387 and latitude -0.286709 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coccopygia quartinia", + "(B) Cypsiurus parvus", + "(C) Colius striatus", + "(D) Lybius bidentatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526025_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0575", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.091990 and latitude 0.537357 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.14 degrees. The mean diurnal range is 12.73 degrees. The isothermality is 82.07. The temperature seasonality (100 times the standard deviation) is 79.15. The max temperature of the warmest month is 26.58 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.51 degrees. The mean temperature of the wettest quarter is 17.14 degrees. The mean temperature of the driest quarter is 18.58 degrees. The mean temperature of the warmest quarter is 19.14 degrees. The mean temperature of the coldest quarter is 17.14 degrees. The annual precipitation is 1225.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 52.85. The precipitation of the wettest quarter is 491.0 mm. The precipitation of the driest quarter is 121.0 mm. The precipitation of the warmest quarter is 264.0 mm. The precipitation of the coldest quarter is 491.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Gypohierax angolensis", + "(C) Onychognathus salvadorii", + "(D) Halcyon senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15874060_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0576", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308579 and latitude -0.145117 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Thalassornis leuconotus", + "(B) Clamator levaillantii", + "(C) Apalis porphyrolaema", + "(D) Cisticola lais", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19266793_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0577", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474706 and latitude -0.554303 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia lugens", + "(B) Smutsornis africanus", + "(C) Calidris temminckii", + "(D) Macronyx aurantiigula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21213112_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0578", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.648853 and latitude -0.508865 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Apalis jacksoni", + "(C) Chelictinia riocourii", + "(D) Onychognathus tenuirostris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778924_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0579", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.106168 and latitude -0.403316 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Crithagra koliensis", + "(C) Crithagra donaldsoni", + "(D) Alcedo quadribrachys", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4122705_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0580", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.373847 and latitude -0.802140 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chloropicus xantholophus", + "(B) Turdoides sharpei", + "(C) Streptopelia decipiens", + "(D) Cercotrichas leucophrys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6520979_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0581", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.430243 and latitude -0.629545 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Otus senegalensis", + "(B) Elminia longicauda", + "(C) Lagonosticta senegala", + "(D) Cossypha heuglini", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5307845_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0582", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401900 and latitude -0.767200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numenius arquata", + "(B) Sylvia borin", + "(C) Cypsiurus parvus", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10561143_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0583", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129222 and latitude -0.304008 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Zosterops mbuluensis", + "(C) Gorsachius leuconotus", + "(D) Fraseria caerulescens", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11887905_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0584", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.693575 and latitude -4.047847 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Amaurornis marginalis", + "(C) Dicrurus adsimilis", + "(D) Vidua funerea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13608231_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0585", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490715 and latitude -0.595653 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Oriolus percivali", + "(C) Melaniparus albiventris", + "(D) Todiramphus chloris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10859569_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0586", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.034991 and latitude -0.269870 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubulcus ibis", + "(B) Crithagra sulphurata", + "(C) Muscicapa aquatica", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5533753_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0587", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263924 and latitude -0.821967 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Apus barbatus", + "(C) Corvus capensis", + "(D) Apus berliozi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756371_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0588", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425708 and latitude -0.720986 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Estrilda nonnula", + "(B) Alopochen aegyptiaca", + "(C) Chalcomitra amethystina", + "(D) Torgos tracheliotos", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20832213_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0589", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108066 and latitude -0.306113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Butorides striata", + "(B) Hieraaetus pennatus", + "(C) Anas undulata", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5517500_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0590", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.467638 and latitude -0.595870 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola carruthersi", + "(B) Passer shelleyi", + "(C) Podica senegalensis", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11376055_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0591", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425924 and latitude -0.618675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nigrita fusconotus", + "(B) Cisticola carruthersi", + "(C) Buteo buteo", + "(D) Lamprotornis albicapillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520785_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0592", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.216155 and latitude -0.435056 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zapornia flavirostra", + "(B) Histurgops ruficauda", + "(C) Ceuthmochares australis", + "(D) Netta erythrophthalma", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283240_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0593", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.410694 and latitude -0.777785 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola juncidis", + "(B) Pogonocichla stellata", + "(C) Alopochen aegyptiaca", + "(D) Amadina fasciata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14289607_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0594", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.416544 and latitude -0.798903 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tachybaptus ruficollis", + "(B) Cossypha natalensis", + "(C) Dicrurus modestus", + "(D) Amaurornis marginalis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8692210_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0595", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.419316 and latitude 0.685222 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.22 degrees. The mean diurnal range is 12.17 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.56. The max temperature of the warmest month is 29.24 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 14.75 degrees. The mean temperature of the wettest quarter is 21.12 degrees. The mean temperature of the driest quarter is 21.89 degrees. The mean temperature of the warmest quarter is 22.17 degrees. The mean temperature of the coldest quarter is 20.41 degrees. The annual precipitation is 1520.0 mm. The precipitation of the wettest month is 234.0 mm. The precipitation of the driest month is 52.0 mm. The precipitation seasonality (coefficient of variation) is 42.70. The precipitation of the wettest quarter is 580.0 mm. The precipitation of the driest quarter is 190.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 365.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Treron waalia", + "(C) Rhinoptilus cinctus", + "(D) Pseudhirundo griseopyga", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15752435_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0596", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308712 and latitude -0.144087 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco fasciinucha", + "(B) Thalassornis leuconotus", + "(C) Crithagra hyposticta", + "(D) Melaniparus thruppi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20920735_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0597", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.417357 and latitude -0.667544 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Erythrocercus holochlorus", + "(B) Otus senegalensis", + "(C) Numida meleagris", + "(D) Apalis fuscigularis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19266636_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0598", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362797 and latitude -0.860224 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Caprimulgus fraenatus", + "(B) Numida meleagris", + "(C) Euplectes axillaris", + "(D) Nectarinia tacazze", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16367492_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0599", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.703054 and latitude -4.044854 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Passer suahelicus", + "(C) Corvus albus", + "(D) Megabyas flammulatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17029554_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0600", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489093 and latitude -0.625338 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Aplopelia larvata", + "(B) Coturnix coturnix", + "(C) Neophedina cincta", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11604894_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0601", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.733470 and latitude -3.989965 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rynchops flavirostris", + "(B) Falco naumanni", + "(C) Anthus cinnamomeus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12524048_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0602", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.282690 and latitude -0.734770 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco naumanni", + "(B) Ptilopachus petrosus", + "(C) Alopochen aegyptiaca", + "(D) Euplectes franciscanus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700360_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0603", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418351 and latitude -0.720677 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Notopholia corusca", + "(B) Lanius cabanisi", + "(C) Ciconia ciconia", + "(D) Spatula hottentota", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22239295_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0604", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465223 and latitude -0.747529 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus rhipidurus", + "(B) Laniarius ruficeps", + "(C) Chloropicus goertae", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10061779_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0605", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411910 and latitude -0.763410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Cecropis abyssinica", + "(C) Acrocephalus schoenobaenus", + "(D) Calidris ferruginea", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4929439_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0606", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090260 and latitude -0.356779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pelecanus onocrotalus", + "(B) Pogonocichla stellata", + "(C) Oxyura maccoa", + "(D) Neotis denhami", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L920937_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0607", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.822843 and latitude -3.824118 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pogoniulus bilineatus", + "(B) Zosterops kikuyuensis", + "(C) Phoeniculus damarensis", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259752_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0608", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.379367 and latitude 0.303932 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.77 degrees. The mean diurnal range is 12.44 degrees. The isothermality is 82.15. The temperature seasonality (100 times the standard deviation) is 77.61. The max temperature of the warmest month is 24.11 degrees. The min temperature of the coldest month is 8.96 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 14.77 degrees. The mean temperature of the driest quarter is 16.24 degrees. The mean temperature of the warmest quarter is 16.72 degrees. The mean temperature of the coldest quarter is 14.76 degrees. The annual precipitation is 1204.0 mm. The precipitation of the wettest month is 189.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 50.25. The precipitation of the wettest quarter is 449.0 mm. The precipitation of the driest quarter is 137.0 mm. The precipitation of the warmest quarter is 289.0 mm. The precipitation of the coldest quarter is 441.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Agapornis canus", + "(C) Motacilla flava", + "(D) Chrysococcyx caprius", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8123512_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0609", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334920 and latitude -0.825791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Brunhilda erythronotos", + "(B) Glareola ocularis", + "(C) Alopochen aegyptiaca", + "(D) Phylloscopus ruficapilla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16490176_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0610", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.122811 and latitude -0.414418 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Circaetus fasciolatus", + "(C) Sheppardia polioptera", + "(D) Anhinga rufa", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20161142_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0611", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.597244 and latitude -3.122050 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acryllium vulturinum", + "(B) Spilopelia senegalensis", + "(C) Cuculus clamosus", + "(D) Oenanthe lugubris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14898277_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0612", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.124747 and latitude -0.388680 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Platysteira concreta", + "(B) Butastur rufipennis", + "(C) Fraseria lendu", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20174419_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0613", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306596 and latitude -0.885051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prionops poliolophus", + "(B) Myrmecocichla aethiops", + "(C) Jynx torquilla", + "(D) Amadina fasciata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L989976_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0614", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.459984 and latitude -0.738214 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sterna repressa", + "(B) Colius striatus", + "(C) Chrysococcyx klaas", + "(D) Cisticola aberdare", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16767027_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0615", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726754 and latitude -3.999883 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tringa nebularia", + "(B) Sylvietta leucophrys", + "(C) Alopochen aegyptiaca", + "(D) Trochocercus cyanomelas", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14558153_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0616", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.312098 and latitude 0.584058 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Plectropterus gambensis", + "(B) Cuculus clamosus", + "(C) Tachybaptus ruficollis", + "(D) Euplectes jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5186646_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0617", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221335 and latitude -0.406675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Batis mixta", + "(C) Pelecanus onocrotalus", + "(D) Tockus erythrorhynchus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1793672_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0618", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.712955 and latitude -3.948034 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis alticola", + "(B) Lagonosticta senegala", + "(C) Turtur chalcospilos", + "(D) Tockus erythrorhynchus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11436924_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0619", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116630 and latitude -0.410553 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius dorsalis", + "(B) Phoenicopterus roseus", + "(C) Euplectes nigroventris", + "(D) Microcarbo africanus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819859_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0620", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.571038 and latitude -0.607497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus crassirostris", + "(B) Alopochen aegyptiaca", + "(C) Oena capensis", + "(D) Halcyon chelicuti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12629846_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0621", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.071567 and latitude -0.315449 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Macronyx croceus", + "(B) Poicephalus rufiventris", + "(C) Euplectes capensis", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4213876_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0622", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491776 and latitude -0.573038 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coturnix coturnix", + "(B) Cisticola ayresii", + "(C) Hirundo angolensis", + "(D) Apalis rufogularis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9240465_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0623", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.119614 and latitude -0.371656 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Phoeniculus purpureus", + "(C) Thalassornis leuconotus", + "(D) Eremopterix leucotis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2853940_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0624", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.109042 and latitude 0.388282 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.43 degrees. The mean diurnal range is 10.72 degrees. The isothermality is 73.81. The temperature seasonality (100 times the standard deviation) is 117.59. The max temperature of the warmest month is 36.23 degrees. The min temperature of the coldest month is 21.71 degrees. The temperature annual range is 14.53 degrees. The mean temperature of the wettest quarter is 28.48 degrees. The mean temperature of the driest quarter is 26.91 degrees. The mean temperature of the warmest quarter is 29.90 degrees. The mean temperature of the coldest quarter is 26.91 degrees. The annual precipitation is 337.0 mm. The precipitation of the wettest month is 98.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 107.78. The precipitation of the wettest quarter is 155.0 mm. The precipitation of the driest quarter is 14.0 mm. The precipitation of the warmest quarter is 132.0 mm. The precipitation of the coldest quarter is 14.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo atrocaerulea", + "(B) Macronyx aurantiigula", + "(C) Struthio molybdophanes", + "(D) Bostrychia olivacea", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22298211_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0625", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606123 and latitude -2.982345 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Scleroptila shelleyi", + "(B) Acrocephalus gracilirostris", + "(C) Corvus capensis", + "(D) Pternistis hildebrandti", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12053795_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0626", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.695232 and latitude -3.994353 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Otus scops", + "(B) Dendrocygna viduata", + "(C) Lamprotornis fischeri", + "(D) Ploceus subaureus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12525001_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0627", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120086 and latitude -0.361313 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Accipiter badius", + "(B) Apalis jacksoni", + "(C) Numida meleagris", + "(D) Merops bullockoides", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4929449_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0628", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.308900 and latitude 0.582214 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prionops plumatus", + "(B) Streptopelia capicola", + "(C) Charadrius dubius", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6311615_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0629", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.531521 and latitude -0.551474 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychoprion anaethetus", + "(B) Alopochen aegyptiaca", + "(C) Rhinopomastus minor", + "(D) Gypaetus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11329676_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0630", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444340 and latitude -0.722888 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Stactolaema olivacea", + "(B) Sarkidiornis melanotos", + "(C) Lamprotornis purpureus", + "(D) Ploceus jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11433400_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0631", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425569 and latitude -0.721061 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bubo cinerascens", + "(B) Upupa epops", + "(C) Platysteira concreta", + "(D) Cuculus solitarius", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19024969_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0632", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.118175 and latitude -0.414585 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sarkidiornis melanotos", + "(B) Anthreptes longuemarei", + "(C) Lanius collurio", + "(D) Merops superciliosus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025784_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0633", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262168 and latitude -0.444845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius ruficeps", + "(B) Muscicapa striata", + "(C) Euplectes progne", + "(D) Phoenicopterus roseus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5135004_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0634", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.247386 and latitude -0.410272 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rostratula benghalensis", + "(B) Crithagra dorsostriata", + "(C) Pelecanus onocrotalus", + "(D) Circaetus beaudouini", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8829559_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0635", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.713939 and latitude -3.993058 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Pogonocichla stellata", + "(C) Turtur chalcospilos", + "(D) Phoenicopterus roseus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11354641_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0636", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.241899 and latitude -0.404983 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Creatophora cinerea", + "(C) Platysteira concreta", + "(D) Chalcomitra amethystina", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10006012_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0637", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.848792 and latitude -1.405414 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.05 degrees. The mean diurnal range is 10.94 degrees. The isothermality is 72.39. The temperature seasonality (100 times the standard deviation) is 124.71. The max temperature of the warmest month is 29.91 degrees. The min temperature of the coldest month is 14.80 degrees. The temperature annual range is 15.11 degrees. The mean temperature of the wettest quarter is 22.51 degrees. The mean temperature of the driest quarter is 20.24 degrees. The mean temperature of the warmest quarter is 23.37 degrees. The mean temperature of the coldest quarter is 20.24 degrees. The annual precipitation is 782.0 mm. The precipitation of the wettest month is 239.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 111.95. The precipitation of the wettest quarter is 424.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 275.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Cisticola tinniens", + "(C) Buccanodon duchaillui", + "(D) Zosterops poliogastrus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120035_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0638", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486263 and latitude -0.610771 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Treron calvus", + "(B) Centropus monachus", + "(C) Polyboroides typus", + "(D) Bostrychia hagedash", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347943_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0639", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946107 and latitude -0.246093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola haematocephalus", + "(B) Merops oreobates", + "(C) Muscicapa striata", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462528_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0640", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.365745 and latitude -0.856539 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chrysococcyx klaas", + "(B) Hylia prasina", + "(C) Bucorvus abyssinicus", + "(D) Telophorus sulfureopectus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925745_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0641", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.605857 and latitude -2.979885 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rhodophoneus cruentus", + "(B) Pternistis hildebrandti", + "(C) Caprimulgus clarus", + "(D) Anas platyrhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12079977_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0642", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.131107 and latitude -0.310540 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Elminia longicauda", + "(B) Calendulauda poecilosterna", + "(C) Alopochen aegyptiaca", + "(D) Riparia riparia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22962104_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0643", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731551 and latitude -3.997904 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Centropus grillii", + "(B) Limosa lapponica", + "(C) Hedydipna platura", + "(D) Pluvialis squatarola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1120356_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0644", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116701 and latitude -0.410734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Scopus umbretta", + "(B) Alopochen aegyptiaca", + "(C) Amandava subflava", + "(D) Scleroptila elgonensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17114258_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0645", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492965 and latitude -0.574878 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spiloptila clamans", + "(B) Lamprotornis chalybaeus", + "(C) Spatula hottentota", + "(D) Zapornia flavirostra", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952035_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0646", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.082220 and latitude -0.308115 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Gymnoris pyrgita", + "(B) Alopochen aegyptiaca", + "(C) Eremomela turneri", + "(D) Eurillas gracilis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16475457_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0647", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444473 and latitude -0.715818 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spatula hottentota", + "(B) Andropadus importunus", + "(C) Monticola saxatilis", + "(D) Coturnix delegorguei", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21447351_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0648", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.771205 and latitude -3.943753 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tockus erythrorhynchus", + "(B) Lagonosticta larvata", + "(C) Arenaria interpres", + "(D) Corvus splendens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3884618_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0649", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362967 and latitude -0.859180 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus cabanisi", + "(B) Lamprotornis albicapillus", + "(C) Tricholaema melanocephala", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17135891_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0650", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.378136 and latitude -0.823002 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardeola idae", + "(B) Cyanomitra veroxii", + "(C) Motacilla alba", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19744907_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0651", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537733 and latitude -0.547081 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius humeralis", + "(B) Estrilda astrild", + "(C) Falco rupicoloides", + "(D) Platysteira concreta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11361405_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0652", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.103821 and latitude -0.308474 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Leptoptilos crumenifer", + "(C) Corvus capensis", + "(D) Pseudonigrita cabanisi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864256_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0653", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.603577 and latitude -2.963005 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Lophoceros hemprichii", + "(C) Chalcomitra senegalensis", + "(D) Ptyonoprogne fuligula", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12031498_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0654", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.626243 and latitude -0.492575 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Estrilda astrild", + "(C) Aplopelia larvata", + "(D) Ploceus vitellinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16582946_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0655", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.578382 and latitude -0.608027 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oenanthe scotocerca", + "(B) Cecropis abyssinica", + "(C) Alopochen aegyptiaca", + "(D) Apalis jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12921572_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0656", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.398392 and latitude -0.765587 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris falcinellus", + "(B) Melaniparus albiventris", + "(C) Spatula querquedula", + "(D) Haliaeetus vocifer", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L961800_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0657", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411198 and latitude -0.777333 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius sublacteus", + "(B) Alopochen aegyptiaca", + "(C) Myrmecocichla nigra", + "(D) Turtur chalcospilos", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16416313_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0658", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474390 and latitude -0.561497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acrocephalus palustris", + "(B) Speculipastor bicolor", + "(C) Anas undulata", + "(D) Agapornis pullarius", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16228704_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0659", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450697 and latitude -0.741258 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Oriolus larvatus", + "(B) Oena capensis", + "(C) Pinarochroa sordida", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20944652_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0660", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.099234 and latitude -0.303565 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Cisticola hunteri", + "(C) Calidris temminckii", + "(D) Tchagra senegalus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4994948_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0661", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337650 and latitude -2.249473 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tockus erythrorhynchus", + "(B) Lanius dorsalis", + "(C) Gypaetus barbatus", + "(D) Phyllastrephus debilis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22572263_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0662", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.386633 and latitude -0.805065 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Camaroptera brachyura", + "(B) Alopochen aegyptiaca", + "(C) Bathmocercus rufus", + "(D) Estrilda nonnula", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076206_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0663", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321579 and latitude -0.667457 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pycnonotus barbatus", + "(B) Phylloscopus collybita", + "(C) Linurgus olivaceus", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6102152_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0664", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.383973 and latitude -0.817318 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Amandava subflava", + "(C) Indicator exilis", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15039930_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0665", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.304110 and latitude 0.573945 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthreptes longuemarei", + "(B) Streptopelia lugens", + "(C) Tauraco hartlaubi", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21379647_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0666", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.636223 and latitude -0.502958 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis jacksoni", + "(B) Oenanthe pleschanka", + "(C) Estrilda rhodopyga", + "(D) Saxicola torquatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10716936_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0667", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.067732 and latitude -0.268997 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris minuta", + "(B) Lamprotornis superbus", + "(C) Cisticola marginatus", + "(D) Apus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930250_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0668", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.338767 and latitude 0.158103 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.22 degrees. The mean diurnal range is 11.34 degrees. The isothermality is 81.65. The temperature seasonality (100 times the standard deviation) is 72.62. The max temperature of the warmest month is 22.82 degrees. The min temperature of the coldest month is 8.93 degrees. The temperature annual range is 13.88 degrees. The mean temperature of the wettest quarter is 14.26 degrees. The mean temperature of the driest quarter is 15.69 degrees. The mean temperature of the warmest quarter is 16.10 degrees. The mean temperature of the coldest quarter is 14.26 degrees. The annual precipitation is 1326.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 47.26. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 307.0 mm. The precipitation of the coldest quarter is 486.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola marginatus", + "(B) Streptopelia semitorquata", + "(C) Pogoniulus leucomystax", + "(D) Falco cherrug", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8137654_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0669", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.110792 and latitude -0.561781 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus melanogaster", + "(B) Ploceus cucullatus", + "(C) Turtur chalcospilos", + "(D) Laniarius mufumbiri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10902833_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0670", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490550 and latitude -0.589737 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius humeralis", + "(B) Hirundo smithii", + "(C) Alopochen aegyptiaca", + "(D) Phylloscopus collybita", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9954043_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0671", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.351700 and latitude -0.771080 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera mombassica", + "(B) Haliaeetus vocifer", + "(C) Ptilopsis granti", + "(D) Anthus leucophrys", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1195069_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0672", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.380350 and latitude -0.804890 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phalaropus lobatus", + "(B) Colius leucocephalus", + "(C) Alopochen aegyptiaca", + "(D) Amaurornis marginalis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076105_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0673", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424234 and latitude -0.763541 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Cinnyris chalcomelas", + "(C) Phyllastrephus cabanisi", + "(D) Delichon urbicum", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14509122_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0674", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063427 and latitude -0.325958 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Balearica pavonina", + "(B) Butastur rufipennis", + "(C) Lybius melanopterus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6680855_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0675", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.590838 and latitude -2.919183 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ortygornis sephaena", + "(B) Oriolus chlorocephalus", + "(C) Guttera verreauxi", + "(D) Kaupifalco monogrammicus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060081_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0676", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391460 and latitude -0.810386 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Accipiter rufiventris", + "(B) Alopochen aegyptiaca", + "(C) Clamator levaillantii", + "(D) Eurillas curvirostris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13019591_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0677", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.587077 and latitude -0.576565 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Merops persicus", + "(C) Cinnyris tsavoensis", + "(D) Melierax poliopterus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14813987_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0678", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.590325 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Podica senegalensis", + "(B) Zosterops senegalensis", + "(C) Tachybaptus ruficollis", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11353714_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0679", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.018205 and latitude -1.424610 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Egretta gularis", + "(B) Mirafra rufocinnamomea", + "(C) Streptopelia semitorquata", + "(D) Poicephalus cryptoxanthus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16869306_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0680", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.010834 and latitude -0.237932 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Poeoptera stuhlmanni", + "(B) Treron waalia", + "(C) Falco rupicoloides", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17953479_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0681", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431565 and latitude -0.759218 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ardea goliath", + "(B) Hypargos niveoguttatus", + "(C) Streptopelia lugens", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9905627_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0682", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.955154 and latitude 0.455048 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.43 degrees. The mean diurnal range is 14.77 degrees. The isothermality is 82.21. The temperature seasonality (100 times the standard deviation) is 64.30. The max temperature of the warmest month is 27.63 degrees. The min temperature of the coldest month is 9.67 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 19.26 degrees. The mean temperature of the driest quarter is 18.32 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.75 degrees. The annual precipitation is 812.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 65.48. The precipitation of the wettest quarter is 345.0 mm. The precipitation of the driest quarter is 90.0 mm. The precipitation of the warmest quarter is 345.0 mm. The precipitation of the coldest quarter is 146.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius funebris", + "(B) Cursorius somalensis", + "(C) Tchagra jamesi", + "(D) Passer domesticus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5276557_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0683", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.708925 and latitude -3.531405 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia capicola", + "(B) Mirafra rufocinnamomea", + "(C) Crex egregia", + "(D) Actitis hypoleucos", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12801772_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0684", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610410 and latitude -2.982675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Cyanomitra cyanolaema", + "(C) Bycanistes brevis", + "(D) Cinnyris tsavoensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12021597_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0685", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.730080 and latitude -0.482860 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buteo augur", + "(B) Pternistis jacksoni", + "(C) Anthus similis", + "(D) Malaconotus blanchoti", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3830979_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0686", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.543245 and latitude -0.548779 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Estrilda kandti", + "(B) Plocepasser donaldsoni", + "(C) Scopus umbretta", + "(D) Caprimulgus vexillarius", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11538126_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0687", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.724135 and latitude -4.024563 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Acrocephalus gracilirostris", + "(B) Centropus grillii", + "(C) Apus affinis", + "(D) Elminia albonotata", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8930976_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0688", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.485187 and latitude -0.652962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Sarothrura boehmi", + "(C) Psittacus erithacus", + "(D) Ploceus vitellinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734170_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0689", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425533 and latitude -0.632287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola aberdare", + "(B) Agapornis fischeri", + "(C) Alopochen aegyptiaca", + "(D) Spatula hottentota", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10989694_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0690", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493109 and latitude -0.570587 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus cabanisi", + "(B) Lophaetus occipitalis", + "(C) Cisticola hunteri", + "(D) Lamprotornis superbus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11117640_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0691", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.803000 and latitude -3.870000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis chariessa", + "(B) Pogoniulus pusillus", + "(C) Eurocephalus ruppelli", + "(D) Corvus splendens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7738672_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0692", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450859 and latitude -0.731743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo smithii", + "(B) Streptopelia capicola", + "(C) Bradornis microrhynchus", + "(D) Corythaeola cristata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17069045_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0693", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308674 and latitude -0.887838 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis hildebrandti", + "(B) Actophilornis africanus", + "(C) Fraseria lendu", + "(D) Lamprotornis regius", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020812_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0694", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337927 and latitude -2.245161 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chlidonias leucopterus", + "(B) Falco tinnunculus", + "(C) Pternistis leucoscepus", + "(D) Cossypha heuglini", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18777803_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0695", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334420 and latitude -0.828872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus rochii", + "(B) Cisticola cinereolus", + "(C) Anas undulata", + "(D) Pytilia afra", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8838554_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0696", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.634782 and latitude -0.301388 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Thalassornis leuconotus", + "(B) Ploceus subaureus", + "(C) Pytilia melba", + "(D) Pseudonigrita cabanisi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20352740_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0697", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.094788 and latitude -0.325321 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Agapornis canus", + "(B) Dendrocygna viduata", + "(C) Circaetus beaudouini", + "(D) Xenus cinereus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22896641_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0698", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321090 and latitude -0.668276 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Recurvirostra avosetta", + "(B) Ceuthmochares australis", + "(C) Colius striatus", + "(D) Ardea goliath", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298525_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0699", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.073791 and latitude -0.334946 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Clanga pomarina", + "(C) Coracias caudatus", + "(D) Pogoniulus simplex", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17278719_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0700", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431027 and latitude -0.717178 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco naumanni", + "(B) Alopochen aegyptiaca", + "(C) Cisticola ruficeps", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15684869_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0701", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564085 and latitude -0.562197 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Vanellus superciliosus", + "(C) Corvus capensis", + "(D) Falco cuvierii", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11134929_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0702", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490027 and latitude -0.587858 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Halcyon senegaloides", + "(B) Lissotis melanogaster", + "(C) Fulica cristata", + "(D) Saxicola torquatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294580_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0703", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.871250 and latitude -1.671304 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cinnyris erythrocercus", + "(B) Eupodotis gindiana", + "(C) Streptopelia capicola", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22138528_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0704", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.647223 and latitude -0.293334 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus lineiventris", + "(B) Balearica regulorum", + "(C) Bostrychia hagedash", + "(D) Merops pusillus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1437096_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0705", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260674 and latitude -0.442675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tricholaema diademata", + "(B) Alopochen aegyptiaca", + "(C) Ortygornis sephaena", + "(D) Chloropicus goertae", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10658952_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0706", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.865608 and latitude -1.695195 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ephippiorhynchus senegalensis", + "(B) Struthio camelus", + "(C) Oenanthe pileata", + "(D) Tringa nebularia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8196928_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0707", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.551894 and latitude -0.544869 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius asiaticus", + "(B) Ploceus taeniopterus", + "(C) Alopochen aegyptiaca", + "(D) Agapornis personatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14509947_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0708", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.336411 and latitude -0.826705 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anastomus lamelligerus", + "(B) Haliaeetus vocifer", + "(C) Batis orientalis", + "(D) Accipiter minullus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2366739_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0709", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.996090 and latitude 0.225545 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.27 degrees. The mean diurnal range is 11.79 degrees. The isothermality is 82.01. The temperature seasonality (100 times the standard deviation) is 77.54. The max temperature of the warmest month is 26.77 degrees. The min temperature of the coldest month is 12.40 degrees. The temperature annual range is 14.37 degrees. The mean temperature of the wettest quarter is 19.08 degrees. The mean temperature of the driest quarter is 19.91 degrees. The mean temperature of the warmest quarter is 20.18 degrees. The mean temperature of the coldest quarter is 18.29 degrees. The annual precipitation is 1839.0 mm. The precipitation of the wettest month is 253.0 mm. The precipitation of the driest month is 68.0 mm. The precipitation seasonality (coefficient of variation) is 38.12. The precipitation of the wettest quarter is 652.0 mm. The precipitation of the driest quarter is 243.0 mm. The precipitation of the warmest quarter is 306.0 mm. The precipitation of the coldest quarter is 531.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus rochii", + "(B) Euplectes macroura", + "(C) Turtur tympanistria", + "(D) Corvus splendens", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6355606_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0710", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433431 and latitude -0.723262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phaethon lepturus", + "(B) Alopochen aegyptiaca", + "(C) Cisticola marginatus", + "(D) Cisticola eximius", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17801432_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0711", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560245 and latitude -0.553263 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus dichrocephalus", + "(B) Charadrius hiaticula", + "(C) Tachybaptus ruficollis", + "(D) Apalis thoracica", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11379808_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0712", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554973 and latitude -0.549678 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tachybaptus ruficollis", + "(B) Ficedula semitorquata", + "(C) Cisticola juncidis", + "(D) Sarothrura pulchra", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11363822_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0713", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.316827 and latitude -0.700020 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Quelea cardinalis", + "(C) Mycteria ibis", + "(D) Tringa nebularia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17115991_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0714", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.752254 and latitude -3.568972 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Quelea cardinalis", + "(C) Cisticola natalensis", + "(D) Passer rufocinctus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10807956_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0715", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.301133 and latitude -0.711030 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Halcyon senegalensis", + "(B) Alopochen aegyptiaca", + "(C) Estrilda astrild", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11401294_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0716", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425081 and latitude -0.721190 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tauraco hartlaubi", + "(B) Alopochen aegyptiaca", + "(C) Zosterops stuhlmanni", + "(D) Bradypterus baboecala", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21316833_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0717", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.691930 and latitude -3.990577 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dicrurus adsimilis", + "(B) Oreolais pulcher", + "(C) Aythya fuligula", + "(D) Rostratula benghalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3267612_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0718", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.078463 and latitude -0.573668 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola lais", + "(B) Streptopelia semitorquata", + "(C) Phoeniculus purpureus", + "(D) Dicrurus modestus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3989563_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0719", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.413888 and latitude -0.792999 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tringa nebularia", + "(B) Campethera cailliautii", + "(C) Crithagra canicapilla", + "(D) Threskiornis aethiopicus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18371916_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0720", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229546 and latitude -0.405126 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eremomela icteropygialis", + "(B) Circus macrourus", + "(C) Chalcomitra rubescens", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151970_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0721", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491962 and latitude -0.573307 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus insignis", + "(B) Zosterops senegalensis", + "(C) Eremopterix leucotis", + "(D) Coturnix coturnix", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13374816_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0722", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.611015 and latitude -2.982577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Euplectes orix", + "(C) Apalis jacksoni", + "(D) Ploceus ocularis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12023045_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0723", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267712 and latitude -0.814428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Muscicapa adusta", + "(B) Sylvia abyssinica", + "(C) Thalassornis leuconotus", + "(D) Lanius cabanisi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6714321_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0724", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491238 and latitude -0.636892 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Quelea quelea", + "(B) Vanellus superciliosus", + "(C) Dryoscopus cubla", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6492845_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0725", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.635875 and latitude -0.502425 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Melaenornis semipartitus", + "(B) Sheppardia gunningi", + "(C) Nectarinia kilimensis", + "(D) Pternistis jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16228684_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0726", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570261 and latitude -0.606583 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Paragallinula angulata", + "(B) Cisticola aberrans", + "(C) Oxyura maccoa", + "(D) Streptopelia lugens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10075852_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0727", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.327839 and latitude -0.744303 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ficedula semitorquata", + "(B) Laniarius mufumbiri", + "(C) Buteo oreophilus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1219423_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0728", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308656 and latitude -0.816523 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Malimbus rubricollis", + "(B) Muscicapa aquatica", + "(C) Apus niansae", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1917524_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0729", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.325463 and latitude -0.891143 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.34 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 81.52. The temperature seasonality (100 times the standard deviation) is 63.49. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 15.11 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.63 degrees. The mean temperature of the driest quarter is 21.47 degrees. The mean temperature of the warmest quarter is 23.09 degrees. The mean temperature of the coldest quarter is 21.47 degrees. The annual precipitation is 1140.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 53.60. The precipitation of the wettest quarter is 480.0 mm. The precipitation of the driest quarter is 138.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 138.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zapornia pusilla", + "(B) Hydroprogne caspia", + "(C) Colius striatus", + "(D) Cercotrichas leucophrys", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9097664_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0730", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.277757 and latitude -0.813519 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus solitarius", + "(B) Alopochen aegyptiaca", + "(C) Cecropis daurica", + "(D) Euplectes hartlaubi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1027936_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0731", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326310 and latitude -0.717697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Arizelocichla nigriceps", + "(B) Turdus tephronotus", + "(C) Platalea alba", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11413533_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0732", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.845929 and latitude 1.034954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Ploceus bojeri", + "(C) Crithagra canicapilla", + "(D) Polihierax semitorquatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279837_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0733", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.221202 and latitude 0.174242 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.00 degrees. The mean diurnal range is 11.80 degrees. The isothermality is 83.86. The temperature seasonality (100 times the standard deviation) is 62.05. The max temperature of the warmest month is 29.41 degrees. The min temperature of the coldest month is 15.34 degrees. The temperature annual range is 14.07 degrees. The mean temperature of the wettest quarter is 22.37 degrees. The mean temperature of the driest quarter is 22.51 degrees. The mean temperature of the warmest quarter is 22.77 degrees. The mean temperature of the coldest quarter is 21.19 degrees. The annual precipitation is 1701.0 mm. The precipitation of the wettest month is 262.0 mm. The precipitation of the driest month is 53.0 mm. The precipitation seasonality (coefficient of variation) is 41.56. The precipitation of the wettest quarter is 648.0 mm. The precipitation of the driest quarter is 247.0 mm. The precipitation of the warmest quarter is 293.0 mm. The precipitation of the coldest quarter is 357.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius luehderi", + "(B) Streptopelia semitorquata", + "(C) Pterocles lichtensteinii", + "(D) Schoutedenapus myoptilus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15479302_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0734", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.863928 and latitude -1.668777 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera nivosa", + "(B) Columba guinea", + "(C) Ardeola idae", + "(D) Monticola saxatilis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19048757_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0735", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.190270 and latitude -0.808495 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spermophaga ruficapilla", + "(B) Campocolinus coqui", + "(C) Streptopelia reichenowi", + "(D) Columba livia", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21155557_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0736", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426978 and latitude -0.765083 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Limosa limosa", + "(B) Melaenornis fischeri", + "(C) Apalis jacksoni", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20803961_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0737", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.455446 and latitude -0.735221 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Limosa limosa", + "(B) Tricholaema diademata", + "(C) Ploceus ocularis", + "(D) Myrmecocichla aethiops", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16279479_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0738", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.300201 and latitude -0.821200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Passer eminibey", + "(C) Mirafra javanica", + "(D) Plectropterus gambensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1027894_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0739", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240434 and latitude -0.404942 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campocolinus coqui", + "(B) Cypsiurus parvus", + "(C) Thalasseus sandvicensis", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9997050_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0740", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.349719 and latitude -0.816269 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Polyboroides typus", + "(B) Alopochen aegyptiaca", + "(C) Spermestes cucullata", + "(D) Trochocercus cyanomelas", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19129445_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0741", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612130 and latitude -2.985147 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis cinerea", + "(B) Elanus caeruleus", + "(C) Estrilda rhodopyga", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12125053_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0742", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451718 and latitude -0.739879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Clanga pomarina", + "(B) Corvus albus", + "(C) Vidua paradisaea", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614369_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0743", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120250 and latitude -0.376524 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Creatophora cinerea", + "(B) Lanius phoenicuroides", + "(C) Alopochen aegyptiaca", + "(D) Glaucidium capense", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17860014_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0744", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.245980 and latitude -0.410204 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus solitarius", + "(B) Numida meleagris", + "(C) Cisticola ruficeps", + "(D) Cinnyris cupreus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151885_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0745", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.348996 and latitude -0.826693 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Euplectes hordeaceus", + "(C) Cypsiurus parvus", + "(D) Oriolus percivali", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4985917_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0746", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.135895 and latitude -0.613163 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pycnonotus barbatus", + "(B) Oenanthe lugens", + "(C) Schistolais leucopogon", + "(D) Motacilla flava", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2101438_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0747", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.375432 and latitude -0.662052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis castaneicollis", + "(B) Apus barbatus", + "(C) Threskiornis aethiopicus", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298532_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0748", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610720 and latitude -2.980845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Eremopterix leucopareia", + "(B) Zosterops stuhlmanni", + "(C) Columba guinea", + "(D) Thalassornis leuconotus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12069484_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0749", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240989 and latitude -0.404745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nectarinia kilimensis", + "(B) Emberiza striolata", + "(C) Pelecanus onocrotalus", + "(D) Eupodotis gindiana", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9805701_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0750", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111939 and latitude -0.512160 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Torgos tracheliotos", + "(B) Columba guinea", + "(C) Cyanomitra cyanolaema", + "(D) Granatina ianthinogaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10091419_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0751", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.064505 and latitude -0.294279 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Colius striatus", + "(B) Agapornis pullarius", + "(C) Cercococcyx montanus", + "(D) Rhinoptilus chalcopterus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18498216_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0752", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.803397 and latitude -3.847356 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mirafra rufocinnamomea", + "(B) Centropus superciliosus", + "(C) Vidua hypocherina", + "(D) Ploceus spekei", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16591200_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0753", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267000 and latitude -0.391000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Buteo rufinus", + "(C) Ceuthmochares australis", + "(D) Sylvia atricapilla", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9656777_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0754", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063727 and latitude 0.728790 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus trivialis", + "(B) Columba guinea", + "(C) Nilaus afer", + "(D) Galerida cristata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13539972_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0755", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.710000 and latitude -4.049833 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Thalasseus bengalensis", + "(B) Tricholaema melanocephala", + "(C) Corvus splendens", + "(D) Synoicus adansonii", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2484720_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0756", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.864672 and latitude -1.666409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lymnocryptes minimus", + "(B) Lophoceros nasutus", + "(C) Lamprotornis superbus", + "(D) Sula dactylatra", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6150442_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0757", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328739 and latitude -0.809682 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pseudhirundo griseopyga", + "(B) Cuculus clamosus", + "(C) Chroicocephalus cirrocephalus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974532_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0758", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.913344 and latitude 0.063140 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.97 degrees. The mean diurnal range is 11.67 degrees. The isothermality is 81.23. The temperature seasonality (100 times the standard deviation) is 72.48. The max temperature of the warmest month is 26.50 degrees. The min temperature of the coldest month is 12.14 degrees. The temperature annual range is 14.36 degrees. The mean temperature of the wettest quarter is 19.37 degrees. The mean temperature of the driest quarter is 19.54 degrees. The mean temperature of the warmest quarter is 19.80 degrees. The mean temperature of the coldest quarter is 18.05 degrees. The annual precipitation is 1927.0 mm. The precipitation of the wettest month is 277.0 mm. The precipitation of the driest month is 77.0 mm. The precipitation seasonality (coefficient of variation) is 36.56. The precipitation of the wettest quarter is 686.0 mm. The precipitation of the driest quarter is 279.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 505.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus albus", + "(B) Laniarius major", + "(C) Coracina pectoralis", + "(D) Trachyphonus darnaudii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9160408_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0759", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.965087 and latitude -0.002546 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Leptoptilos crumenifer", + "(B) Ardea purpurea", + "(C) Ceuthmochares australis", + "(D) Chroicocephalus cirrocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8291945_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0760", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418281 and latitude -0.769957 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera caroli", + "(B) Hirundo angolensis", + "(C) Alopochen aegyptiaca", + "(D) Corvus capensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17031906_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0761", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.225915 and latitude -0.375062 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Milvus migrans", + "(B) Iduna natalensis", + "(C) Streptopelia lugens", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3638713_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0762", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.243000 and latitude -0.436900 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Caprimulgus stellatus", + "(C) Spizocorys personata", + "(D) Falco cherrug", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10598574_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0763", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.440641 and latitude -0.723812 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Sarothrura rufa", + "(C) Saxicola rubetra", + "(D) Cyanomitra cyanolaema", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18581685_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0764", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.224466 and latitude -0.451912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Ortyxelos meiffrenii", + "(C) Camaroptera chloronota", + "(D) Charadrius pallidus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16985203_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0765", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.284696 and latitude 0.521274 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes axillaris", + "(B) Ploceus melanocephalus", + "(C) Ploceus nigerrimus", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290833_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0766", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.283195 and latitude -0.716460 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Amaurornis marginalis", + "(B) Bathmocercus rufus", + "(C) Alopochen aegyptiaca", + "(D) Laniarius ruficeps", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14798664_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0767", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952315 and latitude 0.009622 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prionops retzii", + "(B) Anas erythrorhyncha", + "(C) Falco peregrinus", + "(D) Numida meleagris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925698_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0768", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493755 and latitude -0.589523 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cryptospiza salvadorii", + "(B) Dryoscopus pringlii", + "(C) Alopochen aegyptiaca", + "(D) Cisticola lais", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10072386_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0769", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610542 and latitude -2.982743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis hildebrandti", + "(B) Bubalornis albirostris", + "(C) Tmetothylacus tenellus", + "(D) Pogonocichla stellata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12045024_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0770", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437874 and latitude -0.712376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phoeniconaias minor", + "(B) Circaetus pectoralis", + "(C) Cisticola robustus", + "(D) Corvus albus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279452_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0771", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420519 and latitude -0.775280 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta senegala", + "(B) Alopochen aegyptiaca", + "(C) Euplectes hordeaceus", + "(D) Chalcomitra senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284261_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0772", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435263 and latitude -0.717722 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes albonotatus", + "(B) Anas sparsa", + "(C) Prinia somalica", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11682534_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0773", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.378083 and latitude -0.822826 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cuculus gularis", + "(B) Ceryle rudis", + "(C) Mirafra rufocinnamomea", + "(D) Eminia lepida", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8051680_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0774", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.752829 and latitude -3.571346 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta rhodopareia", + "(B) Pycnonotus barbatus", + "(C) Apus caffer", + "(D) Cuculus clamosus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14087004_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0775", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.090179 and latitude -0.613906 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Mirafra cheniana", + "(B) Vanellus armatus", + "(C) Terpsiphone viridis", + "(D) Cisticola woosnami", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3990989_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0776", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125236 and latitude -0.361688 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Struthio camelus", + "(B) Halcyon albiventris", + "(C) Cossypha heuglini", + "(D) Clamator jacobinus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5255397_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0777", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229570 and latitude -0.461040 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Terathopius ecaudatus", + "(B) Pycnonotus barbatus", + "(C) Nectarinia tacazze", + "(D) Anas capensis", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21692520_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0778", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570869 and latitude -0.572879 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Erythrocercus holochlorus", + "(B) Macronyx sharpei", + "(C) Tringa ochropus", + "(D) Chalcomitra hunteri", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294587_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0779", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442682 and latitude -0.721603 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Emberiza flaviventris", + "(C) Anastomus lamelligerus", + "(D) Xenus cinereus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10176494_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0780", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.303336 and latitude -0.676259 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pholia sharpii", + "(B) Turdoides sharpei", + "(C) Halcyon senegaloides", + "(D) Pycnonotus barbatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11202841_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0781", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117479 and latitude -0.478450 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ploceus ocularis", + "(B) Colius striatus", + "(C) Eremomela flavicrissalis", + "(D) Geokichla guttata", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6301196_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0782", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.106152 and latitude -0.401560 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pterocles exustus", + "(B) Lissotis hartlaubii", + "(C) Alopochen aegyptiaca", + "(D) Zapornia pusilla", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16457239_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0783", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.068058 and latitude -0.390541 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus similis", + "(B) Alopochen aegyptiaca", + "(C) Bleda syndactylus", + "(D) Tauraco hartlaubi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6687369_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0784", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554947 and latitude -0.549995 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Limosa lapponica", + "(C) Ptilostomus afer", + "(D) Thalasseus bengalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12264886_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0785", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425371 and latitude -0.720112 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Euplectes jacksoni", + "(C) Macronyx aurantiigula", + "(D) Caprimulgus fraenatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930747_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0786", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.060538 and latitude -1.357928 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.64 degrees. The mean diurnal range is 12.06 degrees. The isothermality is 72.91. The temperature seasonality (100 times the standard deviation) is 127.40. The max temperature of the warmest month is 28.49 degrees. The min temperature of the coldest month is 11.95 degrees. The temperature annual range is 16.54 degrees. The mean temperature of the wettest quarter is 20.60 degrees. The mean temperature of the driest quarter is 18.10 degrees. The mean temperature of the warmest quarter is 21.05 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 636.0 mm. The precipitation of the wettest month is 139.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 85.66. The precipitation of the wettest quarter is 289.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 23.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sylvia abyssinica", + "(B) Apalis chariessa", + "(C) Anas capensis", + "(D) Lamprotornis superbus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16196959_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0787", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.729631 and latitude -3.947831 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Centropus superciliosus", + "(B) Stactolaema leucotis", + "(C) Corvus splendens", + "(D) Pachyphantes superciliosus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3857011_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0788", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419010 and latitude -0.762516 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Prodotiscus regulus", + "(C) Uraeginthus bengalus", + "(D) Bucorvus abyssinicus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8092248_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0789", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.422257 and latitude -0.797786 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Buphagus africanus", + "(B) Apalis thoracica", + "(C) Centropus superciliosus", + "(D) Batis erlangeri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15541395_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0790", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.118768 and latitude -0.408528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Cinnyris chloropygius", + "(C) Circus aeruginosus", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214600_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0791", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328096 and latitude -0.745032 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tringa nebularia", + "(B) Alopochen aegyptiaca", + "(C) Onychognathus morio", + "(D) Myrmecocichla aethiops", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21760547_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0792", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.324620 and latitude -0.517466 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius somalicus", + "(B) Apus niansae", + "(C) Anastomus lamelligerus", + "(D) Cisticola carruthersi", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1874608_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0793", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.247270 and latitude -0.411410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Passer eminibey", + "(B) Anthus cinnamomeus", + "(C) Batis orientalis", + "(D) Uraeginthus bengalus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6201096_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0794", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.291683 and latitude -0.713102 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prionops poliolophus", + "(B) Alopochen aegyptiaca", + "(C) Cossypha niveicapilla", + "(D) Luscinia megarhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14962292_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0795", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.239173 and latitude -0.403064 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lophoceros alboterminatus", + "(B) Crex crex", + "(C) Geokichla gurneyi", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10076522_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0796", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.223909 and latitude -0.457088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Turdoides sharpei", + "(B) Apus niansae", + "(C) Alopochen aegyptiaca", + "(D) Egretta gularis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237255_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0797", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.016729 and latitude -1.424873 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Egretta garzetta", + "(B) Apalis jacksoni", + "(C) Turtur chalcospilos", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15691623_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0798", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.151949 and latitude -0.421988 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Melierax metabates", + "(B) Merops nubicus", + "(C) Hippolais icterina", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10031354_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0799", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.110418 and latitude -0.307472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spizocorys personata", + "(B) Ploceus taeniopterus", + "(C) Tringa erythropus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9863251_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0800", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.261497 and latitude -0.426087 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Podiceps cristatus", + "(C) Accipiter rufiventris", + "(D) Tringa erythropus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16054578_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0801", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.692246 and latitude -3.047183 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.87 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 68.99. The temperature seasonality (100 times the standard deviation) is 163.68. The max temperature of the warmest month is 31.18 degrees. The min temperature of the coldest month is 13.94 degrees. The temperature annual range is 17.23 degrees. The mean temperature of the wettest quarter is 22.60 degrees. The mean temperature of the driest quarter is 19.66 degrees. The mean temperature of the warmest quarter is 23.71 degrees. The mean temperature of the coldest quarter is 19.66 degrees. The annual precipitation is 781.0 mm. The precipitation of the wettest month is 196.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 89.27. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 32.0 mm. The precipitation of the warmest quarter is 204.0 mm. The precipitation of the coldest quarter is 32.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nigrita fusconotus", + "(B) Falco cherrug", + "(C) Ortygornis sephaena", + "(D) Psittacus erithacus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12038122_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0802", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.561378 and latitude -0.557328 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola aridulus", + "(B) Psalidoprocne albiceps", + "(C) Lanius senator", + "(D) Anas sparsa", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12677064_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0803", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.335490 and latitude -2.241674 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis leucoscepus", + "(B) Dinemellia dinemelli", + "(C) Halcyon senegalensis", + "(D) Lagonosticta rubricata", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13301310_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0804", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718151 and latitude -4.017357 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Tachybaptus ruficollis", + "(B) Ploceus cucullatus", + "(C) Cisticola brachypterus", + "(D) Coracias garrulus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070641_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0805", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.384507 and latitude -0.818119 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracias garrulus", + "(B) Turdoides jardineii", + "(C) Alopochen aegyptiaca", + "(D) Sterna hirundo", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756373_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0806", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.581487 and latitude -2.894942 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Circaetus beaudouini", + "(B) Strix woodfordii", + "(C) Turdoides hypoleuca", + "(D) Streptopelia decipiens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060089_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0807", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452243 and latitude -0.735218 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo smithii", + "(B) Dinemellia dinemelli", + "(C) Tricholaema diademata", + "(D) Laniarius major", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15770066_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0808", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.632589 and latitude -1.412630 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.42 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 72.41. The temperature seasonality (100 times the standard deviation) is 126.48. The max temperature of the warmest month is 29.39 degrees. The min temperature of the coldest month is 14.02 degrees. The temperature annual range is 15.37 degrees. The mean temperature of the wettest quarter is 21.91 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.57 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 204.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 105.97. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 270.0 mm. The precipitation of the coldest quarter is 10.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo angolensis", + "(B) Lagonosticta senegala", + "(C) Caprimulgus longipennis", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10056690_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0809", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612393 and latitude -2.983073 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Egretta ardesiaca", + "(C) Mirafra cheniana", + "(D) Indicator variegatus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12071643_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0810", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456322 and latitude -0.730952 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cursorius somalensis", + "(B) Streptopelia capicola", + "(C) Falco cuvierii", + "(D) Cisticola nana", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18098985_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0811", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262007 and latitude -0.782408 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anaplectes rubriceps", + "(B) Buteo buteo", + "(C) Mandingoa nitidula", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279523_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0812", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.579637 and latitude 0.338600 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Coracias caudatus", + "(C) Lamprotornis superbus", + "(D) Calidris pugnax", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638669_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0813", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.302593 and latitude -0.722962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracina pectoralis", + "(B) Alopochen aegyptiaca", + "(C) Euplectes macroura", + "(D) Pterocles lichtensteinii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964191_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0814", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718976 and latitude -4.014098 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Prodotiscus insignis", + "(B) Megaceryle maxima", + "(C) Alopochen aegyptiaca", + "(D) Caprimulgus poliocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14464425_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0815", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.716266 and latitude -0.454711 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hippolais icterina", + "(B) Pinarochroa sordida", + "(C) Ploceus ocularis", + "(D) Hieraaetus ayresii", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2688861_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0816", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469995 and latitude -0.552480 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Calidris alba", + "(B) Turdoides hypoleuca", + "(C) Eurillas curvirostris", + "(D) Streptopelia lugens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6428377_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0817", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.614320 and latitude -2.983500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chalcomitra senegalensis", + "(B) Argya rubiginosa", + "(C) Nectarinia kilimensis", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12018725_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0818", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.578122 and latitude -2.996700 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Iduna natalensis", + "(B) Pternistis hildebrandti", + "(C) Aquila rapax", + "(D) Bycanistes brevis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12116603_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0819", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.020203 and latitude -0.078163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Xenus cinereus", + "(B) Charadrius tricollaris", + "(C) Cisticola aridulus", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8219781_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0820", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240913 and latitude -0.404855 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pelecanus rufescens", + "(B) Spizocorys personata", + "(C) Cinnyris venustus", + "(D) Turdus abyssinicus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9996816_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0821", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087149 and latitude -0.265111 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Plegadis falcinellus", + "(B) Rhodophoneus cruentus", + "(C) Ploceus golandi", + "(D) Turdus pelios", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10051579_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0822", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.721884 and latitude -4.029045 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Egretta ardesiaca", + "(B) Ardeola idae", + "(C) Ichthyaetus hemprichii", + "(D) Tringa erythropus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10691981_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0823", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120769 and latitude -0.400954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Melaenornis pammelaina", + "(C) Cuculus clamosus", + "(D) Cisticola restrictus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14106163_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0824", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.430247 and latitude -0.719660 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Cisticola troglodytes", + "(C) Turdus abyssinicus", + "(D) Cinnyris reichenowi", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16104638_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0825", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426588 and latitude -0.759612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Illadopsis albipectus", + "(B) Thalassornis leuconotus", + "(C) Oenanthe pleschanka", + "(D) Tockus erythrorhynchus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10819022_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0826", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285334 and latitude 0.501972 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Streptopelia semitorquata", + "(B) Pogoniulus simplex", + "(C) Balearica regulorum", + "(D) Emberiza flaviventris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7695066_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0827", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420754 and latitude -0.776724 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Zapornia flavirostra", + "(C) Melaniparus thruppi", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4377528_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0828", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.460391 and latitude 1.492150 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.66 degrees. The mean diurnal range is 12.31 degrees. The isothermality is 82.42. The temperature seasonality (100 times the standard deviation) is 66.01. The max temperature of the warmest month is 26.50 degrees. The min temperature of the coldest month is 11.56 degrees. The temperature annual range is 14.94 degrees. The mean temperature of the wettest quarter is 17.89 degrees. The mean temperature of the driest quarter is 18.99 degrees. The mean temperature of the warmest quarter is 19.56 degrees. The mean temperature of the coldest quarter is 17.89 degrees. The annual precipitation is 945.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 53.44. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 223.0 mm. The precipitation of the coldest quarter is 358.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hirundo aethiopica", + "(B) Lamprotornis superbus", + "(C) Corvus rhipidurus", + "(D) Laniarius mufumbiri", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2338173_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0829", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988534 and latitude -0.219421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Microparra capensis", + "(B) Numida meleagris", + "(C) Thamnolaea cinnamomeiventris", + "(D) Lybius bidentatus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119968_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0830", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.601350 and latitude -2.950138 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apus barbatus", + "(B) Prodotiscus zambesiae", + "(C) Pternistis hildebrandti", + "(D) Psittacus erithacus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060066_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0831", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.640961 and latitude -2.974739 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Corvus capensis", + "(B) Merops muelleri", + "(C) Numida meleagris", + "(D) Cossypha natalensis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18597563_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0832", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453385 and latitude -0.728857 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Schoutedenapus myoptilus", + "(B) Trigonoceps occipitalis", + "(C) Lamprotornis superbus", + "(D) Batis molitor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13758223_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0833", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.363400 and latitude -0.470640 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Curruca boehmi", + "(B) Alopochen aegyptiaca", + "(C) Melaniparus funereus", + "(D) Euplectes macroura", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21005691_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0834", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120347 and latitude -0.373093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Turdoides plebejus", + "(C) Telophorus nigrifrons", + "(D) Tringa ochropus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794356_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0835", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.130841 and latitude -0.310531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pachyphantes superciliosus", + "(B) Oenanthe oenanthe", + "(C) Numida meleagris", + "(D) Treron calvus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18147093_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0836", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.786000 and latitude -3.908000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campethera tullbergi", + "(B) Gelochelidon nilotica", + "(C) Bubulcus ibis", + "(D) Pachycoccyx audeberti", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4561068_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0837", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.248771 and latitude -0.434102 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco rupicoloides", + "(B) Struthio camelus", + "(C) Actitis hypoleucos", + "(D) Elminia longicauda", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3846997_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0838", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.124408 and latitude -0.423229 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phyllastrephus hypochloris", + "(B) Sarkidiornis melanotos", + "(C) Cisticola ayresii", + "(D) Struthio camelus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21476921_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0839", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418809 and latitude -0.772926 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Amblyospiza albifrons", + "(C) Glareola nuchalis", + "(D) Riparia riparia", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20229590_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0840", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249894 and latitude -0.433598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus vaalensis", + "(B) Lamprotornis superbus", + "(C) Turtur tympanistria", + "(D) Cisticola marginatus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4235132_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0841", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.024926 and latitude -0.077162 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anas undulata", + "(B) Vanellus superciliosus", + "(C) Sternula saundersi", + "(D) Aquila rapax", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3074898_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0842", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.385322 and latitude -0.817636 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes afer", + "(B) Spermophaga ruficapilla", + "(C) Muscicapa striata", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21656097_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0843", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426106 and latitude -0.714779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lybius guifsobalito", + "(B) Spatula clypeata", + "(C) Ploceus vitellinus", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919751_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0844", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088105 and latitude -0.404465 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius collurio", + "(B) Laniarius mufumbiri", + "(C) Struthio camelus", + "(D) Bradypterus carpalis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7666090_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0845", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.242540 and latitude -0.405014 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Microcarbo africanus", + "(B) Illadopsis pyrrhoptera", + "(C) Alopochen aegyptiaca", + "(D) Oriolus chlorocephalus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1926871_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0846", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432161 and latitude -0.742143 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hieraaetus pennatus", + "(B) Alopochen aegyptiaca", + "(C) Cisticola chiniana", + "(D) Chlorocichla flaviventris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298492_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0847", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433018 and latitude -0.719505 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Charadrius mongolus", + "(C) Anas erythrorhyncha", + "(D) Riparia paludicola", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9581283_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0848", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432933 and latitude -0.745042 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Camaroptera brachyura", + "(C) Acrocephalus griseldis", + "(D) Luscinia megarhynchos", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5287529_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0849", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.616753 and latitude -2.969602 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Falco fasciinucha", + "(B) Oreolais pulcher", + "(C) Bradypterus lopezi", + "(D) Columba guinea", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12077587_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0850", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486642 and latitude -0.586780 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Charadrius dubius", + "(C) Circus pygargus", + "(D) Apus horus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9571885_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0851", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.536811 and latitude -0.548603 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Coracias naevius", + "(B) Burhinus capensis", + "(C) Pogonocichla stellata", + "(D) Ardea melanocephala", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11372449_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0852", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431218 and latitude -0.716916 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bradypterus baboecala", + "(B) Hypargos niveoguttatus", + "(C) Melaniparus guineensis", + "(D) Dendrocygna viduata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11763290_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0853", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088687 and latitude -0.312322 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Melierax poliopterus", + "(B) Glareola ocularis", + "(C) Struthio camelus", + "(D) Chloropicus poecilolaemus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4074487_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0854", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451435 and latitude -0.740282 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Crithagra reichenowi", + "(B) Streptopelia capicola", + "(C) Phylloscopus umbrovirens", + "(D) Spilopelia senegalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19693144_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0855", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391852 and latitude -0.810876 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis superbus", + "(B) Passer castanopterus", + "(C) Chalcomitra amethystina", + "(D) Nigrita canicapillus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3645588_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0856", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.121000 and latitude -0.548000 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Ficedula semitorquata", + "(C) Agricola pallidus", + "(D) Apalis jacksoni", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16433855_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0857", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.070350 and latitude -0.319439 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola galactotes", + "(B) Spatula hottentota", + "(C) Chroicocephalus genei", + "(D) Phoeniconaias minor", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5093141_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0858", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.291592 and latitude -0.723035 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Notopholia corusca", + "(B) Clanga pomarina", + "(C) Bradornis microrhynchus", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20055767_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0859", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431190 and latitude -0.718640 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lanius senator", + "(B) Nigrita bicolor", + "(C) Streptopelia capicola", + "(D) Corythornis cristatus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919755_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0860", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.181097 and latitude 0.921316 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.72 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 81.34. The temperature seasonality (100 times the standard deviation) is 80.70. The max temperature of the warmest month is 26.64 degrees. The min temperature of the coldest month is 10.36 degrees. The temperature annual range is 16.28 degrees. The mean temperature of the wettest quarter is 16.74 degrees. The mean temperature of the driest quarter is 18.20 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 16.72 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 21.0 mm. The precipitation seasonality (coefficient of variation) is 52.27. The precipitation of the wettest quarter is 389.0 mm. The precipitation of the driest quarter is 96.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 370.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Zosterops poliogastrus", + "(B) Chloropicus obsoletus", + "(C) Streptopelia capicola", + "(D) Monticola saxatilis", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15854931_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0861", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.308395 and latitude 0.472096 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spermestes cucullata", + "(B) Streptopelia lugens", + "(C) Apaloderma narina", + "(D) Spermestes griseicapilla", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17886635_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0862", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437416 and latitude -0.740186 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nectarinia kilimensis", + "(B) Haliaeetus vocifer", + "(C) Chlorocichla laetissima", + "(D) Glaucidium tephronotum", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12821674_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0863", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.775877 and latitude 0.935621 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.53 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 82.89. The temperature seasonality (100 times the standard deviation) is 75.43. The max temperature of the warmest month is 26.48 degrees. The min temperature of the coldest month is 8.92 degrees. The temperature annual range is 17.57 degrees. The mean temperature of the wettest quarter is 18.61 degrees. The mean temperature of the driest quarter is 17.45 degrees. The mean temperature of the warmest quarter is 18.61 degrees. The mean temperature of the coldest quarter is 16.72 degrees. The annual precipitation is 660.0 mm. The precipitation of the wettest month is 119.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 52.81. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 80.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 144.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Crithagra burtoni", + "(C) Charadrius dubius", + "(D) Polyboroides typus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17875037_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0864", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424516 and latitude -0.641202 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Hippolais icterina", + "(B) Passer rufocinctus", + "(C) Torgos tracheliotos", + "(D) Macronyx croceus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6833748_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0865", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111486 and latitude -0.310105 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lamprotornis hildebrandti", + "(B) Dicrurus adsimilis", + "(C) Alopochen aegyptiaca", + "(D) Calendulauda africanoides", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9354873_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0866", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610318 and latitude -2.980595 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pternistis hildebrandti", + "(B) Eurystomus glaucurus", + "(C) Circaetus pectoralis", + "(D) Prinia erythroptera", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12055115_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0867", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.210594 and latitude -0.408207 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pachyphantes superciliosus", + "(B) Coracias caudatus", + "(C) Egretta ardesiaca", + "(D) Eurillas curvirostris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284269_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0868", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.415048 and latitude -0.770567 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Alopochen aegyptiaca", + "(B) Nectarinia famosa", + "(C) Motacilla aguimp", + "(D) Vidua purpurascens", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207400_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0869", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063208 and latitude -0.269197 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Anthus similis", + "(B) Illadopsis pyrrhoptera", + "(C) Cossypha caffra", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13929931_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0870", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.772658 and latitude -0.324769 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.69 degrees. The mean diurnal range is 10.64 degrees. The isothermality is 85.02. The temperature seasonality (100 times the standard deviation) is 65.57. The max temperature of the warmest month is 29.12 degrees. The min temperature of the coldest month is 16.61 degrees. The temperature annual range is 12.51 degrees. The mean temperature of the wettest quarter is 22.99 degrees. The mean temperature of the driest quarter is 23.26 degrees. The mean temperature of the warmest quarter is 23.46 degrees. The mean temperature of the coldest quarter is 21.80 degrees. The annual precipitation is 1185.0 mm. The precipitation of the wettest month is 183.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 39.91. The precipitation of the wettest quarter is 477.0 mm. The precipitation of the driest quarter is 217.0 mm. The precipitation of the warmest quarter is 259.0 mm. The precipitation of the coldest quarter is 238.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Phoeniconaias minor", + "(B) Dendrocygna viduata", + "(C) Alcedo semitorquata", + "(D) Elminia longicauda", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17105361_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0871", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.921171 and latitude 1.388938 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.18 degrees. The mean diurnal range is 12.89 degrees. The isothermality is 83.58. The temperature seasonality (100 times the standard deviation) is 63.80. The max temperature of the warmest month is 29.46 degrees. The min temperature of the coldest month is 14.03 degrees. The temperature annual range is 15.42 degrees. The mean temperature of the wettest quarter is 20.76 degrees. The mean temperature of the driest quarter is 21.64 degrees. The mean temperature of the warmest quarter is 22.01 degrees. The mean temperature of the coldest quarter is 20.44 degrees. The annual precipitation is 1049.0 mm. The precipitation of the wettest month is 150.0 mm. The precipitation of the driest month is 23.0 mm. The precipitation seasonality (coefficient of variation) is 51.07. The precipitation of the wettest quarter is 387.0 mm. The precipitation of the driest quarter is 93.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 371.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis flavida", + "(B) Netta erythrophthalma", + "(C) Melocichla mentalis", + "(D) Streptopelia decipiens", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20746627_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0872", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120543 and latitude -0.369930 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Nettapus auritus", + "(B) Ichthyaetus ichthyaetus", + "(C) Alopochen aegyptiaca", + "(D) Riparia paludicola", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683759_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0873", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.272914 and latitude -0.773269 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Lagonosticta rubricata", + "(B) Stephanoaetus coronatus", + "(C) Melaenornis semipartitus", + "(D) Sarkidiornis melanotos", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260135_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0874", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.270547 and latitude -0.443776 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Pinarochroa sordida", + "(B) Eremomela turneri", + "(C) Struthio camelus", + "(D) Prinia erythroptera", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4463737_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0875", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.605042 and latitude -2.970730 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Cisticola juncidis", + "(B) Synoicus adansonii", + "(C) Burhinus vermiculatus", + "(D) Streptopelia semitorquata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12026564_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0876", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308164 and latitude -0.721051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numida meleagris", + "(B) Estrilda kandti", + "(C) Prodotiscus insignis", + "(D) Streptopelia capicola", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9956046_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0877", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.706267 and latitude -0.386098 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.23 degrees. The mean diurnal range is 10.12 degrees. The isothermality is 72.16. The temperature seasonality (100 times the standard deviation) is 126.04. The max temperature of the warmest month is 35.74 degrees. The min temperature of the coldest month is 21.72 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 28.40 degrees. The mean temperature of the driest quarter is 26.58 degrees. The mean temperature of the warmest quarter is 29.78 degrees. The mean temperature of the coldest quarter is 26.58 degrees. The annual precipitation is 358.0 mm. The precipitation of the wettest month is 95.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 103.10. The precipitation of the wettest quarter is 181.0 mm. The precipitation of the driest quarter is 15.0 mm. The precipitation of the warmest quarter is 125.0 mm. The precipitation of the coldest quarter is 15.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Spilopelia senegalensis", + "(B) Phoenicurus phoenicurus", + "(C) Columba livia", + "(D) Anthreptes reichenowi", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12768672_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0878", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452555 and latitude -0.745897 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Laniarius major", + "(B) Corvus albus", + "(C) Pinarochroa sordida", + "(D) Riparia paludicola", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14739048_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0879", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606940 and latitude -2.983382 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Chlidonias hybrida", + "(B) Burhinus vermiculatus", + "(C) Scleroptila shelleyi", + "(D) Dicrurus sharpei", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12085520_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0880", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437895 and latitude -0.727570 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Galerida theklae", + "(B) Circaetus cinereus", + "(C) Alopochen aegyptiaca", + "(D) Cuculus canorus", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17974825_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0881", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490242 and latitude -0.589063 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Indicator exilis", + "(B) Arizelocichla milanjensis", + "(C) Sterna dougallii", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11370815_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0882", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321595 and latitude -0.666745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Vanellus coronatus", + "(B) Uraeginthus bengalus", + "(C) Sterna repressa", + "(D) Colius striatus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22689728_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0883", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726090 and latitude -4.013932 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Bias musicus", + "(B) Microcarbo africanus", + "(C) Pycnonotus barbatus", + "(D) Ardeotis kori", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3039691_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0884", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.555278 and latitude -2.041702 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.60 degrees. The mean diurnal range is 11.48 degrees. The isothermality is 72.45. The temperature seasonality (100 times the standard deviation) is 130.85. The max temperature of the warmest month is 28.91 degrees. The min temperature of the coldest month is 13.06 degrees. The temperature annual range is 15.85 degrees. The mean temperature of the wettest quarter is 21.40 degrees. The mean temperature of the driest quarter is 19.06 degrees. The mean temperature of the warmest quarter is 21.94 degrees. The mean temperature of the coldest quarter is 18.69 degrees. The annual precipitation is 523.0 mm. The precipitation of the wettest month is 119.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 81.52. The precipitation of the wettest quarter is 258.0 mm. The precipitation of the driest quarter is 10.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 14.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sylvia atricapilla", + "(B) Circaetus beaudouini", + "(C) Pelecanus onocrotalus", + "(D) Struthio camelus", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14837930_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0885", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.789798 and latitude -3.798998 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Clamator jacobinus", + "(B) Motacilla aguimp", + "(C) Tringa nebularia", + "(D) Nettapus auritus", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4022409_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0886", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059912 and latitude -0.317391 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Campephaga phoenicea", + "(B) Anthus vaalensis", + "(C) Alopochen aegyptiaca", + "(D) Crex egregia", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7833802_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0887", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.086678 and latitude -0.360487 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rostratula benghalensis", + "(B) Pytilia afra", + "(C) Charadrius hiaticula", + "(D) Burhinus capensis", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11815420_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0888", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115220 and latitude -0.411950 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Apalis alticola", + "(B) Ceuthmochares aereus", + "(C) Alopochen aegyptiaca", + "(D) Scopus umbretta", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2663788_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0889", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.536243 and latitude -0.548666 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Numenius phaeopus", + "(B) Bostrychia hagedash", + "(C) Columba guinea", + "(D) Thalasseus bengalensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964149_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0890", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490874 and latitude -0.575399 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Stactolaema leucotis", + "(B) Anas undulata", + "(C) Dicrurus modestus", + "(D) Zosterops mbuluensis", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1235046_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0891", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.468400 and latitude -0.596197 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Charadrius tricollaris", + "(B) Alopochen aegyptiaca", + "(C) Burhinus senegalensis", + "(D) Chloropicus fuscescens", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11118238_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0892", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.075629 and latitude -0.436018 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Sarkidiornis melanotos", + "(B) Batis orientalis", + "(C) Gyps rueppelli", + "(D) Euplectes axillaris", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020563_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0893", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612265 and latitude -2.983033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Rhodophoneus cruentus", + "(B) Pternistis hildebrandti", + "(C) Oriolus brachyrynchus", + "(D) Ploceus heuglini", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12135116_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0894", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249964 and latitude -0.432776 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Clanga pomarina", + "(B) Alopochen aegyptiaca", + "(C) Trigonoceps occipitalis", + "(D) Arizelocichla nigriceps", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12667927_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0895", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429561 and latitude -0.719988 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Onychognathus morio", + "(B) Pycnonotus barbatus", + "(C) Malimbus rubricollis", + "(D) Anas undulata", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16347346_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0896", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120112 and latitude -0.411840 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Ispidina picta", + "(B) Iduna pallida", + "(C) Lamprotornis chalcurus", + "(D) Alopochen aegyptiaca", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6680860_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0897", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.618337 and latitude -0.963265 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.81 degrees. The mean diurnal range is 11.52 degrees. The isothermality is 75.52. The temperature seasonality (100 times the standard deviation) is 113.42. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 14.71 degrees. The temperature annual range is 15.26 degrees. The mean temperature of the wettest quarter is 22.28 degrees. The mean temperature of the driest quarter is 20.19 degrees. The mean temperature of the warmest quarter is 22.99 degrees. The mean temperature of the coldest quarter is 20.19 degrees. The annual precipitation is 777.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 104.94. The precipitation of the wettest quarter is 357.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 305.0 mm. The precipitation of the coldest quarter is 13.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Euplectes capensis", + "(B) Pternistis leucoscepus", + "(C) Lybius bidentatus", + "(D) Poicephalus rufiventris", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14860959_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0898", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456055 and latitude -0.569332 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Columba guinea", + "(B) Oxyura maccoa", + "(C) Estrilda paludicola", + "(D) Gyps africanus", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347994_visual.jpg" + ] + }, + { + "Question_id": "Most likely species to occur/0899", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.032394 and latitude -0.058795 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. Which of the following bird species is most likely to occur in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Most likely species to occur", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Dendrocygna viduata", + "(B) Ciconia nigra", + "(C) Acrocephalus scirpaceus", + "(D) Campocolinus coqui", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12143078_visual.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_occurrence_probability_estimation.json b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_occurrence_probability_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..41d1b389cc71dd28a0c8a95ff82a1f026f8fd796 --- /dev/null +++ b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_occurrence_probability_estimation.json @@ -0,0 +1,9515 @@ +[ + { + "Question_id": "Species occurrence probability estimation/0006", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.392700 and latitude -0.635840 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Balearica regulorum occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120392_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0008", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375457 and latitude 0.607683 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Buteo augur occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15843032_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0009", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.525207 and latitude -0.617251 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Vanellus melanopterus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294819_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0010", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.374544 and latitude 0.606404 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Gallinago nigripennis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13962733_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0013", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.280240 and latitude -0.456203 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290905_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0015", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.949176 and latitude -0.231627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Hirundo smithii occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20132459_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0016", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495022 and latitude -0.586243 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16218182_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0018", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.321445 and latitude -0.749309 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. What is the probability of the species Lanius excubitoroides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449320_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0019", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.609671 and latitude -0.515350 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Turdus abyssinicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18745097_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0020", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.272520 and latitude -0.827416 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467884_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0022", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429442 and latitude -0.703606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Chalcomitra amethystina occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16189252_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0026", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.135577 and latitude -0.676287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. What is the probability of the species Aquila rapax occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10501648_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0027", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.866303 and latitude 1.071369 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. What is the probability of the species Ciconia abdimii occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9061441_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0028", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560670 and latitude -0.553776 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21033789_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0030", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.336645 and latitude -0.649582 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola chiniana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16553147_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0032", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.506728 and latitude -0.565488 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16785945_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0034", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.053010 and latitude -0.427459 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Vidua macroura occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22969685_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0035", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369008 and latitude -0.852497 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Oenanthe lugubris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20971407_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0041", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.704891 and latitude -0.448206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.31 degrees. The mean diurnal range is 11.79 degrees. The isothermality is 81.32. The temperature seasonality (100 times the standard deviation) is 71.36. The max temperature of the warmest month is 20.27 degrees. The min temperature of the coldest month is 5.77 degrees. The temperature annual range is 14.50 degrees. The mean temperature of the wettest quarter is 11.42 degrees. The mean temperature of the driest quarter is 12.71 degrees. The mean temperature of the warmest quarter is 13.20 degrees. The mean temperature of the coldest quarter is 11.42 degrees. The annual precipitation is 1210.0 mm. The precipitation of the wettest month is 174.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 42.21. The precipitation of the wettest quarter is 408.0 mm. The precipitation of the driest quarter is 157.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 408.0 mm. What is the probability of the species Streptopelia capicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16285046_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0042", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.073127 and latitude -0.304779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Phoeniconaias minor occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8664033_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0043", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.139337 and latitude -0.676059 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. What is the probability of the species Milvus migrans occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5159521_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0046", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.560444 and latitude 0.293821 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12826528_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0047", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.530309 and latitude -0.553023 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Saxicola torquatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22174073_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0049", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.068174 and latitude -3.745175 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.10 degrees. The mean diurnal range is 9.47 degrees. The isothermality is 67.84. The temperature seasonality (100 times the standard deviation) is 147.05. The max temperature of the warmest month is 31.33 degrees. The min temperature of the coldest month is 17.38 degrees. The temperature annual range is 13.95 degrees. The mean temperature of the wettest quarter is 24.55 degrees. The mean temperature of the driest quarter is 22.25 degrees. The mean temperature of the warmest quarter is 25.70 degrees. The mean temperature of the coldest quarter is 22.21 degrees. The annual precipitation is 704.0 mm. The precipitation of the wettest month is 105.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 49.88. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 100.0 mm. What is the probability of the species Passer domesticus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17070362_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0050", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375622 and latitude 0.607860 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Lagonosticta senegala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498960_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0051", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.516404 and latitude -0.621530 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Estrilda astrild occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15773403_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0052", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419660 and latitude -0.693710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ploceus spekei occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235554_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0056", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471970 and latitude -0.829753 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10348524_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0057", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572807 and latitude -0.608167 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Motacilla capensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12544941_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0060", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368079 and latitude -0.486409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21193393_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0061", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.182879 and latitude -1.486376 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16920068_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0063", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368525 and latitude -0.850262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467384_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0064", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308605 and latitude -0.143869 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Anas undulata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9083281_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0066", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.475232 and latitude -0.626622 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Lanius humeralis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294840_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0068", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419903 and latitude -0.693012 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lophaetus occipitalis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284267_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0069", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.319829 and latitude -0.895510 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. What is the probability of the species Apalis flavida occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674637_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0070", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663894 and latitude -0.524886 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Cinnyris mediocris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106454_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0072", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435363 and latitude -0.759531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Pelecanus rufescens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21141544_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0073", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.422322 and latitude -0.769772 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lophoceros nasutus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16775941_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0075", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.088557 and latitude 1.765971 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.29 degrees. The mean diurnal range is 11.01 degrees. The isothermality is 73.01. The temperature seasonality (100 times the standard deviation) is 112.08. The max temperature of the warmest month is 36.63 degrees. The min temperature of the coldest month is 21.55 degrees. The temperature annual range is 15.08 degrees. The mean temperature of the wettest quarter is 29.15 degrees. The mean temperature of the driest quarter is 27.01 degrees. The mean temperature of the warmest quarter is 29.79 degrees. The mean temperature of the coldest quarter is 27.01 degrees. The annual precipitation is 344.0 mm. The precipitation of the wettest month is 102.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 105.81. The precipitation of the wettest quarter is 172.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 52.0 mm. The precipitation of the coldest quarter is 8.0 mm. What is the probability of the species Leptoptilos crumenifer occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12546876_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0076", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.259475 and latitude -0.810887 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Columba guinea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294170_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0079", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.123014 and latitude -0.392039 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Merops bullockoides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21172815_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0082", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486100 and latitude -0.635759 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola hunteri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17772247_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0084", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323675 and latitude -0.499642 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Apus affinis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20336553_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0087", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420049 and latitude -0.692290 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638675_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0094", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.143364 and latitude -0.317675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Corvus albus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20990360_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0095", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663925 and latitude -0.525000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Crithagra striolata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952181_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0097", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.868821 and latitude -0.991104 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.10 degrees. The mean diurnal range is 12.02 degrees. The isothermality is 81.24. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 25.91 degrees. The min temperature of the coldest month is 11.12 degrees. The temperature annual range is 14.79 degrees. The mean temperature of the wettest quarter is 18.57 degrees. The mean temperature of the driest quarter is 17.21 degrees. The mean temperature of the warmest quarter is 19.06 degrees. The mean temperature of the coldest quarter is 17.17 degrees. The annual precipitation is 1634.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 81.0 mm. The precipitation seasonality (coefficient of variation) is 33.85. The precipitation of the wettest quarter is 594.0 mm. The precipitation of the driest quarter is 321.0 mm. The precipitation of the warmest quarter is 352.0 mm. The precipitation of the coldest quarter is 324.0 mm. What is the probability of the species Laniarius major occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16111596_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0101", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321573 and latitude -0.815879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Actophilornis africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2674368_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0102", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.134727 and latitude -3.283860 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.99 degrees. The mean diurnal range is 11.08 degrees. The isothermality is 68.93. The temperature seasonality (100 times the standard deviation) is 157.66. The max temperature of the warmest month is 30.57 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 16.08 degrees. The mean temperature of the wettest quarter is 22.82 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 23.75 degrees. The mean temperature of the coldest quarter is 19.88 degrees. The annual precipitation is 681.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 8.0 mm. The precipitation seasonality (coefficient of variation) is 86.43. The precipitation of the wettest quarter is 311.0 mm. The precipitation of the driest quarter is 28.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 28.0 mm. What is the probability of the species Cinnyris tsavoensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23139548_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0107", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095495 and latitude -0.226743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17442753_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0108", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726778 and latitude -4.008682 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Microcarbo africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15592344_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0112", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129259 and latitude -0.423819 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498976_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0113", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.391011 and latitude 0.591302 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22761827_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0114", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.238076 and latitude -0.406703 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7023051_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0115", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.091412 and latitude -0.270824 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17518972_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0117", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420072 and latitude -0.692664 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Chrysococcyx caprius occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3853026_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0118", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308716 and latitude -0.144961 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Microparra capensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689305_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0122", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.192613 and latitude -0.397264 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6814199_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0125", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.615962 and latitude -0.492373 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. What is the probability of the species Psalidoprocne pristoptera occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12920048_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0126", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.338270 and latitude -0.876449 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10037320_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0129", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.630098 and latitude -0.486990 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. What is the probability of the species Merops oreobates occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462321_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0132", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.625373 and latitude -4.005898 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Apus affinis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21072125_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0133", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.881431 and latitude -1.713421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16916219_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0134", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.195626 and latitude -0.470653 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Cossypha heuglini occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4295706_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0135", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.543559 and latitude -0.545766 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Anthus cinnamomeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4499224_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0138", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.558097 and latitude -0.546847 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Pinarochroa sordida occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106357_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0139", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308797 and latitude -0.144997 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Buteo oreophilus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689310_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0141", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635711 and latitude -3.166800 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.21 degrees. The mean diurnal range is 8.43 degrees. The isothermality is 67.81. The temperature seasonality (100 times the standard deviation) is 127.80. The max temperature of the warmest month is 31.70 degrees. The min temperature of the coldest month is 19.26 degrees. The temperature annual range is 12.44 degrees. The mean temperature of the wettest quarter is 25.58 degrees. The mean temperature of the driest quarter is 26.49 degrees. The mean temperature of the warmest quarter is 26.66 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 772.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 52.07. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 104.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 128.0 mm. What is the probability of the species Speculipastor bicolor occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176915_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0142", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237815 and latitude -0.399852 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16702750_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0143", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.325837 and latitude -0.880693 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. What is the probability of the species Buteo augur occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674644_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0146", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425782 and latitude -0.734198 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19074709_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0148", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229283 and latitude -0.396912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4209333_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0149", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431405 and latitude -0.844088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12492683_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0153", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.514038 and latitude -2.533392 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. What is the probability of the species Hirundo smithii occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2665890_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0158", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.276000 and latitude -0.769000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Buphagus erythrorynchus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2372252_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0159", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.412310 and latitude -0.773144 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ceryle rudis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9338447_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0163", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465225 and latitude -0.736990 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Anthus cinnamomeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23190870_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0164", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.320935 and latitude -1.256069 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.94 degrees. The mean diurnal range is 11.66 degrees. The isothermality is 73.58. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 28.34 degrees. The min temperature of the coldest month is 12.49 degrees. The temperature annual range is 15.84 degrees. The mean temperature of the wettest quarter is 20.91 degrees. The mean temperature of the driest quarter is 18.46 degrees. The mean temperature of the warmest quarter is 21.24 degrees. The mean temperature of the coldest quarter is 18.16 degrees. The annual precipitation is 753.0 mm. The precipitation of the wettest month is 180.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 95.06. The precipitation of the wettest quarter is 331.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 301.0 mm. The precipitation of the coldest quarter is 18.0 mm. What is the probability of the species Cinnyris venustus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17198500_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0165", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262911 and latitude -0.816015 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151424_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0168", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260102 and latitude -0.814364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20004655_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0169", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217298 and latitude 0.159901 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. What is the probability of the species Apus affinis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13087824_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0172", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.503816 and latitude -0.565360 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232902_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0175", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.077002 and latitude -0.319021 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Pelecanus rufescens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16098203_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0178", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.959969 and latitude -0.040555 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Vanellus tectus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11469923_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0179", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.462258 and latitude -0.903389 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Serinus flavivertex occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674581_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0181", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375000 and latitude 0.606944 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Saxicola torquatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10171402_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0185", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237024 and latitude -0.397715 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Agricola pallidus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20792007_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0186", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.725290 and latitude -0.391729 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Drepanorhynchus reichenowi occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283134_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0187", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.504741 and latitude -3.146385 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. What is the probability of the species Calendulauda poecilosterna occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176924_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0188", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464045 and latitude -0.738076 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Crithagra sulphurata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16432755_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0192", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.666655 and latitude -0.416597 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. What is the probability of the species Cisticola aberdare occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15780478_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0193", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.607773 and latitude -4.033453 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Ardea melanocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070470_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0194", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.127913 and latitude -0.425033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446678_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0196", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308737 and latitude -0.144019 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Jynx ruficollis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21584322_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0198", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321058 and latitude -0.512058 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. What is the probability of the species Bucorvus leadbeateri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5541002_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0199", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.356469 and latitude -0.738459 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. What is the probability of the species Ploceus cucullatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563397_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0200", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.667486 and latitude -1.245196 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.46 degrees. The mean diurnal range is 11.48 degrees. The isothermality is 73.55. The temperature seasonality (100 times the standard deviation) is 122.66. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 14.09 degrees. The temperature annual range is 15.61 degrees. The mean temperature of the wettest quarter is 21.93 degrees. The mean temperature of the driest quarter is 19.68 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.68 degrees. The annual precipitation is 724.0 mm. The precipitation of the wettest month is 225.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 113.52. The precipitation of the wettest quarter is 383.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 8.0 mm. What is the probability of the species Prinia subflava occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12595326_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0202", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.630898 and latitude -2.885577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Merops bullockoides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10986333_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0207", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724500 and latitude -0.498620 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Zosterops kikuyuensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844377_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0208", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059661 and latitude 3.685803 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.60 degrees. The mean diurnal range is 9.46 degrees. The isothermality is 80.33. The temperature seasonality (100 times the standard deviation) is 76.16. The max temperature of the warmest month is 34.84 degrees. The min temperature of the coldest month is 23.06 degrees. The temperature annual range is 11.78 degrees. The mean temperature of the wettest quarter is 28.96 degrees. The mean temperature of the driest quarter is 28.27 degrees. The mean temperature of the warmest quarter is 29.56 degrees. The mean temperature of the coldest quarter is 27.64 degrees. The annual precipitation is 203.0 mm. The precipitation of the wettest month is 46.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 80.02. The precipitation of the wettest quarter is 100.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 53.0 mm. The precipitation of the coldest quarter is 19.0 mm. What is the probability of the species Ardea purpurea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6286237_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0210", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.155125 and latitude 0.734127 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.31 degrees. The mean diurnal range is 13.08 degrees. The isothermality is 82.01. The temperature seasonality (100 times the standard deviation) is 78.19. The max temperature of the warmest month is 27.02 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.95 degrees. The mean temperature of the wettest quarter is 17.32 degrees. The mean temperature of the driest quarter is 18.80 degrees. The mean temperature of the warmest quarter is 19.29 degrees. The mean temperature of the coldest quarter is 17.32 degrees. The annual precipitation is 1160.0 mm. The precipitation of the wettest month is 188.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 56.08. The precipitation of the wettest quarter is 474.0 mm. The precipitation of the driest quarter is 103.0 mm. The precipitation of the warmest quarter is 250.0 mm. The precipitation of the coldest quarter is 474.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8677517_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0211", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.146769 and latitude -0.421919 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Merops bullockoides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16582092_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0212", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117312 and latitude -0.315226 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794204_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0216", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115849 and latitude -0.437562 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Melaenornis fischeri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214619_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0218", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120639 and latitude -0.423215 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Lamprotornis chalybaeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446569_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0220", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451164 and latitude -0.732254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Corvus albus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14087358_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0221", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.570883 and latitude 0.318314 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. What is the probability of the species Falco amurensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6107052_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0223", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.670429 and latitude -4.094411 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Plectropterus gambensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2939352_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0225", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450963 and latitude -0.498124 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Cecropis daurica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6303604_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0228", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442316 and latitude -0.734910 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Oenanthe lugubris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12913249_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0230", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337747 and latitude -2.249538 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. What is the probability of the species Ketupa lacteus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21230539_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0237", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564208 and latitude -0.562112 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Tachybaptus ruficollis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16788493_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0239", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.261411 and latitude -1.398081 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12139266_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0242", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.109989 and latitude -0.307528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3189156_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0243", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.573481 and latitude -2.962016 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Eurystomus glaucurus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18498363_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0244", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473665 and latitude -0.594187 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Muscicapa adusta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16089193_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0246", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.977112 and latitude -0.177386 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Streptopelia capicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16897456_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0247", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362561 and latitude -0.858995 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Cisticola brunnescens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18075784_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0249", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.964847 and latitude -0.002364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Melaenornis semipartitus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6108684_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0250", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477656 and latitude -0.711947 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4016734_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0251", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.257458 and latitude -0.482749 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Urocolius macrourus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284276_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0252", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731725 and latitude -3.989566 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Platysteira peltata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16824651_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0255", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.956106 and latitude -0.021973 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Lamprotornis purpuroptera occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18789323_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0256", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.218005 and latitude -0.411473 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17946602_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0258", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090603 and latitude -0.191745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Buteo augur occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487379_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0259", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.787467 and latitude -3.860947 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Cypsiurus parvus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511369_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0262", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458876 and latitude -0.737428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lamprotornis chalybaeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17640008_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0265", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.874158 and latitude -1.662879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. What is the probability of the species Chalcomitra senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18585100_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0268", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.388683 and latitude -0.692627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Haliaeetus vocifer occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21912123_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0270", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.528911 and latitude -2.523347 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. What is the probability of the species Halcyon leucocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6312722_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0272", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328129 and latitude -0.745161 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Megaceryle maxima occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2344413_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0275", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444426 and latitude -0.713927 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21640695_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0278", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217477 and latitude 0.159772 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. What is the probability of the species Glareola nuchalis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14801976_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0282", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.213000 and latitude -0.418000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Pelecanus rufescens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16177177_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0283", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.600571 and latitude -4.029169 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Milvus migrans occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21137855_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0284", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.771232 and latitude -3.944620 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Microcarbo africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6755433_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0287", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429457 and latitude -0.629157 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Camaroptera brachyura occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520360_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0291", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.275253 and latitude -0.827148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Hirundo rustica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22718838_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0292", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635757 and latitude -3.166420 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. What is the probability of the species Tockus deckeni occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104263_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0293", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428538 and latitude -0.709808 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20882646_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0295", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.559850 and latitude -3.165834 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. What is the probability of the species Tmetothylacus tenellus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22860349_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0297", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.726790 and latitude -0.433400 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Anas undulata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844387_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0300", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.219629 and latitude -0.479424 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Estrilda rhodopyga occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237310_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0302", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.107865 and latitude -0.257710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Ploceus cucullatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12620886_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0303", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263226 and latitude -0.820533 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4137246_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0305", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458126 and latitude -0.527085 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13033573_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0308", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.676052 and latitude -0.482208 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Serinus flavivertex occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22520447_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0314", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471611 and latitude -0.894685 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Numida meleagris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674569_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0317", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.022308 and latitude -0.070060 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. What is the probability of the species Creatophora cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12901835_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0319", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.808845 and latitude 0.249657 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.38 degrees. The mean diurnal range is 15.42 degrees. The isothermality is 79.55. The temperature seasonality (100 times the standard deviation) is 56.98. The max temperature of the warmest month is 27.08 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 19.39 degrees. The mean temperature of the wettest quarter is 18.16 degrees. The mean temperature of the driest quarter is 17.19 degrees. The mean temperature of the warmest quarter is 18.16 degrees. The mean temperature of the coldest quarter is 16.83 degrees. The annual precipitation is 709.0 mm. The precipitation of the wettest month is 126.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 49.31. The precipitation of the wettest quarter is 259.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 259.0 mm. The precipitation of the coldest quarter is 176.0 mm. What is the probability of the species Camaroptera brachyura occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8193671_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0320", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486027 and latitude -0.645036 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17730556_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0325", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.601035 and latitude -4.030511 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5404977_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0326", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473812 and latitude -0.589608 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952019_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0327", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.446179 and latitude -0.755743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23122301_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0329", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.940865 and latitude -1.097290 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.63 degrees. The mean diurnal range is 9.45 degrees. The isothermality is 69.39. The temperature seasonality (100 times the standard deviation) is 135.63. The max temperature of the warmest month is 34.78 degrees. The min temperature of the coldest month is 21.16 degrees. The temperature annual range is 13.62 degrees. The mean temperature of the wettest quarter is 28.10 degrees. The mean temperature of the driest quarter is 25.77 degrees. The mean temperature of the warmest quarter is 29.16 degrees. The mean temperature of the coldest quarter is 25.77 degrees. The annual precipitation is 425.0 mm. The precipitation of the wettest month is 100.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 95.08. The precipitation of the wettest quarter is 194.0 mm. The precipitation of the driest quarter is 24.0 mm. The precipitation of the warmest quarter is 152.0 mm. The precipitation of the coldest quarter is 24.0 mm. What is the probability of the species Dicrurus adsimilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12753463_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0331", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.381939 and latitude -0.762206 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. What is the probability of the species Turdoides jardineii occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449300_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0332", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116309 and latitude -0.410675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Motacilla flava occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683921_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0333", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.301178 and latitude 0.472054 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Batis molitor occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5190089_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0336", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.191342 and latitude -1.465708 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. What is the probability of the species Cecropis daurica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22054860_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0344", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.448282 and latitude -0.727571 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511060_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0346", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418797 and latitude -0.720689 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Treron calvus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18137410_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0348", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260664 and latitude -0.451287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Platalea alba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22454762_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0349", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537651 and latitude -0.548722 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Anthus cinnamomeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11217739_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0352", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.621668 and latitude -0.492862 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. What is the probability of the species Iduna similis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970656_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0353", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.594228 and latitude -0.520317 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970890_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0355", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.389996 and latitude -0.846563 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614321_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0357", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.299127 and latitude 0.750025 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.45 degrees. The mean diurnal range is 13.17 degrees. The isothermality is 82.23. The temperature seasonality (100 times the standard deviation) is 77.96. The max temperature of the warmest month is 26.16 degrees. The min temperature of the coldest month is 10.14 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 16.45 degrees. The mean temperature of the driest quarter is 17.86 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.45 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 160.0 mm. The precipitation of the driest month is 24.0 mm. The precipitation seasonality (coefficient of variation) is 52.76. The precipitation of the wettest quarter is 398.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 380.0 mm. What is the probability of the species Crinifer zonurus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18568633_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0360", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.300407 and latitude -0.818526 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Actophilornis africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304185_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0361", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.426550 and latitude -0.700406 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. What is the probability of the species Atimastillas flavicollis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436289_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0363", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.314601 and latitude -0.814606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Dicrurus adsimilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5635215_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0366", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.373900 and latitude 0.606011 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. What is the probability of the species Motacilla flava occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14384250_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0368", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369111 and latitude -0.852654 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Sagittarius serpentarius occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18272761_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0369", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.393146 and latitude -0.809223 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Megaceryle maxima occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9850797_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0370", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189833 and latitude -0.808010 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Psalidoprocne pristoptera occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21155579_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0372", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.315994 and latitude -0.505364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1966451_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0373", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.413886 and latitude -0.714329 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Chroicocephalus cirrocephalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526554_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0374", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.587900 and latitude -0.527418 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Corvus albus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14838352_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0375", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492998 and latitude -0.573957 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola tinniens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258666_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0376", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189847 and latitude -0.499457 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Lagonosticta rubricata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4192719_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0378", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391354 and latitude -0.810172 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076203_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0380", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477413 and latitude -0.548408 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Melaenornis fischeri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952041_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0381", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.292430 and latitude -0.474668 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Lanius collurio occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10016562_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0382", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.750250 and latitude -0.385840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Riparia paludicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844397_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0383", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.553340 and latitude -0.544870 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Saxicola torquatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12677036_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0385", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.109073 and latitude -0.625061 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. What is the probability of the species Cossypha natalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5053497_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0387", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.787022 and latitude -3.611775 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12512160_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0388", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428950 and latitude -0.631089 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520123_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0389", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.309540 and latitude 0.480940 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Laniarius major occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025079_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0391", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117551 and latitude -0.423970 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Ardea cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20175100_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0395", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493108 and latitude -0.574312 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola hunteri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13649793_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0397", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464309 and latitude -0.711496 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7793665_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0400", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554389 and latitude -0.545723 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Cisticola hunteri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4897237_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0401", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323909 and latitude -0.716962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14451311_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0405", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572693 and latitude -0.608155 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Micronisus gabar occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14188081_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0406", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.439377 and latitude -0.736368 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Passer griseus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17074113_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0407", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469185 and latitude -0.596552 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola tinniens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20163417_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0408", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438713 and latitude -0.728692 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7239787_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0409", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.732674 and latitude -3.996109 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Ardea melanocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8781358_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0410", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.581564 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Threskiornis aethiopicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462486_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0411", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.745582 and latitude -3.935211 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Tringa glareola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6368285_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0414", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401497 and latitude -0.775472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lanius excubitoroides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17279003_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0416", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084155 and latitude -0.310158 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22149720_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0417", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.987358 and latitude -0.065888 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Mirafra africana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020893_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0419", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309504 and latitude -0.144840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Anas undulata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17105797_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0422", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.751548 and latitude -3.972793 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Dicrurus adsimilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15271561_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0424", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.025098 and latitude -0.272587 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487314_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0429", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731682 and latitude -3.989279 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Butorides striata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19738874_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0431", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.755890 and latitude 0.551423 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.52 degrees. The mean diurnal range is 12.84 degrees. The isothermality is 83.19. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 16.30 degrees. The temperature annual range is 15.43 degrees. The mean temperature of the wettest quarter is 23.34 degrees. The mean temperature of the driest quarter is 22.72 degrees. The mean temperature of the warmest quarter is 24.38 degrees. The mean temperature of the coldest quarter is 22.72 degrees. The annual precipitation is 533.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.08. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 11.0 mm. What is the probability of the species Melierax poliopterus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2262871_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0432", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.633362 and latitude -0.206337 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.24 degrees. The mean diurnal range is 10.34 degrees. The isothermality is 73.35. The temperature seasonality (100 times the standard deviation) is 120.47. The max temperature of the warmest month is 35.74 degrees. The min temperature of the coldest month is 21.65 degrees. The temperature annual range is 14.10 degrees. The mean temperature of the wettest quarter is 28.40 degrees. The mean temperature of the driest quarter is 26.66 degrees. The mean temperature of the warmest quarter is 29.73 degrees. The mean temperature of the coldest quarter is 26.66 degrees. The annual precipitation is 333.0 mm. The precipitation of the wettest month is 93.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.95. The precipitation of the wettest quarter is 176.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 116.0 mm. The precipitation of the coldest quarter is 11.0 mm. What is the probability of the species Pterocles decoratus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734557_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0434", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.584468 and latitude -0.349529 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.23 degrees. The mean diurnal range is 12.53 degrees. The isothermality is 82.31. The temperature seasonality (100 times the standard deviation) is 70.01. The max temperature of the warmest month is 22.62 degrees. The min temperature of the coldest month is 7.39 degrees. The temperature annual range is 15.23 degrees. The mean temperature of the wettest quarter is 14.39 degrees. The mean temperature of the driest quarter is 14.68 degrees. The mean temperature of the warmest quarter is 15.10 degrees. The mean temperature of the coldest quarter is 13.35 degrees. The annual precipitation is 1397.0 mm. The precipitation of the wettest month is 193.0 mm. The precipitation of the driest month is 47.0 mm. The precipitation seasonality (coefficient of variation) is 43.71. The precipitation of the wettest quarter is 492.0 mm. The precipitation of the driest quarter is 171.0 mm. The precipitation of the warmest quarter is 331.0 mm. The precipitation of the coldest quarter is 460.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20352553_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0437", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461087 and latitude -0.740838 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Cuculus solitarius occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15448089_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0443", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456529 and latitude -0.738829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Oriolus larvatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20255070_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0444", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.741623 and latitude -3.608959 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. What is the probability of the species Calamonastes simplex occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1461598_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0445", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307068 and latitude -0.719586 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Pelecanus onocrotalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2126423_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0448", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.416637 and latitude -0.725118 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ardea intermedia occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10009116_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0449", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.877869 and latitude -3.632665 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.32 degrees. The mean diurnal range is 10.16 degrees. The isothermality is 69.34. The temperature seasonality (100 times the standard deviation) is 150.42. The max temperature of the warmest month is 31.94 degrees. The min temperature of the coldest month is 17.29 degrees. The temperature annual range is 14.65 degrees. The mean temperature of the wettest quarter is 24.78 degrees. The mean temperature of the driest quarter is 22.40 degrees. The mean temperature of the warmest quarter is 25.97 degrees. The mean temperature of the coldest quarter is 22.36 degrees. The annual precipitation is 730.0 mm. The precipitation of the wettest month is 117.0 mm. The precipitation of the driest month is 21.0 mm. The precipitation seasonality (coefficient of variation) is 58.42. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 72.0 mm. The precipitation of the warmest quarter is 226.0 mm. The precipitation of the coldest quarter is 85.0 mm. What is the probability of the species Cypsiurus parvus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1875249_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0450", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.126686 and latitude -0.361053 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Bucorvus leadbeateri occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6525805_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0451", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461958 and latitude -0.739721 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16981110_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0452", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.481020 and latitude -0.629872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11533438_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0454", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.256105 and latitude -0.817704 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Passer rufocinctus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22415482_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0456", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.472665 and latitude -0.629135 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Colius striatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11371034_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0458", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.472955 and latitude 0.000007 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.41 degrees. The mean diurnal range is 10.47 degrees. The isothermality is 74.66. The temperature seasonality (100 times the standard deviation) is 111.40. The max temperature of the warmest month is 34.82 degrees. The min temperature of the coldest month is 20.80 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 27.52 degrees. The mean temperature of the driest quarter is 25.94 degrees. The mean temperature of the warmest quarter is 28.79 degrees. The mean temperature of the coldest quarter is 25.94 degrees. The annual precipitation is 318.0 mm. The precipitation of the wettest month is 96.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 121.15. The precipitation of the wettest quarter is 175.0 mm. The precipitation of the driest quarter is 4.0 mm. The precipitation of the warmest quarter is 118.0 mm. The precipitation of the coldest quarter is 4.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13474964_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0459", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.893886 and latitude -1.640236 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. What is the probability of the species Mirafra africana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17524706_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0460", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.105425 and latitude -0.279641 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Chalcomitra senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14796716_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0463", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469800 and latitude -0.597199 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Ardea cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22469746_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0464", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.740000 and latitude -3.928000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Corvus splendens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6200626_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0467", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309045 and latitude -0.144258 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13918587_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0468", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450073 and latitude -0.742200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20973630_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0469", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.403588 and latitude -0.760829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Actophilornis africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1770518_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0474", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.603889 and latitude -0.673041 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.91 degrees. The mean diurnal range is 10.14 degrees. The isothermality is 71.62. The temperature seasonality (100 times the standard deviation) is 130.14. The max temperature of the warmest month is 35.39 degrees. The min temperature of the coldest month is 21.24 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 28.23 degrees. The mean temperature of the driest quarter is 26.16 degrees. The mean temperature of the warmest quarter is 29.46 degrees. The mean temperature of the coldest quarter is 26.16 degrees. The annual precipitation is 417.0 mm. The precipitation of the wettest month is 110.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 103.09. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 145.0 mm. The precipitation of the coldest quarter is 16.0 mm. What is the probability of the species Coracias caudatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974502_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0475", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.313000 and latitude -2.304400 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.09 degrees. The mean diurnal range is 7.52 degrees. The isothermality is 66.86. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 33.17 degrees. The min temperature of the coldest month is 21.92 degrees. The temperature annual range is 11.25 degrees. The mean temperature of the wettest quarter is 27.14 degrees. The mean temperature of the driest quarter is 28.26 degrees. The mean temperature of the warmest quarter is 28.48 degrees. The mean temperature of the coldest quarter is 25.50 degrees. The annual precipitation is 806.0 mm. The precipitation of the wettest month is 149.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 56.60. The precipitation of the wettest quarter is 348.0 mm. The precipitation of the driest quarter is 81.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 160.0 mm. What is the probability of the species Halcyon leucocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3059463_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0476", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.032930 and latitude 0.718093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. What is the probability of the species Lamprotornis purpuroptera occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10504169_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0477", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.513280 and latitude -0.193907 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. What is the probability of the species Agricola pallidus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462536_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0479", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.026337 and latitude -2.514263 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.85 degrees. The mean diurnal range is 12.31 degrees. The isothermality is 72.62. The temperature seasonality (100 times the standard deviation) is 142.97. The max temperature of the warmest month is 30.87 degrees. The min temperature of the coldest month is 13.92 degrees. The temperature annual range is 16.95 degrees. The mean temperature of the wettest quarter is 22.68 degrees. The mean temperature of the driest quarter is 20.07 degrees. The mean temperature of the warmest quarter is 23.33 degrees. The mean temperature of the coldest quarter is 19.80 degrees. The annual precipitation is 587.0 mm. The precipitation of the wettest month is 125.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 81.83. The precipitation of the wettest quarter is 262.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 177.0 mm. The precipitation of the coldest quarter is 15.0 mm. What is the probability of the species Struthio camelus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7148979_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0480", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946283 and latitude -0.063598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Ardea melanocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22563197_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0481", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250000 and latitude -0.432800 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11221555_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0483", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326134 and latitude -0.717464 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Ardea cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17291269_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0485", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453735 and latitude -0.729773 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Milvus migrans occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15873929_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0486", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.878873 and latitude 1.048376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. What is the probability of the species Euplectes axillaris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8685118_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0487", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.083000 and latitude -0.366000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Charadrius tricollaris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11222896_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0493", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.003179 and latitude -1.382342 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. What is the probability of the species Platalea alba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17063854_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0494", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.723417 and latitude -4.025348 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Anthus cinnamomeus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10702920_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0499", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421278 and latitude -0.675163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Pelecanus rufescens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18607968_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0502", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492103 and latitude -0.572615 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Macronyx sharpei occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18099519_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0503", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.382245 and latitude -0.719936 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. What is the probability of the species Turdus pelios occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563225_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0508", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493826 and latitude -0.574831 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Euplectes jacksoni occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232869_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0510", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444822 and latitude -0.724114 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Passer domesticus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16776594_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0512", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419407 and latitude -0.591604 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Megaceryle maxima occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6864111_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0513", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452536 and latitude -0.737041 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lanius humeralis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20290844_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0515", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.928646 and latitude 2.241613 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.99 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 81.08. The temperature seasonality (100 times the standard deviation) is 79.21. The max temperature of the warmest month is 30.29 degrees. The min temperature of the coldest month is 15.88 degrees. The temperature annual range is 14.40 degrees. The mean temperature of the wettest quarter is 23.83 degrees. The mean temperature of the driest quarter is 22.08 degrees. The mean temperature of the warmest quarter is 24.02 degrees. The mean temperature of the coldest quarter is 22.01 degrees. The annual precipitation is 347.0 mm. The precipitation of the wettest month is 81.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 78.03. The precipitation of the wettest quarter is 164.0 mm. The precipitation of the driest quarter is 27.0 mm. The precipitation of the warmest quarter is 139.0 mm. The precipitation of the coldest quarter is 31.0 mm. What is the probability of the species Streptopelia decipiens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15234248_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0516", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.465658 and latitude -0.693972 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. What is the probability of the species Scopus umbretta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436290_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0518", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.758317 and latitude -3.569227 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. What is the probability of the species Dinemellia dinemelli occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12511852_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0519", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298536 and latitude -0.666360 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. What is the probability of the species Nectarinia tacazze occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15283938_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0520", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125347 and latitude -0.311612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Cossypha caffra occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21097299_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0521", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952315 and latitude 0.009791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Corythaixoides leucogaster occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925707_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0522", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298562 and latitude -0.665901 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. What is the probability of the species Laniarius major occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15145101_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0523", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.187452 and latitude -0.499206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284271_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0524", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.396730 and latitude -0.803697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Cossypha heuglini occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12596376_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0526", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111946 and latitude -0.402734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20726818_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0529", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988431 and latitude -0.219000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Nectarinia kilimensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119851_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0530", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444690 and latitude -0.716908 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Corvus albus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15474902_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0531", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.577802 and latitude 0.334909 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. What is the probability of the species Spilopelia senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5120073_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0533", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.616972 and latitude -0.559458 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Cinnyris mediocris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15208954_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0534", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.400280 and latitude -0.772281 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Haliaeetus vocifer occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17539501_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0535", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.113925 and latitude -0.438052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819665_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0536", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.333855 and latitude -0.830245 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Granatina ianthinogaster occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3754839_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0538", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108072 and latitude -0.309220 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Platalea alba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304151_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0539", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.919813 and latitude 2.097865 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.41 degrees. The mean diurnal range is 10.92 degrees. The isothermality is 80.29. The temperature seasonality (100 times the standard deviation) is 79.33. The max temperature of the warmest month is 27.37 degrees. The min temperature of the coldest month is 13.77 degrees. The temperature annual range is 13.60 degrees. The mean temperature of the wettest quarter is 21.29 degrees. The mean temperature of the driest quarter is 19.51 degrees. The mean temperature of the warmest quarter is 21.46 degrees. The mean temperature of the coldest quarter is 19.45 degrees. The annual precipitation is 473.0 mm. The precipitation of the wettest month is 106.0 mm. The precipitation of the driest month is 9.0 mm. The precipitation seasonality (coefficient of variation) is 70.90. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 51.0 mm. The precipitation of the warmest quarter is 178.0 mm. The precipitation of the coldest quarter is 58.0 mm. What is the probability of the species Dicrurus adsimilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3633236_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0540", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.354062 and latitude -0.563343 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22693049_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0543", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.798427 and latitude -3.808263 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. What is the probability of the species Turtur chalcospilos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7049464_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0545", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450879 and latitude -0.739549 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Numida meleagris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21073073_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0546", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.656872 and latitude -0.297796 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. What is the probability of the species Crithagra citrinelloides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20348961_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0547", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285811 and latitude 0.491439 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4272139_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0550", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428400 and latitude -0.725289 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025953_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0553", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.720935 and latitude -2.257880 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.40 degrees. The mean diurnal range is 11.22 degrees. The isothermality is 69.37. The temperature seasonality (100 times the standard deviation) is 144.94. The max temperature of the warmest month is 30.83 degrees. The min temperature of the coldest month is 14.66 degrees. The temperature annual range is 16.17 degrees. The mean temperature of the wettest quarter is 22.92 degrees. The mean temperature of the driest quarter is 20.33 degrees. The mean temperature of the warmest quarter is 23.99 degrees. The mean temperature of the coldest quarter is 20.33 degrees. The annual precipitation is 604.0 mm. The precipitation of the wettest month is 165.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 104.51. The precipitation of the wettest quarter is 316.0 mm. The precipitation of the driest quarter is 7.0 mm. The precipitation of the warmest quarter is 217.0 mm. The precipitation of the coldest quarter is 7.0 mm. What is the probability of the species Turtur chalcospilos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7302297_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0555", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.085625 and latitude -0.315834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Lophaetus occipitalis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6610312_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0557", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952508 and latitude 0.009905 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Ploceus vitellinus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925726_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0562", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285800 and latitude 0.491500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Balearica regulorum occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9205333_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0563", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.582116 and latitude 0.349416 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. What is the probability of the species Streptopelia capicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10223384_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0565", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.903004 and latitude -3.083243 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.19 degrees. The mean diurnal range is 7.97 degrees. The isothermality is 67.30. The temperature seasonality (100 times the standard deviation) is 123.33. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 19.64 degrees. The temperature annual range is 11.84 degrees. The mean temperature of the wettest quarter is 25.21 degrees. The mean temperature of the driest quarter is 26.43 degrees. The mean temperature of the warmest quarter is 26.64 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 884.0 mm. The precipitation of the wettest month is 187.0 mm. The precipitation of the driest month is 12.0 mm. The precipitation seasonality (coefficient of variation) is 61.39. The precipitation of the wettest quarter is 385.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 183.0 mm. The precipitation of the coldest quarter is 188.0 mm. What is the probability of the species Kaupifalco monogrammicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18990924_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0568", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432900 and latitude -0.714300 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Cisticola chiniana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10608444_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0569", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492268 and latitude -0.572895 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Euplectes progne occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10494075_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0570", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.291267 and latitude 0.498667 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Lanius humeralis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7716763_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0571", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469527 and latitude -0.596445 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Anas undulata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258662_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0572", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.781843 and latitude -3.596470 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. What is the probability of the species Turtur chalcospilos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12531865_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0573", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.060133 and latitude -0.354307 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Cecropis senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864288_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0574", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.114387 and latitude -0.286709 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Corvus albus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526025_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0575", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.091990 and latitude 0.537357 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.14 degrees. The mean diurnal range is 12.73 degrees. The isothermality is 82.07. The temperature seasonality (100 times the standard deviation) is 79.15. The max temperature of the warmest month is 26.58 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.51 degrees. The mean temperature of the wettest quarter is 17.14 degrees. The mean temperature of the driest quarter is 18.58 degrees. The mean temperature of the warmest quarter is 19.14 degrees. The mean temperature of the coldest quarter is 17.14 degrees. The annual precipitation is 1225.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 52.85. The precipitation of the wettest quarter is 491.0 mm. The precipitation of the driest quarter is 121.0 mm. The precipitation of the warmest quarter is 264.0 mm. The precipitation of the coldest quarter is 491.0 mm. What is the probability of the species Cisticola cantans occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15874060_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0576", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308579 and latitude -0.145117 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. What is the probability of the species Thalassornis leuconotus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19266793_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0577", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474706 and latitude -0.554303 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Crithagra striolata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21213112_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0579", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.106168 and latitude -0.403316 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Tringa stagnatilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4122705_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0582", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401900 and latitude -0.767200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Megaceryle maxima occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10561143_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0583", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129222 and latitude -0.304008 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Cisticola chiniana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11887905_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0584", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.693575 and latitude -4.047847 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Notopholia corusca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13608231_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0586", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.034991 and latitude -0.269870 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Nectarinia famosa occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5533753_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0587", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263924 and latitude -0.821967 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Pelecanus onocrotalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756371_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0588", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425708 and latitude -0.720986 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lamprotornis superbus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20832213_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0589", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108066 and latitude -0.306113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Lanius excubitoroides occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5517500_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0595", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.419316 and latitude 0.685222 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.22 degrees. The mean diurnal range is 12.17 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.56. The max temperature of the warmest month is 29.24 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 14.75 degrees. The mean temperature of the wettest quarter is 21.12 degrees. The mean temperature of the driest quarter is 21.89 degrees. The mean temperature of the warmest quarter is 22.17 degrees. The mean temperature of the coldest quarter is 20.41 degrees. The annual precipitation is 1520.0 mm. The precipitation of the wettest month is 234.0 mm. The precipitation of the driest month is 52.0 mm. The precipitation seasonality (coefficient of variation) is 42.70. The precipitation of the wettest quarter is 580.0 mm. The precipitation of the driest quarter is 190.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 365.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15752435_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0601", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.733470 and latitude -3.989965 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Terpsiphone viridis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12524048_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0602", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.282690 and latitude -0.734770 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Cisticola marginatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700360_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0603", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418351 and latitude -0.720677 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Gelochelidon nilotica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22239295_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0605", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411910 and latitude -0.763410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Recurvirostra avosetta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4929439_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0606", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090260 and latitude -0.356779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Asio capensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L920937_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0607", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.822843 and latitude -3.824118 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. What is the probability of the species Cossypha heuglini occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259752_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0610", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.122811 and latitude -0.414418 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Camaroptera brachyura occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20161142_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0613", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306596 and latitude -0.885051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. What is the probability of the species Passer gongonensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L989976_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0618", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.712955 and latitude -3.948034 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Turtur chalcospilos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11436924_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0619", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116630 and latitude -0.410553 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Calidris pugnax occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819859_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0620", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.571038 and latitude -0.607497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12629846_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0622", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491776 and latitude -0.573038 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Gallinago nigripennis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9240465_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0623", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.119614 and latitude -0.371656 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Phoenicopterus roseus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2853940_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0624", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.109042 and latitude 0.388282 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.43 degrees. The mean diurnal range is 10.72 degrees. The isothermality is 73.81. The temperature seasonality (100 times the standard deviation) is 117.59. The max temperature of the warmest month is 36.23 degrees. The min temperature of the coldest month is 21.71 degrees. The temperature annual range is 14.53 degrees. The mean temperature of the wettest quarter is 28.48 degrees. The mean temperature of the driest quarter is 26.91 degrees. The mean temperature of the warmest quarter is 29.90 degrees. The mean temperature of the coldest quarter is 26.91 degrees. The annual precipitation is 337.0 mm. The precipitation of the wettest month is 98.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 107.78. The precipitation of the wettest quarter is 155.0 mm. The precipitation of the driest quarter is 14.0 mm. The precipitation of the warmest quarter is 132.0 mm. The precipitation of the coldest quarter is 14.0 mm. What is the probability of the species Tockus erythrorhynchus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22298211_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0625", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606123 and latitude -2.982345 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Halcyon leucocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12053795_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0629", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.531521 and latitude -0.551474 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11329676_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0632", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.118175 and latitude -0.414585 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Spilopelia senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025784_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0633", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262168 and latitude -0.444845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Campephaga flava occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5135004_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0636", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.241899 and latitude -0.404983 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Numida meleagris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10006012_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0637", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.848792 and latitude -1.405414 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.05 degrees. The mean diurnal range is 10.94 degrees. The isothermality is 72.39. The temperature seasonality (100 times the standard deviation) is 124.71. The max temperature of the warmest month is 29.91 degrees. The min temperature of the coldest month is 14.80 degrees. The temperature annual range is 15.11 degrees. The mean temperature of the wettest quarter is 22.51 degrees. The mean temperature of the driest quarter is 20.24 degrees. The mean temperature of the warmest quarter is 23.37 degrees. The mean temperature of the coldest quarter is 20.24 degrees. The annual precipitation is 782.0 mm. The precipitation of the wettest month is 239.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 111.95. The precipitation of the wettest quarter is 424.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 275.0 mm. The precipitation of the coldest quarter is 11.0 mm. What is the probability of the species Hirundo rustica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120035_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0638", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486263 and latitude -0.610771 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Streptopelia lugens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347943_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0639", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946107 and latitude -0.246093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Clanga pomarina occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462528_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0640", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.365745 and latitude -0.856539 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. What is the probability of the species Campethera nubica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925745_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0641", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.605857 and latitude -2.979885 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Euplectes orix occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12079977_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0644", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116701 and latitude -0.410734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Monticola saxatilis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17114258_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0646", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.082220 and latitude -0.308115 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Polemaetus bellicosus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16475457_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0650", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.378136 and latitude -0.823002 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Laniarius major occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19744907_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0651", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537733 and latitude -0.547081 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Cinnyris venustus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11361405_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0652", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.103821 and latitude -0.308474 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Himantopus himantopus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864256_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0653", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.603577 and latitude -2.963005 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Campethera nubica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12031498_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0655", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.578382 and latitude -0.608027 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Hirundo rustica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12921572_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0658", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474390 and latitude -0.561497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Saxicola torquatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16228704_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0661", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337650 and latitude -2.249473 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. What is the probability of the species Circus macrourus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22572263_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0664", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.383973 and latitude -0.817318 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Vanellus coronatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15039930_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0666", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.636223 and latitude -0.502958 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Apus affinis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10716936_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0667", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.067732 and latitude -0.268997 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Spilopelia senegalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930250_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0668", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.338767 and latitude 0.158103 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.22 degrees. The mean diurnal range is 11.34 degrees. The isothermality is 81.65. The temperature seasonality (100 times the standard deviation) is 72.62. The max temperature of the warmest month is 22.82 degrees. The min temperature of the coldest month is 8.93 degrees. The temperature annual range is 13.88 degrees. The mean temperature of the wettest quarter is 14.26 degrees. The mean temperature of the driest quarter is 15.69 degrees. The mean temperature of the warmest quarter is 16.10 degrees. The mean temperature of the coldest quarter is 14.26 degrees. The annual precipitation is 1326.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 47.26. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 307.0 mm. The precipitation of the coldest quarter is 486.0 mm. What is the probability of the species Tauraco hartlaubi occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8137654_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0669", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.110792 and latitude -0.561781 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. What is the probability of the species Prinia subflava occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10902833_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0670", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490550 and latitude -0.589737 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Platalea alba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9954043_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0671", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.351700 and latitude -0.771080 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Coracias garrulus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1195069_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0674", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063427 and latitude -0.325958 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Spatula querquedula occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6680855_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0678", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.590325 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Turdus abyssinicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11353714_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0682", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.955154 and latitude 0.455048 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.43 degrees. The mean diurnal range is 14.77 degrees. The isothermality is 82.21. The temperature seasonality (100 times the standard deviation) is 64.30. The max temperature of the warmest month is 27.63 degrees. The min temperature of the coldest month is 9.67 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 19.26 degrees. The mean temperature of the driest quarter is 18.32 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.75 degrees. The annual precipitation is 812.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 65.48. The precipitation of the wettest quarter is 345.0 mm. The precipitation of the driest quarter is 90.0 mm. The precipitation of the warmest quarter is 345.0 mm. The precipitation of the coldest quarter is 146.0 mm. What is the probability of the species Anaplectes rubriceps occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5276557_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0684", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610410 and latitude -2.982675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Cinnyris mariquensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12021597_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0688", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.485187 and latitude -0.652962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Mirafra africana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734170_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0690", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493109 and latitude -0.570587 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Ardea melanocephala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11117640_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0692", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450859 and latitude -0.731743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Lagonosticta senegala occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17069045_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0695", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334420 and latitude -0.828872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ardea purpurea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8838554_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0697", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.094788 and latitude -0.325321 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Nilaus afer occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22896641_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0698", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321090 and latitude -0.668276 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Apus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298525_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0700", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431027 and latitude -0.717178 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Oena capensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15684869_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0704", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.647223 and latitude -0.293334 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. What is the probability of the species Ploceus baglafecht occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1437096_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0705", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260674 and latitude -0.442675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Recurvirostra avosetta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10658952_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0710", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433431 and latitude -0.723262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Pycnonotus barbatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17801432_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0711", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560245 and latitude -0.553263 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Crithagra sulphurata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11379808_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0713", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.316827 and latitude -0.700020 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Chloropicus spodocephalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17115991_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0717", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.691930 and latitude -3.990577 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Ciconia microscelis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3267612_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0718", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.078463 and latitude -0.573668 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. What is the probability of the species Egretta garzetta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3989563_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0722", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.611015 and latitude -2.982577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Cinnyris venustus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12023045_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0723", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267712 and latitude -0.814428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6714321_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0726", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570261 and latitude -0.606583 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Passer rufocinctus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10075852_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0727", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.327839 and latitude -0.744303 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Alopochen aegyptiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1219423_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0728", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308656 and latitude -0.816523 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Apus melba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1917524_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0729", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.325463 and latitude -0.891143 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.34 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 81.52. The temperature seasonality (100 times the standard deviation) is 63.49. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 15.11 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.63 degrees. The mean temperature of the driest quarter is 21.47 degrees. The mean temperature of the warmest quarter is 23.09 degrees. The mean temperature of the coldest quarter is 21.47 degrees. The annual precipitation is 1140.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 53.60. The precipitation of the wettest quarter is 480.0 mm. The precipitation of the driest quarter is 138.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 138.0 mm. What is the probability of the species Tchagra senegalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9097664_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0730", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.277757 and latitude -0.813519 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Eminia lepida occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1027936_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0731", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326310 and latitude -0.717697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Anas undulata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11413533_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0732", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.845929 and latitude 1.034954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. What is the probability of the species Dryoscopus gambensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279837_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0737", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.455446 and latitude -0.735221 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Cossypha caffra occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16279479_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0741", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612130 and latitude -2.985147 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Chloropicus spodocephalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12125053_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0742", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451718 and latitude -0.739879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ardea cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614369_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0743", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120250 and latitude -0.376524 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Calidris minuta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17860014_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0744", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.245980 and latitude -0.410204 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Malaconotus blanchoti occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151885_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0746", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.135895 and latitude -0.613163 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. What is the probability of the species Passer griseus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2101438_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0747", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.375432 and latitude -0.662052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Sagittarius serpentarius occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298532_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0748", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610720 and latitude -2.980845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Bubulcus ibis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12069484_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0752", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.803397 and latitude -3.847356 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Dryoscopus cubla occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16591200_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0753", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267000 and latitude -0.391000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Threskiornis aethiopicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9656777_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0754", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063727 and latitude 0.728790 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. What is the probability of the species Streptopelia decipiens occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13539972_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0756", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.864672 and latitude -1.666409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. What is the probability of the species Ortygornis sephaena occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6150442_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0757", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328739 and latitude -0.809682 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Egretta garzetta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974532_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0758", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.913344 and latitude 0.063140 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.97 degrees. The mean diurnal range is 11.67 degrees. The isothermality is 81.23. The temperature seasonality (100 times the standard deviation) is 72.48. The max temperature of the warmest month is 26.50 degrees. The min temperature of the coldest month is 12.14 degrees. The temperature annual range is 14.36 degrees. The mean temperature of the wettest quarter is 19.37 degrees. The mean temperature of the driest quarter is 19.54 degrees. The mean temperature of the warmest quarter is 19.80 degrees. The mean temperature of the coldest quarter is 18.05 degrees. The annual precipitation is 1927.0 mm. The precipitation of the wettest month is 277.0 mm. The precipitation of the driest month is 77.0 mm. The precipitation seasonality (coefficient of variation) is 36.56. The precipitation of the wettest quarter is 686.0 mm. The precipitation of the driest quarter is 279.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 505.0 mm. What is the probability of the species Atimastillas flavicollis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9160408_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0759", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.965087 and latitude -0.002546 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Crithagra sulphurata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8291945_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0762", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.243000 and latitude -0.436900 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Uraeginthus bengalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10598574_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0764", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.224466 and latitude -0.451912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Nilaus afer occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16985203_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0765", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.284696 and latitude 0.521274 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. What is the probability of the species Crithagra striolata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290833_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0766", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.283195 and latitude -0.716460 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Numida meleagris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14798664_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0769", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610542 and latitude -2.982743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Creatophora cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12045024_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0770", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437874 and latitude -0.712376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Buphagus erythrorynchus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279452_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0771", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420519 and latitude -0.775280 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ploceus ocularis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284261_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0772", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435263 and latitude -0.717722 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Myrmecocichla aethiops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11682534_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0776", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125236 and latitude -0.361688 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Himantopus himantopus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5255397_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0778", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570869 and latitude -0.572879 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Actitis hypoleucos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294587_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0779", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442682 and latitude -0.721603 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Actitis hypoleucos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10176494_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0780", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.303336 and latitude -0.676259 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Campethera nubica occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11202841_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0781", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117479 and latitude -0.478450 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Phoeniculus purpureus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6301196_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0783", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.068058 and latitude -0.390541 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Vanellus armatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6687369_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0785", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425371 and latitude -0.720112 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Microcarbo africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930747_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0786", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.060538 and latitude -1.357928 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.64 degrees. The mean diurnal range is 12.06 degrees. The isothermality is 72.91. The temperature seasonality (100 times the standard deviation) is 127.40. The max temperature of the warmest month is 28.49 degrees. The min temperature of the coldest month is 11.95 degrees. The temperature annual range is 16.54 degrees. The mean temperature of the wettest quarter is 20.60 degrees. The mean temperature of the driest quarter is 18.10 degrees. The mean temperature of the warmest quarter is 21.05 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 636.0 mm. The precipitation of the wettest month is 139.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 85.66. The precipitation of the wettest quarter is 289.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 23.0 mm. What is the probability of the species Platalea alba occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16196959_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0792", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.324620 and latitude -0.517466 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. What is the probability of the species Riparia paludicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1874608_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0793", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.247270 and latitude -0.411410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Urocolius macrourus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6201096_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0795", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.239173 and latitude -0.403064 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Streptopelia capicola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10076522_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0796", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.223909 and latitude -0.457088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Ardea intermedia occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237255_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0798", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.151949 and latitude -0.421988 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Phoenicopterus roseus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10031354_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0799", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.110418 and latitude -0.307472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Threskiornis aethiopicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9863251_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0801", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.692246 and latitude -3.047183 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.87 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 68.99. The temperature seasonality (100 times the standard deviation) is 163.68. The max temperature of the warmest month is 31.18 degrees. The min temperature of the coldest month is 13.94 degrees. The temperature annual range is 17.23 degrees. The mean temperature of the wettest quarter is 22.60 degrees. The mean temperature of the driest quarter is 19.66 degrees. The mean temperature of the warmest quarter is 23.71 degrees. The mean temperature of the coldest quarter is 19.66 degrees. The annual precipitation is 781.0 mm. The precipitation of the wettest month is 196.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 89.27. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 32.0 mm. The precipitation of the warmest quarter is 204.0 mm. The precipitation of the coldest quarter is 32.0 mm. What is the probability of the species Tockus erythrorhynchus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12038122_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0803", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.335490 and latitude -2.241674 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. What is the probability of the species Vanellus coronatus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13301310_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0804", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718151 and latitude -4.017357 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Cossypha natalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070641_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0805", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.384507 and latitude -0.818119 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Creatophora cinerea occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756373_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0808", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.632589 and latitude -1.412630 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.42 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 72.41. The temperature seasonality (100 times the standard deviation) is 126.48. The max temperature of the warmest month is 29.39 degrees. The min temperature of the coldest month is 14.02 degrees. The temperature annual range is 15.37 degrees. The mean temperature of the wettest quarter is 21.91 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.57 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 204.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 105.97. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 270.0 mm. The precipitation of the coldest quarter is 10.0 mm. What is the probability of the species Apalis flavida occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10056690_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0809", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612393 and latitude -2.983073 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Micronisus gabar occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12071643_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0811", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262007 and latitude -0.782408 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Chalcomitra amethystina occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279523_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0812", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.579637 and latitude 0.338600 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. What is the probability of the species Brunhilda charmosyna occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638669_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0813", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.302593 and latitude -0.722962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Tringa glareola occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964191_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0815", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.716266 and latitude -0.454711 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. What is the probability of the species Cisticola aberdare occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2688861_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0816", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469995 and latitude -0.552480 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Passer rufocinctus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6428377_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0817", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.614320 and latitude -2.983500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Luscinia megarhynchos occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12018725_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0819", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.020203 and latitude -0.078163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. What is the probability of the species Vanellus crassirostris occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8219781_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0820", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240913 and latitude -0.404855 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9996816_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0821", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087149 and latitude -0.265111 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Plegadis falcinellus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10051579_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0822", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.721884 and latitude -4.029045 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. What is the probability of the species Egretta ardesiaca occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10691981_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0823", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120769 and latitude -0.400954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. What is the probability of the species Lamprotornis purpuroptera occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14106163_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0825", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426588 and latitude -0.759612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Motacilla aguimp occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10819022_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0826", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285334 and latitude 0.501972 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. What is the probability of the species Accipiter melanoleucus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7695066_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0827", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420754 and latitude -0.776724 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ceryle rudis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4377528_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0829", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988534 and latitude -0.219421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119968_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0830", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.601350 and latitude -2.950138 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Coracias naevius occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060066_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0835", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.130841 and latitude -0.310531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Egretta garzetta occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18147093_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0836", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.786000 and latitude -3.908000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. What is the probability of the species Thalasseus bengalensis occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4561068_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0837", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.248771 and latitude -0.434102 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Vanellus spinosus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3846997_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0840", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249894 and latitude -0.433598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Buphagus africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4235132_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0846", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432161 and latitude -0.742143 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Ketupa lacteus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298492_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0848", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432933 and latitude -0.745042 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Microcarbo africanus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5287529_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0853", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088687 and latitude -0.312322 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Pelecanus onocrotalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4074487_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0854", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451435 and latitude -0.740282 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Camaroptera brachyura occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19693144_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0855", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391852 and latitude -0.810876 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Accipiter minullus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3645588_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0861", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.308395 and latitude 0.472096 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. What is the probability of the species Bostrychia hagedash occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17886635_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0863", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.775877 and latitude 0.935621 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.53 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 82.89. The temperature seasonality (100 times the standard deviation) is 75.43. The max temperature of the warmest month is 26.48 degrees. The min temperature of the coldest month is 8.92 degrees. The temperature annual range is 17.57 degrees. The mean temperature of the wettest quarter is 18.61 degrees. The mean temperature of the driest quarter is 17.45 degrees. The mean temperature of the warmest quarter is 18.61 degrees. The mean temperature of the coldest quarter is 16.72 degrees. The annual precipitation is 660.0 mm. The precipitation of the wettest month is 119.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 52.81. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 80.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 144.0 mm. What is the probability of the species Phylloscopus trochilus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17875037_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0864", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424516 and latitude -0.641202 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Crithagra reichenowi occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6833748_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0867", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.210594 and latitude -0.408207 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Oenanthe oenanthe occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284269_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0868", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.415048 and latitude -0.770567 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Nycticorax nycticorax occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207400_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0876", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308164 and latitude -0.721051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Chrysococcyx klaas occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9956046_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0878", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452555 and latitude -0.745897 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Upupa epops occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14739048_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0879", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606940 and latitude -2.983382 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Aquila spilogaster occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12085520_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0880", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437895 and latitude -0.727570 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. What is the probability of the species Butorides striata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17974825_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0882", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321595 and latitude -0.666745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. What is the probability of the species Streptopelia semitorquata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22689728_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0885", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.789798 and latitude -3.798998 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. What is the probability of the species Chalcomitra amethystina occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4022409_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0886", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059912 and latitude -0.317391 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. What is the probability of the species Threskiornis aethiopicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7833802_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0889", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.536243 and latitude -0.548666 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. What is the probability of the species Threskiornis aethiopicus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964149_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0891", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.468400 and latitude -0.596197 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Fulica cristata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11118238_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0893", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612265 and latitude -2.983033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. What is the probability of the species Vidua chalybeata occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12135116_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0894", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249964 and latitude -0.432776 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. What is the probability of the species Pelecanus onocrotalus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12667927_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0897", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.618337 and latitude -0.963265 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.81 degrees. The mean diurnal range is 11.52 degrees. The isothermality is 75.52. The temperature seasonality (100 times the standard deviation) is 113.42. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 14.71 degrees. The temperature annual range is 15.26 degrees. The mean temperature of the wettest quarter is 22.28 degrees. The mean temperature of the driest quarter is 20.19 degrees. The mean temperature of the warmest quarter is 22.99 degrees. The mean temperature of the coldest quarter is 20.19 degrees. The annual precipitation is 777.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 104.94. The precipitation of the wettest quarter is 357.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 305.0 mm. The precipitation of the coldest quarter is 13.0 mm. What is the probability of the species Telophorus sulfureopectus occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14860959_visual.jpg" + ] + }, + { + "Question_id": "Species occurrence probability estimation/0898", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456055 and latitude -0.569332 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. What is the probability of the species Cisticola chiniana occurring in this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species occurrence probability estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) Unlikely to occur in this region", + "(B) 0-0.3", + "(C) 0.3-0.6", + "(D) 0.6-1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347994_visual.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_richness_estimation.json b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_richness_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..14c0157a26be23527eedda5e12c258f3d95bfefe --- /dev/null +++ b/jsons/Cross-sphere/Bird_species_prediction/Reasoning/Species_richness_estimation.json @@ -0,0 +1,18902 @@ +[ + { + "Question_id": "Species richness estimation/0000", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.216366 and latitude -0.418769 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 64", + "(C) 4", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791999_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0001", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.591984 and latitude -0.251026 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.80 degrees. The mean diurnal range is 11.81 degrees. The isothermality is 79.31. The temperature seasonality (100 times the standard deviation) is 73.89. The max temperature of the warmest month is 18.69 degrees. The min temperature of the coldest month is 3.80 degrees. The temperature annual range is 14.89 degrees. The mean temperature of the wettest quarter is 11.73 degrees. The mean temperature of the driest quarter is 10.85 degrees. The mean temperature of the warmest quarter is 11.73 degrees. The mean temperature of the coldest quarter is 9.91 degrees. The annual precipitation is 1282.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 37.0 mm. The precipitation seasonality (coefficient of variation) is 35.95. The precipitation of the wettest quarter is 424.0 mm. The precipitation of the driest quarter is 175.0 mm. The precipitation of the warmest quarter is 424.0 mm. The precipitation of the coldest quarter is 325.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 82", + "(B) 30", + "(C) 10", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264913_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0002", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724232 and latitude -0.477635 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 138", + "(C) 12", + "(D) 311", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10216638_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0003", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084390 and latitude -0.308472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 62", + "(C) 21", + "(D) 78", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8216888_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0004", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.734492 and latitude -3.991614 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 31", + "(C) 9", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16837097_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0005", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.112115 and latitude -0.510023 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 121", + "(B) 16", + "(C) 3", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19033567_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0006", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.392700 and latitude -0.635840 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 64", + "(B) 2", + "(C) 20", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120392_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0007", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.077993 and latitude -0.299696 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 138", + "(B) 173", + "(C) 60", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7852020_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0008", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375457 and latitude 0.607683 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 67", + "(C) 12", + "(D) 113", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15843032_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0009", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.525207 and latitude -0.617251 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 36", + "(C) 4", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294819_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0010", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.374544 and latitude 0.606404 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 95", + "(B) 6", + "(C) 44", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13962733_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0011", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.245280 and latitude 2.563797 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.31 degrees. The mean diurnal range is 14.24 degrees. The isothermality is 88.89. The temperature seasonality (100 times the standard deviation) is 62.26. The max temperature of the warmest month is 36.33 degrees. The min temperature of the coldest month is 20.31 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 29.02 degrees. The mean temperature of the driest quarter is 28.06 degrees. The mean temperature of the warmest quarter is 29.08 degrees. The mean temperature of the coldest quarter is 27.57 degrees. The annual precipitation is 246.0 mm. The precipitation of the wettest month is 56.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 70.66. The precipitation of the wettest quarter is 121.0 mm. The precipitation of the driest quarter is 28.0 mm. The precipitation of the warmest quarter is 92.0 mm. The precipitation of the coldest quarter is 40.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 102", + "(C) 83", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1317903_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0012", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.529492 and latitude -0.552789 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 112", + "(B) 45", + "(C) 134", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462312_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0013", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.280240 and latitude -0.456203 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 2", + "(C) 126", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290905_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0014", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.934569 and latitude 0.040166 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 271", + "(B) 256", + "(C) 61", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23281957_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0015", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.949176 and latitude -0.231627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 64", + "(B) 44", + "(C) 117", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20132459_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0016", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495022 and latitude -0.586243 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 87", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16218182_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0017", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.668869 and latitude -4.064917 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 139", + "(C) 266", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18133972_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0018", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.321445 and latitude -0.749309 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 249", + "(C) 204", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449320_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0019", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.609671 and latitude -0.515350 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 89", + "(C) 1", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18745097_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0020", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.272520 and latitude -0.827416 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 278", + "(B) 68", + "(C) 2", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467884_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0021", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.723547 and latitude -3.625617 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 8", + "(C) 82", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16057973_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0022", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429442 and latitude -0.703606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 49", + "(B) 8", + "(C) 126", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16189252_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0023", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429360 and latitude -0.703113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 62", + "(C) 53", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10284497_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0024", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309831 and latitude -0.707895 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 5", + "(C) 135", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12116683_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0025", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489479 and latitude -0.625293 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 6", + "(C) 98", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12955644_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0026", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.135577 and latitude -0.676287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 49", + "(C) 137", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10501648_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0027", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.866303 and latitude 1.071369 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 168", + "(C) 12", + "(D) 57", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9061441_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0028", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560670 and latitude -0.553776 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 19", + "(B) 63", + "(C) 53", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21033789_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0029", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309482 and latitude -0.143795 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 50", + "(C) 98", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214628_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0030", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.336645 and latitude -0.649582 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 102", + "(B) 11", + "(C) 35", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16553147_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0031", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.813115 and latitude -0.299148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.62 degrees. The mean diurnal range is 12.85 degrees. The isothermality is 82.28. The temperature seasonality (100 times the standard deviation) is 66.45. The max temperature of the warmest month is 23.10 degrees. The min temperature of the coldest month is 7.49 degrees. The temperature annual range is 15.61 degrees. The mean temperature of the wettest quarter is 14.87 degrees. The mean temperature of the driest quarter is 14.98 degrees. The mean temperature of the warmest quarter is 15.47 degrees. The mean temperature of the coldest quarter is 13.79 degrees. The annual precipitation is 1119.0 mm. The precipitation of the wettest month is 167.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 44.48. The precipitation of the wettest quarter is 386.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 289.0 mm. The precipitation of the coldest quarter is 357.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 505", + "(C) 26", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16581772_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0032", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.506728 and latitude -0.565488 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 12", + "(C) 177", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16785945_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0033", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.226784 and latitude -0.482796 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 54", + "(C) 88", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020900_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0034", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.053010 and latitude -0.427459 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 102", + "(B) 12", + "(C) 60", + "(D) 129", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22969685_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0035", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369008 and latitude -0.852497 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 44", + "(C) 72", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20971407_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0036", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.637739 and latitude -0.483904 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 27", + "(C) 89", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4154933_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0037", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.679613 and latitude -4.062863 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 99", + "(C) 4", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9419646_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0038", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.472359 and latitude -0.627016 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 10", + "(C) 171", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15073030_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0039", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.520126 and latitude -0.558900 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 185", + "(C) 72", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17683552_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0040", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.445448 and latitude -0.713535 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 134", + "(C) 49", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17578070_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0041", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.704891 and latitude -0.448206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.31 degrees. The mean diurnal range is 11.79 degrees. The isothermality is 81.32. The temperature seasonality (100 times the standard deviation) is 71.36. The max temperature of the warmest month is 20.27 degrees. The min temperature of the coldest month is 5.77 degrees. The temperature annual range is 14.50 degrees. The mean temperature of the wettest quarter is 11.42 degrees. The mean temperature of the driest quarter is 12.71 degrees. The mean temperature of the warmest quarter is 13.20 degrees. The mean temperature of the coldest quarter is 11.42 degrees. The annual precipitation is 1210.0 mm. The precipitation of the wettest month is 174.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 42.21. The precipitation of the wettest quarter is 408.0 mm. The precipitation of the driest quarter is 157.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 408.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 146", + "(C) 96", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16285046_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0042", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.073127 and latitude -0.304779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 107", + "(B) 10", + "(C) 53", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8664033_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0043", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.139337 and latitude -0.676059 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.19 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 80.44. The temperature seasonality (100 times the standard deviation) is 81.11. The max temperature of the warmest month is 26.37 degrees. The min temperature of the coldest month is 10.96 degrees. The temperature annual range is 15.41 degrees. The mean temperature of the wettest quarter is 18.70 degrees. The mean temperature of the driest quarter is 18.94 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.22 degrees. The annual precipitation is 1477.0 mm. The precipitation of the wettest month is 220.0 mm. The precipitation of the driest month is 79.0 mm. The precipitation seasonality (coefficient of variation) is 31.91. The precipitation of the wettest quarter is 534.0 mm. The precipitation of the driest quarter is 291.0 mm. The precipitation of the warmest quarter is 328.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 49", + "(C) 3", + "(D) 117", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5159521_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0044", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.662399 and latitude -3.024547 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 117", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18000924_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0045", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.507893 and latitude -0.564606 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 21", + "(C) 56", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462333_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0046", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.560444 and latitude 0.293821 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 150", + "(B) 67", + "(C) 33", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12826528_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0047", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.530309 and latitude -0.553023 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 61", + "(C) 50", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22174073_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0048", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.740358 and latitude -3.986573 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 6", + "(C) 266", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22033151_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0049", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.068174 and latitude -3.745175 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.10 degrees. The mean diurnal range is 9.47 degrees. The isothermality is 67.84. The temperature seasonality (100 times the standard deviation) is 147.05. The max temperature of the warmest month is 31.33 degrees. The min temperature of the coldest month is 17.38 degrees. The temperature annual range is 13.95 degrees. The mean temperature of the wettest quarter is 24.55 degrees. The mean temperature of the driest quarter is 22.25 degrees. The mean temperature of the warmest quarter is 25.70 degrees. The mean temperature of the coldest quarter is 22.21 degrees. The annual precipitation is 704.0 mm. The precipitation of the wettest month is 105.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 49.88. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 100.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 3", + "(C) 159", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17070362_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0050", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375622 and latitude 0.607860 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 8", + "(C) 43", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498960_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0051", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.516404 and latitude -0.621530 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 100", + "(C) 8", + "(D) 138", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15773403_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0052", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419660 and latitude -0.693710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 79", + "(C) 12", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235554_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0053", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116420 and latitude -0.209350 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 58", + "(B) 123", + "(C) 117", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076102_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0054", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.012428 and latitude -3.712565 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.10 degrees. The mean diurnal range is 9.47 degrees. The isothermality is 67.84. The temperature seasonality (100 times the standard deviation) is 147.05. The max temperature of the warmest month is 31.33 degrees. The min temperature of the coldest month is 17.38 degrees. The temperature annual range is 13.95 degrees. The mean temperature of the wettest quarter is 24.55 degrees. The mean temperature of the driest quarter is 22.25 degrees. The mean temperature of the warmest quarter is 25.70 degrees. The mean temperature of the coldest quarter is 22.21 degrees. The annual precipitation is 704.0 mm. The precipitation of the wettest month is 105.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 49.88. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 100.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 90", + "(C) 10", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17434837_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0055", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221035 and latitude -0.483580 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 11", + "(C) 33", + "(D) 63", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020897_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0056", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471970 and latitude -0.829753 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 46", + "(B) 107", + "(C) 7", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10348524_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0057", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572807 and latitude -0.608167 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 46", + "(B) 11", + "(C) 54", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12544941_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0058", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456695 and latitude -0.735810 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 8", + "(C) 256", + "(D) 100", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17688211_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0059", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.409981 and latitude -0.688443 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 138", + "(C) 3", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21100134_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0060", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368079 and latitude -0.486409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 19", + "(B) 49", + "(C) 58", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21193393_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0061", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.182879 and latitude -1.486376 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 59", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16920068_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0062", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308691 and latitude -0.144970 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 9", + "(C) 65", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689355_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0063", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.368525 and latitude -0.850262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 85", + "(C) 87", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8467384_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0064", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308605 and latitude -0.143869 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 1", + "(C) 10", + "(D) 58", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9083281_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0065", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306360 and latitude -0.886671 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 19", + "(B) 55", + "(C) 90", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9772879_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0066", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.475232 and latitude -0.626622 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 270", + "(C) 99", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294840_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0067", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.563548 and latitude -0.562090 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 71", + "(B) 105", + "(C) 60", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6253157_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0068", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419903 and latitude -0.693012 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 153", + "(C) 3", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284267_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0069", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.319829 and latitude -0.895510 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 376", + "(B) 26", + "(C) 271", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674637_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0070", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663894 and latitude -0.524886 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 5", + "(C) 69", + "(D) 207", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106454_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0071", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117296 and latitude -0.315254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 19", + "(C) 112", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16745560_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0072", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435363 and latitude -0.759531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 46", + "(C) 1", + "(D) 58", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21141544_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0073", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.422322 and latitude -0.769772 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 1", + "(C) 114", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16775941_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0074", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.602851 and latitude -4.022932 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 78", + "(C) 7", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5398395_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0075", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.088557 and latitude 1.765971 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.29 degrees. The mean diurnal range is 11.01 degrees. The isothermality is 73.01. The temperature seasonality (100 times the standard deviation) is 112.08. The max temperature of the warmest month is 36.63 degrees. The min temperature of the coldest month is 21.55 degrees. The temperature annual range is 15.08 degrees. The mean temperature of the wettest quarter is 29.15 degrees. The mean temperature of the driest quarter is 27.01 degrees. The mean temperature of the warmest quarter is 29.79 degrees. The mean temperature of the coldest quarter is 27.01 degrees. The annual precipitation is 344.0 mm. The precipitation of the wettest month is 102.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 105.81. The precipitation of the wettest quarter is 172.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 52.0 mm. The precipitation of the coldest quarter is 8.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 138", + "(B) 9", + "(C) 100", + "(D) 122", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12546876_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0076", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.259475 and latitude -0.810887 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 58", + "(C) 168", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294170_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0077", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564123 and latitude -0.561994 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 270", + "(C) 1", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264897_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0078", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.826378 and latitude -1.698618 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.23 degrees. The mean diurnal range is 12.21 degrees. The isothermality is 78.96. The temperature seasonality (100 times the standard deviation) is 100.59. The max temperature of the warmest month is 25.18 degrees. The min temperature of the coldest month is 9.72 degrees. The temperature annual range is 15.47 degrees. The mean temperature of the wettest quarter is 17.70 degrees. The mean temperature of the driest quarter is 16.14 degrees. The mean temperature of the warmest quarter is 18.23 degrees. The mean temperature of the coldest quarter is 15.83 degrees. The annual precipitation is 886.0 mm. The precipitation of the wettest month is 185.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 65.99. The precipitation of the wettest quarter is 402.0 mm. The precipitation of the driest quarter is 65.0 mm. The precipitation of the warmest quarter is 389.0 mm. The precipitation of the coldest quarter is 70.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 6", + "(C) 46", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19588647_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0079", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.123014 and latitude -0.392039 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 2", + "(C) 54", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21172815_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0080", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.529719 and latitude -2.547062 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 33", + "(B) 26", + "(C) 9", + "(D) 204", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7938762_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0081", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.679873 and latitude -0.523808 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.27 degrees. The mean diurnal range is 10.87 degrees. The isothermality is 78.19. The temperature seasonality (100 times the standard deviation) is 91.18. The max temperature of the warmest month is 18.77 degrees. The min temperature of the coldest month is 4.87 degrees. The temperature annual range is 13.90 degrees. The mean temperature of the wettest quarter is 12.17 degrees. The mean temperature of the driest quarter is 11.55 degrees. The mean temperature of the warmest quarter is 12.27 degrees. The mean temperature of the coldest quarter is 10.03 degrees. The annual precipitation is 1546.0 mm. The precipitation of the wettest month is 260.0 mm. The precipitation of the driest month is 53.0 mm. The precipitation seasonality (coefficient of variation) is 49.75. The precipitation of the wettest quarter is 618.0 mm. The precipitation of the driest quarter is 226.0 mm. The precipitation of the warmest quarter is 464.0 mm. The precipitation of the coldest quarter is 275.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 58", + "(B) 4", + "(C) 171", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21214949_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0082", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486100 and latitude -0.635759 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 8", + "(C) 152", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17772247_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0083", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718255 and latitude -4.018984 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 111", + "(C) 39", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6495825_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0084", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323675 and latitude -0.499642 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 26", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20336553_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0085", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250000 and latitude -0.433000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 28", + "(C) 150", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11222927_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0086", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.531022 and latitude -3.156209 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 376", + "(B) 55", + "(C) 19", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104171_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0087", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420049 and latitude -0.692290 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 47", + "(C) 96", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638675_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0088", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.566844 and latitude -0.541457 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 69", + "(C) 140", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21241794_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0089", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486637 and latitude -0.634412 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 2", + "(C) 168", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919920_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0090", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.729963 and latitude -0.481095 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 110", + "(B) 80", + "(C) 5", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283074_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0091", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.957191 and latitude -0.226942 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 42", + "(C) 134", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16110022_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0092", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.373469 and latitude 0.605834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 6", + "(C) 266", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874347_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0093", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.375773 and latitude -0.596951 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 24", + "(C) 42", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10343013_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0094", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.143364 and latitude -0.317675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 70", + "(C) 2", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20990360_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0095", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663925 and latitude -0.525000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 12", + "(C) 32", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952181_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0096", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117793 and latitude -0.311317 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 70", + "(C) 5", + "(D) 221", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214625_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0097", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.868821 and latitude -0.991104 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.10 degrees. The mean diurnal range is 12.02 degrees. The isothermality is 81.24. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 25.91 degrees. The min temperature of the coldest month is 11.12 degrees. The temperature annual range is 14.79 degrees. The mean temperature of the wettest quarter is 18.57 degrees. The mean temperature of the driest quarter is 17.21 degrees. The mean temperature of the warmest quarter is 19.06 degrees. The mean temperature of the coldest quarter is 17.17 degrees. The annual precipitation is 1634.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 81.0 mm. The precipitation seasonality (coefficient of variation) is 33.85. The precipitation of the wettest quarter is 594.0 mm. The precipitation of the driest quarter is 321.0 mm. The precipitation of the warmest quarter is 352.0 mm. The precipitation of the coldest quarter is 324.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 54", + "(C) 114", + "(D) 249", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16111596_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0098", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564186 and latitude -0.562208 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 311", + "(C) 1", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10057230_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0099", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.561898 and latitude -0.545246 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 111", + "(B) 10", + "(C) 138", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17600308_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0100", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492688 and latitude -0.574404 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 98", + "(C) 39", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6196854_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0101", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321573 and latitude -0.815879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 66", + "(C) 112", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2674368_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0102", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.134727 and latitude -3.283860 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.99 degrees. The mean diurnal range is 11.08 degrees. The isothermality is 68.93. The temperature seasonality (100 times the standard deviation) is 157.66. The max temperature of the warmest month is 30.57 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 16.08 degrees. The mean temperature of the wettest quarter is 22.82 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 23.75 degrees. The mean temperature of the coldest quarter is 19.88 degrees. The annual precipitation is 681.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 8.0 mm. The precipitation seasonality (coefficient of variation) is 86.43. The precipitation of the wettest quarter is 311.0 mm. The precipitation of the driest quarter is 28.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 28.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 153", + "(B) 6", + "(C) 1", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23139548_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0103", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.596143 and latitude -0.635631 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 132", + "(C) 1", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18748852_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0104", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.799840 and latitude -3.590762 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 41", + "(C) 30", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22761538_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0105", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.528470 and latitude -0.928910 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.66 degrees. The mean diurnal range is 12.70 degrees. The isothermality is 74.72. The temperature seasonality (100 times the standard deviation) is 128.32. The max temperature of the warmest month is 24.01 degrees. The min temperature of the coldest month is 7.01 degrees. The temperature annual range is 17.00 degrees. The mean temperature of the wettest quarter is 15.53 degrees. The mean temperature of the driest quarter is 13.00 degrees. The mean temperature of the warmest quarter is 15.98 degrees. The mean temperature of the coldest quarter is 12.82 degrees. The annual precipitation is 1201.0 mm. The precipitation of the wettest month is 254.0 mm. The precipitation of the driest month is 44.0 mm. The precipitation seasonality (coefficient of variation) is 65.40. The precipitation of the wettest quarter is 556.0 mm. The precipitation of the driest quarter is 139.0 mm. The precipitation of the warmest quarter is 423.0 mm. The precipitation of the coldest quarter is 152.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 5", + "(C) 49", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235556_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0106", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.160548 and latitude -1.041073 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.59 degrees. The mean diurnal range is 12.44 degrees. The isothermality is 82.37. The temperature seasonality (100 times the standard deviation) is 75.98. The max temperature of the warmest month is 26.40 degrees. The min temperature of the coldest month is 11.30 degrees. The temperature annual range is 15.10 degrees. The mean temperature of the wettest quarter is 19.15 degrees. The mean temperature of the driest quarter is 17.65 degrees. The mean temperature of the warmest quarter is 19.50 degrees. The mean temperature of the coldest quarter is 17.60 degrees. The annual precipitation is 1284.0 mm. The precipitation of the wettest month is 202.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 37.26. The precipitation of the wettest quarter is 473.0 mm. The precipitation of the driest quarter is 211.0 mm. The precipitation of the warmest quarter is 316.0 mm. The precipitation of the coldest quarter is 217.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 123", + "(C) 64", + "(D) 376", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17183115_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0107", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095495 and latitude -0.226743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 5", + "(C) 70", + "(D) 89", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17442753_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0108", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726778 and latitude -4.008682 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 89", + "(C) 505", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15592344_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0109", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.665287 and latitude -4.045377 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 2", + "(C) 38", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4669718_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0110", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129303 and latitude -0.423863 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 505", + "(B) 140", + "(C) 92", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6501085_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0111", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.867358 and latitude 3.140660 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.29 degrees. The mean diurnal range is 13.95 degrees. The isothermality is 89.71. The temperature seasonality (100 times the standard deviation) is 59.09. The max temperature of the warmest month is 37.04 degrees. The min temperature of the coldest month is 21.49 degrees. The temperature annual range is 15.55 degrees. The mean temperature of the wettest quarter is 29.87 degrees. The mean temperature of the driest quarter is 29.28 degrees. The mean temperature of the warmest quarter is 29.93 degrees. The mean temperature of the coldest quarter is 28.63 degrees. The annual precipitation is 221.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 71.28. The precipitation of the wettest quarter is 109.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 86.0 mm. The precipitation of the coldest quarter is 37.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 111", + "(B) 37", + "(C) 47", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14796653_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0112", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129259 and latitude -0.423819 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 51", + "(C) 259", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6498976_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0113", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.391011 and latitude 0.591302 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 270", + "(C) 75", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22761827_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0114", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.238076 and latitude -0.406703 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 95", + "(C) 55", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7023051_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0115", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.091412 and latitude -0.270824 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 278", + "(B) 2", + "(C) 177", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17518972_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0116", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.701800 and latitude -4.050448 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 139", + "(C) 83", + "(D) 505", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2125380_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0117", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420072 and latitude -0.692664 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 91", + "(C) 5", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3853026_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0118", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308716 and latitude -0.144961 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 107", + "(B) 89", + "(C) 171", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689305_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0119", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.598020 and latitude -4.035845 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 1", + "(C) 1", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9944576_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0120", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.732938 and latitude -0.394370 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 33", + "(C) 47", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778815_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0121", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.301285 and latitude 0.541854 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 4", + "(C) 61", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21894496_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0122", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.192613 and latitude -0.397264 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 65", + "(C) 3", + "(D) 159", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6814199_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0123", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249344 and latitude -0.433839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 37", + "(C) 256", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7843659_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0124", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.049866 and latitude -0.292842 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 126", + "(C) 82", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16405041_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0125", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.615962 and latitude -0.492373 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 49", + "(C) 5", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12920048_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0126", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.338270 and latitude -0.876449 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 87", + "(B) 41", + "(C) 7", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10037320_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0127", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491996 and latitude -0.575862 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 82", + "(C) 1", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18942222_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0128", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.351698 and latitude 0.585445 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 85", + "(C) 4", + "(D) 204", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5150400_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0129", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.630098 and latitude -0.486990 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 4", + "(C) 134", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462321_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0130", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.817400 and latitude -2.251600 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 9.55 degrees. The isothermality is 68.11. The temperature seasonality (100 times the standard deviation) is 141.43. The max temperature of the warmest month is 32.76 degrees. The min temperature of the coldest month is 18.74 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 25.98 degrees. The mean temperature of the driest quarter is 23.52 degrees. The mean temperature of the warmest quarter is 27.06 degrees. The mean temperature of the coldest quarter is 23.52 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 165.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 93.00. The precipitation of the wettest quarter is 353.0 mm. The precipitation of the driest quarter is 32.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 32.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 52", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10628807_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0131", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492179 and latitude -0.572649 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 221", + "(C) 10", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264892_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0132", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.625373 and latitude -4.005898 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 62", + "(C) 83", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21072125_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0133", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.881431 and latitude -1.713421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 376", + "(B) 7", + "(C) 23", + "(D) 97", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16916219_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0134", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.195626 and latitude -0.470653 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 5", + "(C) 26", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4295706_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0135", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.543559 and latitude -0.545766 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 36", + "(C) 11", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4499224_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0136", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.496572 and latitude 0.131243 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.15 degrees. The mean diurnal range is 10.59 degrees. The isothermality is 76.13. The temperature seasonality (100 times the standard deviation) is 104.18. The max temperature of the warmest month is 32.45 degrees. The min temperature of the coldest month is 18.54 degrees. The temperature annual range is 13.91 degrees. The mean temperature of the wettest quarter is 25.48 degrees. The mean temperature of the driest quarter is 23.74 degrees. The mean temperature of the warmest quarter is 26.34 degrees. The mean temperature of the coldest quarter is 23.74 degrees. The annual precipitation is 429.0 mm. The precipitation of the wettest month is 141.0 mm. The precipitation of the driest month is 0.0 mm. The precipitation seasonality (coefficient of variation) is 128.46. The precipitation of the wettest quarter is 239.0 mm. The precipitation of the driest quarter is 0.0 mm. The precipitation of the warmest quarter is 155.0 mm. The precipitation of the coldest quarter is 0.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 6", + "(C) 207", + "(D) 221", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13475065_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0137", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.205101 and latitude -0.361860 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 75", + "(B) 14", + "(C) 1", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2128014_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0138", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.558097 and latitude -0.546847 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 82", + "(C) 105", + "(D) 139", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6106357_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0139", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308797 and latitude -0.144997 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 5", + "(C) 30", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17689310_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0140", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307505 and latitude -0.821283 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 67", + "(B) 28", + "(C) 8", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020759_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0141", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635711 and latitude -3.166800 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.21 degrees. The mean diurnal range is 8.43 degrees. The isothermality is 67.81. The temperature seasonality (100 times the standard deviation) is 127.80. The max temperature of the warmest month is 31.70 degrees. The min temperature of the coldest month is 19.26 degrees. The temperature annual range is 12.44 degrees. The mean temperature of the wettest quarter is 25.58 degrees. The mean temperature of the driest quarter is 26.49 degrees. The mean temperature of the warmest quarter is 26.66 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 772.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 52.07. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 104.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 128.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 150", + "(C) 3", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176915_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0142", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237815 and latitude -0.399852 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 80", + "(C) 46", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16702750_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0143", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.325837 and latitude -0.880693 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 9", + "(C) 83", + "(D) 121", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674644_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0144", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.773967 and latitude -3.909285 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 117", + "(C) 12", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13849712_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0145", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.601902 and latitude -3.165657 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 60", + "(B) 6", + "(C) 140", + "(D) 271", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104219_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0146", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425782 and latitude -0.734198 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 57", + "(C) 153", + "(D) 135", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19074709_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0147", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309128 and latitude -0.497812 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 123", + "(C) 44", + "(D) 98", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284270_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0148", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229283 and latitude -0.396912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 69", + "(C) 55", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4209333_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0149", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431405 and latitude -0.844088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 65", + "(C) 4", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12492683_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0150", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428331 and latitude -0.769065 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 43", + "(C) 21", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21686523_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0151", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.276834 and latitude -0.740666 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 20", + "(C) 89", + "(D) 122", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10689321_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0152", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461521 and latitude -0.737663 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 19", + "(C) 204", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12955574_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0153", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.514038 and latitude -2.533392 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 177", + "(C) 271", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2665890_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0154", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.373344 and latitude -0.588738 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 88", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20990188_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0155", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.485871 and latitude -1.365101 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.45 degrees. The mean diurnal range is 10.99 degrees. The isothermality is 71.90. The temperature seasonality (100 times the standard deviation) is 129.04. The max temperature of the warmest month is 28.41 degrees. The min temperature of the coldest month is 13.12 degrees. The temperature annual range is 15.29 degrees. The mean temperature of the wettest quarter is 20.95 degrees. The mean temperature of the driest quarter is 18.89 degrees. The mean temperature of the warmest quarter is 21.79 degrees. The mean temperature of the coldest quarter is 18.56 degrees. The annual precipitation is 727.0 mm. The precipitation of the wettest month is 190.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 100.50. The precipitation of the wettest quarter is 338.0 mm. The precipitation of the driest quarter is 9.0 mm. The precipitation of the warmest quarter is 286.0 mm. The precipitation of the coldest quarter is 12.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 135", + "(B) 2", + "(C) 69", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12533990_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0156", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433333 and latitude -0.716667 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 85", + "(B) 8", + "(C) 54", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2247792_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0157", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.234154 and latitude -0.390933 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 505", + "(C) 376", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12512272_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0158", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.276000 and latitude -0.769000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 82", + "(C) 48", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2372252_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0159", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.412310 and latitude -0.773144 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 45", + "(C) 2", + "(D) 117", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9338447_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0160", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.596548 and latitude -3.165534 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 278", + "(C) 16", + "(D) 77", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22696998_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0161", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.091499 and latitude -0.492793 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 67", + "(B) 11", + "(C) 37", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17769544_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0162", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.582512 and latitude 0.350273 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 19", + "(B) 376", + "(C) 221", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1233059_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0163", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465225 and latitude -0.736990 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 60", + "(B) 152", + "(C) 159", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23190870_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0164", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.320935 and latitude -1.256069 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.94 degrees. The mean diurnal range is 11.66 degrees. The isothermality is 73.58. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 28.34 degrees. The min temperature of the coldest month is 12.49 degrees. The temperature annual range is 15.84 degrees. The mean temperature of the wettest quarter is 20.91 degrees. The mean temperature of the driest quarter is 18.46 degrees. The mean temperature of the warmest quarter is 21.24 degrees. The mean temperature of the coldest quarter is 18.16 degrees. The annual precipitation is 753.0 mm. The precipitation of the wettest month is 180.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 95.06. The precipitation of the wettest quarter is 331.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 301.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 505", + "(B) 12", + "(C) 35", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17198500_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0165", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262911 and latitude -0.816015 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 18", + "(C) 4", + "(D) 177", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151424_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0166", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095710 and latitude -0.281802 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 40", + "(C) 4", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18086660_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0167", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.800089 and latitude -3.590644 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 113", + "(C) 1", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14840328_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0168", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260102 and latitude -0.814364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 153", + "(C) 37", + "(D) 72", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20004655_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0169", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217298 and latitude 0.159901 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 56", + "(C) 22", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13087824_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0170", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.863908 and latitude 3.140709 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.29 degrees. The mean diurnal range is 13.95 degrees. The isothermality is 89.71. The temperature seasonality (100 times the standard deviation) is 59.09. The max temperature of the warmest month is 37.04 degrees. The min temperature of the coldest month is 21.49 degrees. The temperature annual range is 15.55 degrees. The mean temperature of the wettest quarter is 29.87 degrees. The mean temperature of the driest quarter is 29.28 degrees. The mean temperature of the warmest quarter is 29.93 degrees. The mean temperature of the coldest quarter is 28.63 degrees. The annual precipitation is 221.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 71.28. The precipitation of the wettest quarter is 109.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 86.0 mm. The precipitation of the coldest quarter is 37.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 58", + "(B) 10", + "(C) 122", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19793047_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0171", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.863567 and latitude -1.669264 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 5", + "(C) 78", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22960416_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0172", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.503816 and latitude -0.565360 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 60", + "(B) 89", + "(C) 6", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232902_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0173", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334140 and latitude -0.891610 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 84", + "(C) 177", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700359_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0174", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411111 and latitude -0.775306 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 57", + "(C) 6", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5650271_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0175", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.077002 and latitude -0.319021 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 249", + "(C) 150", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16098203_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0176", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.772937 and latitude -3.944691 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 117", + "(C) 79", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16237233_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0177", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.305355 and latitude 0.440158 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 54", + "(B) 23", + "(C) 55", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8123311_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0178", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.959969 and latitude -0.040555 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 10", + "(C) 62", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11469923_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0179", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.462258 and latitude -0.903389 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 18", + "(C) 16", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674581_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0180", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444232 and latitude -0.916354 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 123", + "(B) 40", + "(C) 80", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17671545_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0181", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.375000 and latitude 0.606944 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 110", + "(B) 1", + "(C) 29", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10171402_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0182", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.434971 and latitude -0.766284 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 69", + "(B) 259", + "(C) 37", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15027674_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0183", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.333929 and latitude -0.650472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 35", + "(C) 11", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207483_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0184", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429051 and latitude -0.703422 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 9", + "(C) 132", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20290756_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0185", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.237024 and latitude -0.397715 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 1", + "(C) 17", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20792007_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0186", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.725290 and latitude -0.391729 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 50", + "(C) 82", + "(D) 123", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283134_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0187", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.504741 and latitude -3.146385 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 2", + "(C) 54", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17176924_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0188", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464045 and latitude -0.738076 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 140", + "(C) 1", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16432755_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0189", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.112499 and latitude -0.511699 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 7", + "(C) 102", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9929386_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0190", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438832 and latitude -0.696724 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 87", + "(B) 15", + "(C) 4", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16273454_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0191", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.155370 and latitude -0.327273 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 505", + "(C) 39", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20955511_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0192", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.666655 and latitude -0.416597 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 111", + "(B) 16", + "(C) 132", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15780478_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0193", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.607773 and latitude -4.033453 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 1", + "(C) 82", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070470_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0194", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.127913 and latitude -0.425033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 138", + "(B) 132", + "(C) 117", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446678_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0195", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438343 and latitude -0.728957 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 270", + "(C) 27", + "(D) 121", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3111177_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0196", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308737 and latitude -0.144019 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 47", + "(C) 38", + "(D) 311", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21584322_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0197", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435471 and latitude -0.730914 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 129", + "(C) 21", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284268_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0198", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321058 and latitude -0.512058 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 54", + "(C) 1", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5541002_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0199", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.356469 and latitude -0.738459 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 269", + "(C) 185", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563397_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0200", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.667486 and latitude -1.245196 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.46 degrees. The mean diurnal range is 11.48 degrees. The isothermality is 73.55. The temperature seasonality (100 times the standard deviation) is 122.66. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 14.09 degrees. The temperature annual range is 15.61 degrees. The mean temperature of the wettest quarter is 21.93 degrees. The mean temperature of the driest quarter is 19.68 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.68 degrees. The annual precipitation is 724.0 mm. The precipitation of the wettest month is 225.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 113.52. The precipitation of the wettest quarter is 383.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 8.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 28", + "(C) 185", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12595326_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0201", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.613438 and latitude 3.772566 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.53 degrees. The mean diurnal range is 13.60 degrees. The isothermality is 83.55. The temperature seasonality (100 times the standard deviation) is 82.45. The max temperature of the warmest month is 35.21 degrees. The min temperature of the coldest month is 18.93 degrees. The temperature annual range is 16.27 degrees. The mean temperature of the wettest quarter is 26.97 degrees. The mean temperature of the driest quarter is 27.18 degrees. The mean temperature of the warmest quarter is 27.66 degrees. The mean temperature of the coldest quarter is 25.54 degrees. The annual precipitation is 448.0 mm. The precipitation of the wettest month is 81.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 51.57. The precipitation of the wettest quarter is 181.0 mm. The precipitation of the driest quarter is 50.0 mm. The precipitation of the warmest quarter is 77.0 mm. The precipitation of the coldest quarter is 118.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 88", + "(C) 58", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18792294_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0202", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.630898 and latitude -2.885577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 117", + "(C) 40", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10986333_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0203", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308702 and latitude -0.144940 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 100", + "(C) 11", + "(D) 66", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17693303_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0204", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431025 and latitude -0.717178 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 110", + "(C) 27", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10777816_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0205", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.711628 and latitude -4.045739 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 91", + "(B) 9", + "(C) 27", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2125379_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0206", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.184491 and latitude -3.567496 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 87", + "(C) 89", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20640190_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0207", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724500 and latitude -0.498620 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 38", + "(C) 22", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844377_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0208", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059661 and latitude 3.685803 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.60 degrees. The mean diurnal range is 9.46 degrees. The isothermality is 80.33. The temperature seasonality (100 times the standard deviation) is 76.16. The max temperature of the warmest month is 34.84 degrees. The min temperature of the coldest month is 23.06 degrees. The temperature annual range is 11.78 degrees. The mean temperature of the wettest quarter is 28.96 degrees. The mean temperature of the driest quarter is 28.27 degrees. The mean temperature of the warmest quarter is 29.56 degrees. The mean temperature of the coldest quarter is 27.64 degrees. The annual precipitation is 203.0 mm. The precipitation of the wettest month is 46.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 80.02. The precipitation of the wettest quarter is 100.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 53.0 mm. The precipitation of the coldest quarter is 19.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 12", + "(C) 52", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6286237_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0209", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.934120 and latitude -0.234038 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 5", + "(C) 77", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9078674_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0210", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.155125 and latitude 0.734127 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.31 degrees. The mean diurnal range is 13.08 degrees. The isothermality is 82.01. The temperature seasonality (100 times the standard deviation) is 78.19. The max temperature of the warmest month is 27.02 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.95 degrees. The mean temperature of the wettest quarter is 17.32 degrees. The mean temperature of the driest quarter is 18.80 degrees. The mean temperature of the warmest quarter is 19.29 degrees. The mean temperature of the coldest quarter is 17.32 degrees. The annual precipitation is 1160.0 mm. The precipitation of the wettest month is 188.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 56.08. The precipitation of the wettest quarter is 474.0 mm. The precipitation of the driest quarter is 103.0 mm. The precipitation of the warmest quarter is 250.0 mm. The precipitation of the coldest quarter is 474.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 113", + "(C) 10", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8677517_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0211", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.146769 and latitude -0.421919 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 60", + "(B) 6", + "(C) 34", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16582092_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0212", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117312 and latitude -0.315226 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 58", + "(C) 32", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794204_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0213", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.949903 and latitude -0.246765 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 56", + "(C) 117", + "(D) 89", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23261461_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0214", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.388264 and latitude -0.668392 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 4", + "(C) 69", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7839188_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0215", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088550 and latitude -0.281778 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 61", + "(B) 271", + "(C) 140", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16772590_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0216", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115849 and latitude -0.437562 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 19", + "(C) 28", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214619_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0217", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.679827 and latitude -4.062661 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 270", + "(C) 5", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5130641_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0218", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120639 and latitude -0.423215 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 58", + "(C) 1", + "(D) 97", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19446569_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0219", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217522 and latitude 0.159924 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 62", + "(C) 63", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14292511_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0220", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451164 and latitude -0.732254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 38", + "(C) 111", + "(D) 123", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14087358_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0221", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.570883 and latitude 0.318314 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 35", + "(B) 38", + "(C) 10", + "(D) 91", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6107052_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0222", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.617328 and latitude -0.493218 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 92", + "(B) 3", + "(C) 44", + "(D) 133", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22470138_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0223", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.670429 and latitude -4.094411 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 1", + "(C) 52", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2939352_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0224", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453195 and latitude -0.740835 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 61", + "(C) 365", + "(D) 70", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12937401_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0225", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450963 and latitude -0.498124 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 6", + "(C) 53", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6303604_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0226", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.133619 and latitude -0.418663 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 91", + "(B) 22", + "(C) 121", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13413391_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0227", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.742377 and latitude -3.953980 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 8", + "(C) 140", + "(D) 78", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259761_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0228", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442316 and latitude -0.734910 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 28", + "(C) 134", + "(D) 135", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12913249_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0229", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.658327 and latitude -4.085605 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 51", + "(C) 204", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952141_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0230", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337747 and latitude -2.249538 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 18", + "(C) 96", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21230539_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0231", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429984 and latitude -0.814253 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 95", + "(C) 64", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6985066_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0232", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450823 and latitude -0.739571 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 1", + "(C) 3", + "(D) 129", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17505776_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0233", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125623 and latitude -0.177259 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 27", + "(C) 90", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22179103_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0234", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.638608 and latitude -4.052072 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 38", + "(C) 278", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20718767_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0235", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419616 and latitude -0.693378 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 135", + "(C) 83", + "(D) 270", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9680706_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0236", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495962 and latitude -0.568284 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 53", + "(C) 63", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17683548_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0237", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564208 and latitude -0.562112 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 71", + "(C) 19", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16788493_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0238", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.724827 and latitude -0.476804 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 20", + "(C) 102", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15073057_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0239", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.261411 and latitude -1.398081 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 123", + "(B) 11", + "(C) 62", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12139266_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0240", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.744654 and latitude -3.935367 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 12", + "(C) 52", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6209488_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0241", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.579518 and latitude -2.995523 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 1", + "(C) 66", + "(D) 78", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16308585_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0242", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.109989 and latitude -0.307528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 8", + "(C) 146", + "(D) 108", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3189156_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0243", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.573481 and latitude -2.962016 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 56", + "(C) 114", + "(D) 270", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18498363_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0244", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473665 and latitude -0.594187 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 88", + "(B) 150", + "(C) 5", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16089193_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0245", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125643 and latitude -0.477135 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 173", + "(B) 39", + "(C) 114", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7776635_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0246", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.977112 and latitude -0.177386 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 46", + "(C) 95", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16897456_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0247", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362561 and latitude -0.858995 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 25", + "(C) 1", + "(D) 90", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18075784_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0248", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.448680 and latitude -0.717081 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 53", + "(C) 11", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16028041_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0249", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.964847 and latitude -0.002364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 270", + "(C) 11", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6108684_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0250", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477656 and latitude -0.711947 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 80", + "(C) 3", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4016734_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0251", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.257458 and latitude -0.482749 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 46", + "(B) 173", + "(C) 221", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284276_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0252", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731725 and latitude -3.989566 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 107", + "(C) 1", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16824651_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0253", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.578744 and latitude 0.337288 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 79", + "(C) 134", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17092563_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0254", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.470140 and latitude -0.627299 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 27", + "(C) 11", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9240243_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0255", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.956106 and latitude -0.021973 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 66", + "(C) 15", + "(D) 133", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18789323_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0256", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.218005 and latitude -0.411473 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 259", + "(B) 6", + "(C) 57", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17946602_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0257", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298029 and latitude -0.819797 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 31", + "(C) 39", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17540739_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0258", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090603 and latitude -0.191745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 4", + "(C) 117", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487379_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0259", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.787467 and latitude -3.860947 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 111", + "(C) 114", + "(D) 278", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511369_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0260", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.255731 and latitude -0.437468 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 61", + "(B) 1", + "(C) 45", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7725585_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0261", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263032 and latitude -0.815839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 58", + "(B) 9", + "(C) 37", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5007944_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0262", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458876 and latitude -0.737428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 1", + "(C) 88", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17640008_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0263", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451609 and latitude -0.741804 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 16", + "(C) 137", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15304037_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0264", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.144315 and latitude -0.419699 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 132", + "(C) 50", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22402553_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0265", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.874158 and latitude -1.662879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 1", + "(C) 52", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18585100_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0266", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.383148 and latitude -0.624033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 24", + "(C) 77", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207487_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0267", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249900 and latitude -0.482300 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 3", + "(C) 78", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025947_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0268", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.388683 and latitude -0.692627 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 15", + "(C) 5", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21912123_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0269", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.603307 and latitude -4.033056 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 32", + "(C) 5", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20066812_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0270", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.528911 and latitude -2.523347 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 278", + "(B) 80", + "(C) 27", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6312722_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0271", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.062115 and latitude -0.385601 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 66", + "(C) 11", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21471819_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0272", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328129 and latitude -0.745161 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 278", + "(B) 271", + "(C) 8", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2344413_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0273", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421400 and latitude -0.763900 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 259", + "(C) 71", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9216894_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0274", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.294833 and latitude 0.494287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 68", + "(B) 34", + "(C) 9", + "(D) 132", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21147101_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0275", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444426 and latitude -0.713927 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 59", + "(C) 67", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21640695_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0276", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.200337 and latitude -0.887067 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 5", + "(C) 132", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22018381_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0277", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.053008 and latitude -0.427117 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 1", + "(C) 47", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22969367_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0278", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.217477 and latitude 0.159772 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.14 degrees. The mean diurnal range is 11.70 degrees. The isothermality is 83.21. The temperature seasonality (100 times the standard deviation) is 63.72. The max temperature of the warmest month is 29.52 degrees. The min temperature of the coldest month is 15.46 degrees. The temperature annual range is 14.06 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.69 degrees. The mean temperature of the warmest quarter is 22.93 degrees. The mean temperature of the coldest quarter is 21.31 degrees. The annual precipitation is 1408.0 mm. The precipitation of the wettest month is 227.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 42.49. The precipitation of the wettest quarter is 552.0 mm. The precipitation of the driest quarter is 223.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 270.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 43", + "(C) 1", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14801976_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0279", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.575960 and latitude -3.166687 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.21 degrees. The mean diurnal range is 8.43 degrees. The isothermality is 67.81. The temperature seasonality (100 times the standard deviation) is 127.80. The max temperature of the warmest month is 31.70 degrees. The min temperature of the coldest month is 19.26 degrees. The temperature annual range is 12.44 degrees. The mean temperature of the wettest quarter is 25.58 degrees. The mean temperature of the driest quarter is 26.49 degrees. The mean temperature of the warmest quarter is 26.66 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 772.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 52.07. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 104.0 mm. The precipitation of the warmest quarter is 171.0 mm. The precipitation of the coldest quarter is 128.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 117", + "(C) 9", + "(D) 108", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22546889_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0280", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115430 and latitude -0.291496 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 173", + "(C) 8", + "(D) 112", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10108533_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0281", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.168400 and latitude -0.313138 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.18 degrees. The mean diurnal range is 13.35 degrees. The isothermality is 79.94. The temperature seasonality (100 times the standard deviation) is 76.39. The max temperature of the warmest month is 23.24 degrees. The min temperature of the coldest month is 6.53 degrees. The temperature annual range is 16.70 degrees. The mean temperature of the wettest quarter is 14.47 degrees. The mean temperature of the driest quarter is 14.51 degrees. The mean temperature of the warmest quarter is 15.19 degrees. The mean temperature of the coldest quarter is 13.26 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 141.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 43.82. The precipitation of the wettest quarter is 361.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 236.0 mm. The precipitation of the coldest quarter is 314.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 10", + "(C) 33", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7852021_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0282", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.213000 and latitude -0.418000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 1", + "(C) 10", + "(D) 271", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16177177_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0283", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.600571 and latitude -4.029169 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 80", + "(C) 311", + "(D) 4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21137855_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0284", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.771232 and latitude -3.944620 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 43", + "(C) 11", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6755433_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0285", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.402762 and latitude -0.767880 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 12", + "(C) 107", + "(D) 204", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5411827_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0286", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.219587 and latitude -0.507804 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 11", + "(C) 100", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16110678_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0287", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429457 and latitude -0.629157 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 139", + "(C) 269", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520360_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0288", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.384439 and latitude -0.625925 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 5", + "(C) 19", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5731711_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0289", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.795485 and latitude -3.816549 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 71", + "(C) 105", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6691956_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0290", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.916514 and latitude -0.239331 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 4", + "(C) 96", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14119738_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0291", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.275253 and latitude -0.827148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 259", + "(C) 52", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22718838_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0292", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.635757 and latitude -3.166420 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 78", + "(C) 80", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23104263_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0293", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428538 and latitude -0.709808 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 70", + "(C) 66", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20882646_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0294", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.259398 and latitude -0.809206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 112", + "(C) 3", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260053_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0295", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.559850 and latitude -3.165834 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 61", + "(C) 22", + "(D) 88", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22860349_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0296", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.434216 and latitude -0.629440 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 77", + "(B) 43", + "(C) 6", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23521015_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0297", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.726790 and latitude -0.433400 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 126", + "(C) 4", + "(D) 110", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844387_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0298", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334770 and latitude -0.824762 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 153", + "(C) 87", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3448162_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0299", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493359 and latitude -0.573695 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 8", + "(C) 67", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919982_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0300", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.219629 and latitude -0.479424 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 54", + "(B) 505", + "(C) 57", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237310_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0301", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.390540 and latitude -0.800126 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 3", + "(C) 53", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12907483_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0302", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.107865 and latitude -0.257710 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 16", + "(C) 46", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12620886_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0303", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263226 and latitude -0.820533 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 67", + "(C) 16", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4137246_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0304", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.295821 and latitude -0.667481 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 25", + "(C) 111", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8623062_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0305", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.458126 and latitude -0.527085 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 62", + "(C) 23", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13033573_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0306", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221382 and latitude -0.494197 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 365", + "(B) 95", + "(C) 171", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4116722_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0307", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418361 and latitude -0.720639 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 152", + "(B) 30", + "(C) 3", + "(D) 98", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23122367_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0308", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.676052 and latitude -0.482208 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 68", + "(C) 57", + "(D) 83", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22520447_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0309", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.495133 and latitude -0.569162 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 1", + "(C) 75", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21216721_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0310", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451943 and latitude -0.565885 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 49", + "(B) 13", + "(C) 117", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6499619_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0311", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.661374 and latitude -4.051145 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 102", + "(B) 18", + "(C) 98", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259740_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0312", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.427978 and latitude -0.629969 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 92", + "(C) 32", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5650316_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0313", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.681488 and latitude -4.049599 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 17", + "(C) 33", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5398498_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0314", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471611 and latitude -0.894685 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 62", + "(C) 22", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17674569_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0315", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087657 and latitude -0.462113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 102", + "(C) 72", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794460_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0316", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.617162 and latitude -0.492412 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 126", + "(C) 107", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12019208_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0317", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.022308 and latitude -0.070060 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 66", + "(C) 102", + "(D) 134", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12901835_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0318", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421957 and latitude -0.778190 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 138", + "(C) 40", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7864240_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0319", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.808845 and latitude 0.249657 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.38 degrees. The mean diurnal range is 15.42 degrees. The isothermality is 79.55. The temperature seasonality (100 times the standard deviation) is 56.98. The max temperature of the warmest month is 27.08 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 19.39 degrees. The mean temperature of the wettest quarter is 18.16 degrees. The mean temperature of the driest quarter is 17.19 degrees. The mean temperature of the warmest quarter is 18.16 degrees. The mean temperature of the coldest quarter is 16.83 degrees. The annual precipitation is 709.0 mm. The precipitation of the wettest month is 126.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 49.31. The precipitation of the wettest quarter is 259.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 259.0 mm. The precipitation of the coldest quarter is 176.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 5", + "(C) 43", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8193671_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0320", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486027 and latitude -0.645036 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 89", + "(C) 1", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17730556_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0321", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477997 and latitude -0.633960 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 14", + "(C) 72", + "(D) 505", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10223584_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0322", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.086655 and latitude -0.314825 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 61", + "(B) 16", + "(C) 114", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2863798_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0323", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.122900 and latitude -0.194700 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 14", + "(C) 177", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7775990_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0324", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.470818 and latitude -0.596602 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 49", + "(C) 58", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23191175_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0325", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.601035 and latitude -4.030511 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 207", + "(C) 66", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5404977_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0326", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.473812 and latitude -0.589608 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 114", + "(B) 97", + "(C) 146", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952019_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0327", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.446179 and latitude -0.755743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 22", + "(C) 10", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23122301_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0328", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.810734 and latitude -3.817182 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 23", + "(C) 70", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7940307_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0329", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.940865 and latitude -1.097290 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.63 degrees. The mean diurnal range is 9.45 degrees. The isothermality is 69.39. The temperature seasonality (100 times the standard deviation) is 135.63. The max temperature of the warmest month is 34.78 degrees. The min temperature of the coldest month is 21.16 degrees. The temperature annual range is 13.62 degrees. The mean temperature of the wettest quarter is 28.10 degrees. The mean temperature of the driest quarter is 25.77 degrees. The mean temperature of the warmest quarter is 29.16 degrees. The mean temperature of the coldest quarter is 25.77 degrees. The annual precipitation is 425.0 mm. The precipitation of the wettest month is 100.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 95.08. The precipitation of the wettest quarter is 194.0 mm. The precipitation of the driest quarter is 24.0 mm. The precipitation of the warmest quarter is 152.0 mm. The precipitation of the coldest quarter is 24.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 39", + "(C) 23", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12753463_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0330", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.391834 and latitude 0.644891 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 1", + "(C) 33", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6277844_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0331", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.381939 and latitude -0.762206 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 71", + "(C) 31", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449300_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0332", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116309 and latitude -0.410675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 256", + "(B) 25", + "(C) 150", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683921_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0333", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.301178 and latitude 0.472054 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 146", + "(C) 29", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5190089_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0334", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.353146 and latitude 0.471720 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.07 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 81.77. The temperature seasonality (100 times the standard deviation) is 79.91. The max temperature of the warmest month is 24.33 degrees. The min temperature of the coldest month is 9.18 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 15.02 degrees. The mean temperature of the driest quarter is 16.53 degrees. The mean temperature of the warmest quarter is 17.04 degrees. The mean temperature of the coldest quarter is 15.02 degrees. The annual precipitation is 1155.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 49.05. The precipitation of the wettest quarter is 405.0 mm. The precipitation of the driest quarter is 131.0 mm. The precipitation of the warmest quarter is 294.0 mm. The precipitation of the coldest quarter is 405.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 32", + "(C) 51", + "(D) 70", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3539626_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0335", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.657404 and latitude -4.070000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 46", + "(B) 137", + "(C) 139", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21659195_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0336", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.191342 and latitude -1.465708 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.86 degrees. The mean diurnal range is 11.15 degrees. The isothermality is 72.14. The temperature seasonality (100 times the standard deviation) is 128.58. The max temperature of the warmest month is 27.03 degrees. The min temperature of the coldest month is 11.57 degrees. The temperature annual range is 15.46 degrees. The mean temperature of the wettest quarter is 19.84 degrees. The mean temperature of the driest quarter is 17.31 degrees. The mean temperature of the warmest quarter is 20.22 degrees. The mean temperature of the coldest quarter is 16.99 degrees. The annual precipitation is 861.0 mm. The precipitation of the wettest month is 197.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 92.70. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 22.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 89", + "(B) 7", + "(C) 19", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22054860_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0337", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491733 and latitude -0.573341 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 91", + "(B) 92", + "(C) 3", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874268_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0338", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.530113 and latitude -2.546254 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 12.61 degrees. The isothermality is 71.14. The temperature seasonality (100 times the standard deviation) is 152.06. The max temperature of the warmest month is 31.30 degrees. The min temperature of the coldest month is 13.58 degrees. The temperature annual range is 17.72 degrees. The mean temperature of the wettest quarter is 22.58 degrees. The mean temperature of the driest quarter is 19.81 degrees. The mean temperature of the warmest quarter is 23.36 degrees. The mean temperature of the coldest quarter is 19.59 degrees. The annual precipitation is 693.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 90.97. The precipitation of the wettest quarter is 313.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 179.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 91", + "(C) 18", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12171795_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0339", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.764946 and latitude -0.471575 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.64 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 75.78. The temperature seasonality (100 times the standard deviation) is 110.82. The max temperature of the warmest month is 29.44 degrees. The min temperature of the coldest month is 14.75 degrees. The temperature annual range is 14.69 degrees. The mean temperature of the wettest quarter is 22.13 degrees. The mean temperature of the driest quarter is 20.09 degrees. The mean temperature of the warmest quarter is 22.81 degrees. The mean temperature of the coldest quarter is 20.09 degrees. The annual precipitation is 921.0 mm. The precipitation of the wettest month is 231.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.70. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 18.0 mm. The precipitation of the warmest quarter is 351.0 mm. The precipitation of the coldest quarter is 18.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 4", + "(C) 58", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22973092_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0340", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.494308 and latitude -0.574789 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 140", + "(B) 15", + "(C) 41", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22251379_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0341", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.497309 and latitude -0.575281 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 84", + "(C) 41", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21034667_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0342", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.374162 and latitude 0.606630 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 40", + "(C) 1", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16017828_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0343", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.664000 and latitude -0.525000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 376", + "(C) 15", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17120138_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0344", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.448282 and latitude -0.727571 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 129", + "(C) 12", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17511060_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0345", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.406424 and latitude -0.794164 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 185", + "(C) 19", + "(D) 89", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15033982_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0346", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418797 and latitude -0.720689 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 376", + "(C) 61", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18137410_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0347", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419966 and latitude -0.692488 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 129", + "(C) 107", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17894349_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0348", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260664 and latitude -0.451287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 75", + "(C) 29", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22454762_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0349", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537651 and latitude -0.548722 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 25", + "(C) 35", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11217739_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0350", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.527843 and latitude -0.553853 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 13", + "(C) 25", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3837423_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0351", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.174772 and latitude 0.745997 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.45 degrees. The mean diurnal range is 13.17 degrees. The isothermality is 82.23. The temperature seasonality (100 times the standard deviation) is 77.96. The max temperature of the warmest month is 26.16 degrees. The min temperature of the coldest month is 10.14 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 16.45 degrees. The mean temperature of the driest quarter is 17.86 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.45 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 160.0 mm. The precipitation of the driest month is 24.0 mm. The precipitation seasonality (coefficient of variation) is 52.76. The precipitation of the wettest quarter is 398.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 380.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 99", + "(C) 87", + "(D) 91", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15852185_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0352", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.621668 and latitude -0.492862 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 113", + "(C) 112", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970656_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0353", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.594228 and latitude -0.520317 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 150", + "(B) 20", + "(C) 259", + "(D) 221", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12970890_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0354", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323997 and latitude -0.815719 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 7", + "(C) 135", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260914_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0355", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.389996 and latitude -0.846563 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 53", + "(C) 31", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614321_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0356", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.403337 and latitude -0.689528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 121", + "(C) 89", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20882710_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0357", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.299127 and latitude 0.750025 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.45 degrees. The mean diurnal range is 13.17 degrees. The isothermality is 82.23. The temperature seasonality (100 times the standard deviation) is 77.96. The max temperature of the warmest month is 26.16 degrees. The min temperature of the coldest month is 10.14 degrees. The temperature annual range is 16.02 degrees. The mean temperature of the wettest quarter is 16.45 degrees. The mean temperature of the driest quarter is 17.86 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.45 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 160.0 mm. The precipitation of the driest month is 24.0 mm. The precipitation seasonality (coefficient of variation) is 52.76. The precipitation of the wettest quarter is 398.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 380.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 114", + "(C) 14", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18568633_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0358", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.445636 and latitude -0.521177 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 77", + "(B) 256", + "(C) 50", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21193685_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0359", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.723508 and latitude -3.625630 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 71", + "(C) 27", + "(D) 98", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16058252_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0360", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.300407 and latitude -0.818526 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 16", + "(C) 26", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304185_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0361", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.426550 and latitude -0.700406 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 137", + "(B) 25", + "(C) 15", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436289_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0362", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.763536 and latitude -0.385051 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 376", + "(C) 221", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10216632_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0363", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.314601 and latitude -0.814606 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 17", + "(C) 78", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5635215_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0364", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.277937 and latitude -0.467145 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 152", + "(C) 21", + "(D) 311", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3136844_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0365", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.099495 and latitude -0.421912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 17", + "(C) 39", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15414258_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0366", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.373900 and latitude 0.606011 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.27 degrees. The mean diurnal range is 12.58 degrees. The isothermality is 81.71. The temperature seasonality (100 times the standard deviation) is 80.56. The max temperature of the warmest month is 24.60 degrees. The min temperature of the coldest month is 9.20 degrees. The temperature annual range is 15.40 degrees. The mean temperature of the wettest quarter is 16.42 degrees. The mean temperature of the driest quarter is 16.70 degrees. The mean temperature of the warmest quarter is 17.25 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 1088.0 mm. The precipitation of the wettest month is 170.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 47.89. The precipitation of the wettest quarter is 391.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 290.0 mm. The precipitation of the coldest quarter is 352.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 146", + "(C) 204", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14384250_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0367", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492206 and latitude -0.572734 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 132", + "(C) 21", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23191397_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0368", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.369111 and latitude -0.852654 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 87", + "(C) 171", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18272761_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0369", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.393146 and latitude -0.809223 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 14", + "(C) 97", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9850797_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0370", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189833 and latitude -0.808010 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 97", + "(C) 112", + "(D) 134", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21155579_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0371", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.637396 and latitude 0.414141 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.73 degrees. The mean diurnal range is 15.52 degrees. The isothermality is 81.38. The temperature seasonality (100 times the standard deviation) is 60.58. The max temperature of the warmest month is 27.31 degrees. The min temperature of the coldest month is 8.23 degrees. The temperature annual range is 19.08 degrees. The mean temperature of the wettest quarter is 18.18 degrees. The mean temperature of the driest quarter is 17.70 degrees. The mean temperature of the warmest quarter is 18.54 degrees. The mean temperature of the coldest quarter is 17.02 degrees. The annual precipitation is 679.0 mm. The precipitation of the wettest month is 113.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 48.55. The precipitation of the wettest quarter is 245.0 mm. The precipitation of the driest quarter is 78.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 189.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 87", + "(C) 26", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18372057_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0372", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.315994 and latitude -0.505364 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 33", + "(C) 171", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1966451_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0373", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.413886 and latitude -0.714329 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 88", + "(C) 150", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526554_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0374", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.587900 and latitude -0.527418 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 39", + "(C) 25", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14838352_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0375", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492998 and latitude -0.573957 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 47", + "(C) 132", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258666_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0376", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.189847 and latitude -0.499457 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 108", + "(B) 21", + "(C) 132", + "(D) 77", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4192719_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0377", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.630851 and latitude -1.414689 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.42 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 72.41. The temperature seasonality (100 times the standard deviation) is 126.48. The max temperature of the warmest month is 29.39 degrees. The min temperature of the coldest month is 14.02 degrees. The temperature annual range is 15.37 degrees. The mean temperature of the wettest quarter is 21.91 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.57 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 204.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 105.97. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 270.0 mm. The precipitation of the coldest quarter is 10.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 311", + "(C) 19", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3810527_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0378", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391354 and latitude -0.810172 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 64", + "(B) 105", + "(C) 256", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076203_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0379", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.783590 and latitude 3.395485 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 29.48 degrees. The mean diurnal range is 13.65 degrees. The isothermality is 89.33. The temperature seasonality (100 times the standard deviation) is 58.34. The max temperature of the warmest month is 37.24 degrees. The min temperature of the coldest month is 21.96 degrees. The temperature annual range is 15.28 degrees. The mean temperature of the wettest quarter is 29.93 degrees. The mean temperature of the driest quarter is 29.42 degrees. The mean temperature of the warmest quarter is 30.09 degrees. The mean temperature of the coldest quarter is 28.80 degrees. The annual precipitation is 216.0 mm. The precipitation of the wettest month is 51.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 73.14. The precipitation of the wettest quarter is 108.0 mm. The precipitation of the driest quarter is 20.0 mm. The precipitation of the warmest quarter is 90.0 mm. The precipitation of the coldest quarter is 32.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 44", + "(C) 1", + "(D) 168", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18766494_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0380", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.477413 and latitude -0.548408 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 16", + "(C) 69", + "(D) 270", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952041_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0381", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.292430 and latitude -0.474668 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 173", + "(C) 77", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10016562_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0382", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.750250 and latitude -0.385840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 126", + "(B) 14", + "(C) 84", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3844397_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0383", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.553340 and latitude -0.544870 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 30", + "(C) 13", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12677036_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0384", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469705 and latitude -0.596839 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 85", + "(C) 47", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23264886_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0385", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.109073 and latitude -0.625061 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 95", + "(B) 138", + "(C) 110", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5053497_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0386", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.666660 and latitude -0.416660 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 97", + "(C) 53", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700354_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0387", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.787022 and latitude -3.611775 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 100", + "(C) 26", + "(D) 132", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12512160_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0388", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428950 and latitude -0.631089 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 505", + "(C) 65", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520123_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0389", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.309540 and latitude 0.480940 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 68", + "(C) 49", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025079_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0390", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.449158 and latitude -0.736882 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 69", + "(B) 27", + "(C) 43", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17715489_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0391", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117551 and latitude -0.423970 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 31", + "(C) 8", + "(D) 135", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20175100_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0392", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.318789 and latitude -0.686781 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 90", + "(C) 82", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20542245_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0393", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.994504 and latitude -0.243940 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 249", + "(C) 13", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19362935_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0394", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308906 and latitude -0.144131 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 132", + "(C) 23", + "(D) 83", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18512495_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0395", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493108 and latitude -0.574312 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 3", + "(C) 72", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13649793_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0396", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.212121 and latitude -1.750867 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.31 degrees. The mean diurnal range is 8.45 degrees. The isothermality is 67.30. The temperature seasonality (100 times the standard deviation) is 129.89. The max temperature of the warmest month is 34.03 degrees. The min temperature of the coldest month is 21.48 degrees. The temperature annual range is 12.56 degrees. The mean temperature of the wettest quarter is 27.30 degrees. The mean temperature of the driest quarter is 28.77 degrees. The mean temperature of the warmest quarter is 28.81 degrees. The mean temperature of the coldest quarter is 25.64 degrees. The annual precipitation is 602.0 mm. The precipitation of the wettest month is 96.0 mm. The precipitation of the driest month is 9.0 mm. The precipitation seasonality (coefficient of variation) is 52.37. The precipitation of the wettest quarter is 237.0 mm. The precipitation of the driest quarter is 68.0 mm. The precipitation of the warmest quarter is 134.0 mm. The precipitation of the coldest quarter is 113.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 256", + "(B) 97", + "(C) 98", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21815233_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0397", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.464309 and latitude -0.711496 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 36", + "(C) 26", + "(D) 110", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7793665_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0398", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.258316 and latitude -0.472450 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 30", + "(C) 207", + "(D) 90", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5375564_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0399", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.248391 and latitude -0.463011 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 23", + "(C) 4", + "(D) 77", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17889591_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0400", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554389 and latitude -0.545723 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 13", + "(C) 25", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4897237_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0401", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323909 and latitude -0.716962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 75", + "(C) 20", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14451311_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0402", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306295 and latitude -0.888119 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 114", + "(B) 20", + "(C) 38", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21760935_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0403", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450996 and latitude -0.742628 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 9", + "(C) 10", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14709637_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0404", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.627259 and latitude -0.491738 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 62", + "(C) 32", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4897193_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0405", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.572693 and latitude -0.608155 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 70", + "(C) 75", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14188081_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0406", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.439377 and latitude -0.736368 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 121", + "(B) 13", + "(C) 33", + "(D) 129", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17074113_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0407", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469185 and latitude -0.596552 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 150", + "(C) 122", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20163417_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0408", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.438713 and latitude -0.728692 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 97", + "(C) 24", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7239787_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0409", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.732674 and latitude -3.996109 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 107", + "(C) 48", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8781358_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0410", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.581564 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 114", + "(C) 65", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8462486_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0411", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.745582 and latitude -3.935211 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 29", + "(C) 100", + "(D) 177", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6368285_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0412", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421976 and latitude -0.767518 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 40", + "(B) 16", + "(C) 64", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21690200_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0413", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087024 and latitude -0.272079 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 153", + "(B) 59", + "(C) 99", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15579688_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0414", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401497 and latitude -0.775472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 29", + "(C) 123", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17279003_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0415", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437870 and latitude -0.712380 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 64", + "(C) 13", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3235555_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0416", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084155 and latitude -0.310158 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 62", + "(B) 18", + "(C) 270", + "(D) 97", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22149720_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0417", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.987358 and latitude -0.065888 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 271", + "(C) 177", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18020893_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0418", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.653233 and latitude -0.520653 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 14", + "(C) 89", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12922521_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0419", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309504 and latitude -0.144840 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 85", + "(B) 69", + "(C) 122", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17105797_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0420", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.563720 and latitude 0.302911 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.97 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 82.59. The temperature seasonality (100 times the standard deviation) is 78.48. The max temperature of the warmest month is 29.64 degrees. The min temperature of the coldest month is 13.61 degrees. The temperature annual range is 16.03 degrees. The mean temperature of the wettest quarter is 20.77 degrees. The mean temperature of the driest quarter is 20.13 degrees. The mean temperature of the warmest quarter is 21.84 degrees. The mean temperature of the coldest quarter is 20.13 degrees. The annual precipitation is 1084.0 mm. The precipitation of the wettest month is 279.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 100.70. The precipitation of the wettest quarter is 570.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 353.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 85", + "(C) 12", + "(D) 140", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22403601_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0421", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420348 and latitude -0.693444 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 18", + "(C) 92", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8291585_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0422", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.751548 and latitude -3.972793 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 40", + "(B) 278", + "(C) 15", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15271561_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0423", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.698753 and latitude -4.050234 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 49", + "(C) 7", + "(D) 82", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2843164_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0424", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.025098 and latitude -0.272587 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 17", + "(C) 1", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2487314_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0425", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.663763 and latitude -0.524993 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 365", + "(C) 47", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20233097_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0426", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453301 and latitude -0.727955 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 75", + "(B) 129", + "(C) 1", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17028883_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0427", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.866695 and latitude -1.696835 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 14", + "(C) 92", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21108844_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0428", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.789200 and latitude -3.793600 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 63", + "(B) 43", + "(C) 27", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16527480_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0429", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731682 and latitude -3.989279 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 55", + "(C) 17", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19738874_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0430", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425833 and latitude -0.633080 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 31", + "(C) 15", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18595306_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0431", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.755890 and latitude 0.551423 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.52 degrees. The mean diurnal range is 12.84 degrees. The isothermality is 83.19. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 16.30 degrees. The temperature annual range is 15.43 degrees. The mean temperature of the wettest quarter is 23.34 degrees. The mean temperature of the driest quarter is 22.72 degrees. The mean temperature of the warmest quarter is 24.38 degrees. The mean temperature of the coldest quarter is 22.72 degrees. The annual precipitation is 533.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.08. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 75", + "(B) 221", + "(C) 20", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2262871_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0432", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.633362 and latitude -0.206337 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.24 degrees. The mean diurnal range is 10.34 degrees. The isothermality is 73.35. The temperature seasonality (100 times the standard deviation) is 120.47. The max temperature of the warmest month is 35.74 degrees. The min temperature of the coldest month is 21.65 degrees. The temperature annual range is 14.10 degrees. The mean temperature of the wettest quarter is 28.40 degrees. The mean temperature of the driest quarter is 26.66 degrees. The mean temperature of the warmest quarter is 29.73 degrees. The mean temperature of the coldest quarter is 26.66 degrees. The annual precipitation is 333.0 mm. The precipitation of the wettest month is 93.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.95. The precipitation of the wettest quarter is 176.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 116.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 74", + "(C) 111", + "(D) 177", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734557_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0433", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.283353 and latitude -0.757635 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 140", + "(B) 59", + "(C) 27", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19449207_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0434", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.584468 and latitude -0.349529 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.23 degrees. The mean diurnal range is 12.53 degrees. The isothermality is 82.31. The temperature seasonality (100 times the standard deviation) is 70.01. The max temperature of the warmest month is 22.62 degrees. The min temperature of the coldest month is 7.39 degrees. The temperature annual range is 15.23 degrees. The mean temperature of the wettest quarter is 14.39 degrees. The mean temperature of the driest quarter is 14.68 degrees. The mean temperature of the warmest quarter is 15.10 degrees. The mean temperature of the coldest quarter is 13.35 degrees. The annual precipitation is 1397.0 mm. The precipitation of the wettest month is 193.0 mm. The precipitation of the driest month is 47.0 mm. The precipitation seasonality (coefficient of variation) is 43.71. The precipitation of the wettest quarter is 492.0 mm. The precipitation of the driest quarter is 171.0 mm. The precipitation of the warmest quarter is 331.0 mm. The precipitation of the coldest quarter is 460.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 37", + "(C) 80", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20352553_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0435", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.301660 and latitude -0.819634 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 6", + "(C) 173", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12259577_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0436", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.192333 and latitude -0.483834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 52", + "(C) 19", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20782442_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0437", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461087 and latitude -0.740838 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 24", + "(C) 62", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15448089_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0438", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.095954 and latitude -0.458151 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 40", + "(C) 1", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21362294_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0439", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.747138 and latitude -3.955569 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 138", + "(B) 68", + "(C) 112", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7340242_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0440", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108043 and latitude -0.295206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 22", + "(C) 150", + "(D) 58", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4259135_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0441", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.283472 and latitude -0.732351 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 171", + "(C) 16", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21002856_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0442", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.957074 and latitude -0.224339 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 185", + "(C) 111", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8213719_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0443", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456529 and latitude -0.738829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 311", + "(B) 110", + "(C) 32", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20255070_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0444", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.741623 and latitude -3.608959 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 23", + "(C) 221", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1461598_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0445", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307068 and latitude -0.719586 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 123", + "(B) 24", + "(C) 132", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2126423_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0446", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428964 and latitude -0.629723 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 38", + "(C) 22", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6998556_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0447", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.494656 and latitude -0.575474 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 5", + "(C) 64", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025970_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0448", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.416637 and latitude -0.725118 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 20", + "(C) 146", + "(D) 159", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10009116_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0449", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.877869 and latitude -3.632665 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.32 degrees. The mean diurnal range is 10.16 degrees. The isothermality is 69.34. The temperature seasonality (100 times the standard deviation) is 150.42. The max temperature of the warmest month is 31.94 degrees. The min temperature of the coldest month is 17.29 degrees. The temperature annual range is 14.65 degrees. The mean temperature of the wettest quarter is 24.78 degrees. The mean temperature of the driest quarter is 22.40 degrees. The mean temperature of the warmest quarter is 25.97 degrees. The mean temperature of the coldest quarter is 22.36 degrees. The annual precipitation is 730.0 mm. The precipitation of the wettest month is 117.0 mm. The precipitation of the driest month is 21.0 mm. The precipitation seasonality (coefficient of variation) is 58.42. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 72.0 mm. The precipitation of the warmest quarter is 226.0 mm. The precipitation of the coldest quarter is 85.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 173", + "(B) 22", + "(C) 88", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1875249_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0450", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.126686 and latitude -0.361053 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 152", + "(C) 74", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6525805_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0451", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.461958 and latitude -0.739721 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 7", + "(C) 90", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16981110_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0452", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.481020 and latitude -0.629872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 23", + "(C) 89", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11533438_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0453", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.215680 and latitude -0.504725 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 114", + "(B) 138", + "(C) 17", + "(D) 56", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10084302_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0454", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.256105 and latitude -0.817704 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 24", + "(C) 89", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22415482_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0455", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.607782 and latitude -2.975250 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 1", + "(C) 30", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4921609_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0456", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.472665 and latitude -0.629135 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 129", + "(C) 24", + "(D) 5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11371034_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0457", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492129 and latitude -0.572573 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 107", + "(C) 15", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778240_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0458", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.472955 and latitude 0.000007 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.41 degrees. The mean diurnal range is 10.47 degrees. The isothermality is 74.66. The temperature seasonality (100 times the standard deviation) is 111.40. The max temperature of the warmest month is 34.82 degrees. The min temperature of the coldest month is 20.80 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 27.52 degrees. The mean temperature of the driest quarter is 25.94 degrees. The mean temperature of the warmest quarter is 28.79 degrees. The mean temperature of the coldest quarter is 25.94 degrees. The annual precipitation is 318.0 mm. The precipitation of the wettest month is 96.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 121.15. The precipitation of the wettest quarter is 175.0 mm. The precipitation of the driest quarter is 4.0 mm. The precipitation of the warmest quarter is 118.0 mm. The precipitation of the coldest quarter is 4.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 82", + "(C) 9", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13474964_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0459", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.893886 and latitude -1.640236 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 30", + "(C) 18", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17524706_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0460", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.105425 and latitude -0.279641 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 24", + "(B) 8", + "(C) 35", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14796716_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0461", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120032 and latitude -0.395452 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 365", + "(B) 67", + "(C) 66", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17011328_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0462", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120495 and latitude -0.366381 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 114", + "(B) 23", + "(C) 121", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17705838_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0463", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469800 and latitude -0.597199 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 30", + "(C) 57", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22469746_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0464", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.740000 and latitude -3.928000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 17", + "(C) 98", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6200626_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0465", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.113897 and latitude -0.415413 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 80", + "(C) 16", + "(D) 376", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214606_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0466", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.089000 and latitude -0.307217 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 138", + "(C) 27", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10206039_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0467", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.309045 and latitude -0.144258 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 51", + "(C) 9", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13918587_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0468", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450073 and latitude -0.742200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 114", + "(C) 69", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20973630_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0469", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.403588 and latitude -0.760829 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 26", + "(C) 59", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1770518_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0470", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.961799 and latitude -0.234116 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.90 degrees. The mean diurnal range is 12.99 degrees. The isothermality is 84.42. The temperature seasonality (100 times the standard deviation) is 66.83. The max temperature of the warmest month is 30.95 degrees. The min temperature of the coldest month is 15.57 degrees. The temperature annual range is 15.38 degrees. The mean temperature of the wettest quarter is 23.12 degrees. The mean temperature of the driest quarter is 23.54 degrees. The mean temperature of the warmest quarter is 23.76 degrees. The mean temperature of the coldest quarter is 22.03 degrees. The annual precipitation is 1176.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 54.0 mm. The precipitation seasonality (coefficient of variation) is 38.09. The precipitation of the wettest quarter is 464.0 mm. The precipitation of the driest quarter is 218.0 mm. The precipitation of the warmest quarter is 260.0 mm. The precipitation of the coldest quarter is 239.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 57", + "(C) 22", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19362992_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0471", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.160199 and latitude -0.584321 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 25", + "(C) 88", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5656068_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0472", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.307308 and latitude -0.142926 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 132", + "(B) 311", + "(C) 97", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12832036_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0473", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.460528 and latitude -0.739498 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 42", + "(B) 185", + "(C) 29", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21640693_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0474", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.603889 and latitude -0.673041 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.91 degrees. The mean diurnal range is 10.14 degrees. The isothermality is 71.62. The temperature seasonality (100 times the standard deviation) is 130.14. The max temperature of the warmest month is 35.39 degrees. The min temperature of the coldest month is 21.24 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 28.23 degrees. The mean temperature of the driest quarter is 26.16 degrees. The mean temperature of the warmest quarter is 29.46 degrees. The mean temperature of the coldest quarter is 26.16 degrees. The annual precipitation is 417.0 mm. The precipitation of the wettest month is 110.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 103.09. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 145.0 mm. The precipitation of the coldest quarter is 16.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 4", + "(C) 54", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974502_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0475", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.313000 and latitude -2.304400 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 27.09 degrees. The mean diurnal range is 7.52 degrees. The isothermality is 66.86. The temperature seasonality (100 times the standard deviation) is 121.90. The max temperature of the warmest month is 33.17 degrees. The min temperature of the coldest month is 21.92 degrees. The temperature annual range is 11.25 degrees. The mean temperature of the wettest quarter is 27.14 degrees. The mean temperature of the driest quarter is 28.26 degrees. The mean temperature of the warmest quarter is 28.48 degrees. The mean temperature of the coldest quarter is 25.50 degrees. The annual precipitation is 806.0 mm. The precipitation of the wettest month is 149.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 56.60. The precipitation of the wettest quarter is 348.0 mm. The precipitation of the driest quarter is 81.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 160.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 31", + "(C) 105", + "(D) 114", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3059463_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0476", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.032930 and latitude 0.718093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 108", + "(C) 256", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10504169_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0477", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.513280 and latitude -0.193907 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 65", + "(C) 67", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462536_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0478", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.615017 and latitude -2.982955 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 3", + "(B) 17", + "(C) 1", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12065665_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0479", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.026337 and latitude -2.514263 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.85 degrees. The mean diurnal range is 12.31 degrees. The isothermality is 72.62. The temperature seasonality (100 times the standard deviation) is 142.97. The max temperature of the warmest month is 30.87 degrees. The min temperature of the coldest month is 13.92 degrees. The temperature annual range is 16.95 degrees. The mean temperature of the wettest quarter is 22.68 degrees. The mean temperature of the driest quarter is 20.07 degrees. The mean temperature of the warmest quarter is 23.33 degrees. The mean temperature of the coldest quarter is 19.80 degrees. The annual precipitation is 587.0 mm. The precipitation of the wettest month is 125.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 81.83. The precipitation of the wettest quarter is 262.0 mm. The precipitation of the driest quarter is 12.0 mm. The precipitation of the warmest quarter is 177.0 mm. The precipitation of the coldest quarter is 15.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 16", + "(C) 28", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7148979_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0480", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946283 and latitude -0.063598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 105", + "(B) 80", + "(C) 14", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22563197_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0481", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250000 and latitude -0.432800 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 24", + "(B) 7", + "(C) 249", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11221555_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0482", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.463341 and latitude 0.424458 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.07 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 81.77. The temperature seasonality (100 times the standard deviation) is 79.91. The max temperature of the warmest month is 24.33 degrees. The min temperature of the coldest month is 9.18 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 15.02 degrees. The mean temperature of the driest quarter is 16.53 degrees. The mean temperature of the warmest quarter is 17.04 degrees. The mean temperature of the coldest quarter is 15.02 degrees. The annual precipitation is 1155.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 49.05. The precipitation of the wettest quarter is 405.0 mm. The precipitation of the driest quarter is 131.0 mm. The precipitation of the warmest quarter is 294.0 mm. The precipitation of the coldest quarter is 405.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 146", + "(B) 113", + "(C) 376", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290835_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0483", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326134 and latitude -0.717464 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 21", + "(C) 9", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17291269_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0484", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.684506 and latitude -4.058453 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 72", + "(C) 13", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20451066_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0485", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453735 and latitude -0.729773 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 50", + "(B) 153", + "(C) 29", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15873929_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0486", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.878873 and latitude 1.048376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 121", + "(C) 26", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8685118_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0487", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.083000 and latitude -0.366000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 22", + "(C) 138", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11222896_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0488", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.487602 and latitude -0.699514 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 72", + "(B) 122", + "(C) 21", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436304_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0489", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.628074 and latitude -0.490381 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 31", + "(C) 102", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778305_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0490", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.665400 and latitude -4.078700 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.02 degrees. The mean diurnal range is 8.24 degrees. The isothermality is 64.97. The temperature seasonality (100 times the standard deviation) is 148.61. The max temperature of the warmest month is 32.62 degrees. The min temperature of the coldest month is 19.94 degrees. The temperature annual range is 12.68 degrees. The mean temperature of the wettest quarter is 25.92 degrees. The mean temperature of the driest quarter is 27.61 degrees. The mean temperature of the warmest quarter is 27.65 degrees. The mean temperature of the coldest quarter is 24.11 degrees. The annual precipitation is 1085.0 mm. The precipitation of the wettest month is 251.0 mm. The precipitation of the driest month is 16.0 mm. The precipitation seasonality (coefficient of variation) is 70.27. The precipitation of the wettest quarter is 517.0 mm. The precipitation of the driest quarter is 99.0 mm. The precipitation of the warmest quarter is 243.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 42", + "(B) 19", + "(C) 249", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3061002_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0491", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.496000 and latitude -0.574000 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 98", + "(C) 4", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17120227_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0492", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420364 and latitude -0.772920 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 18", + "(C) 271", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10746405_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0493", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.003179 and latitude -1.382342 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 311", + "(B) 3", + "(C) 23", + "(D) 278", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17063854_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0494", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.723417 and latitude -4.025348 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 41", + "(C) 10", + "(D) 140", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10702920_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0495", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.358615 and latitude -0.746634 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 14", + "(C) 58", + "(D) 138", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563404_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0496", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474561 and latitude -0.889059 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 35", + "(C) 35", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8149007_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0497", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.205574 and latitude -0.523311 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 311", + "(B) 159", + "(C) 24", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16126491_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0498", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.719954 and latitude -4.018641 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 45", + "(C) 100", + "(D) 278", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070702_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0499", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.421278 and latitude -0.675163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 14", + "(C) 24", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18607968_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0500", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493883 and latitude -0.573706 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 1", + "(C) 33", + "(D) 77", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19693753_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0501", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.686870 and latitude -0.489771 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 117", + "(C) 34", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16889770_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0502", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492103 and latitude -0.572615 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 20", + "(C) 74", + "(D) 505", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18099519_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0503", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.382245 and latitude -0.719936 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 45", + "(C) 15", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563225_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0504", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.087110 and latitude 2.708801 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 26.00 degrees. The mean diurnal range is 10.50 degrees. The isothermality is 73.28. The temperature seasonality (100 times the standard deviation) is 119.24. The max temperature of the warmest month is 33.35 degrees. The min temperature of the coldest month is 19.02 degrees. The temperature annual range is 14.33 degrees. The mean temperature of the wettest quarter is 26.83 degrees. The mean temperature of the driest quarter is 24.45 degrees. The mean temperature of the warmest quarter is 27.49 degrees. The mean temperature of the coldest quarter is 24.45 degrees. The annual precipitation is 270.0 mm. The precipitation of the wettest month is 80.0 mm. The precipitation of the driest month is 0.0 mm. The precipitation seasonality (coefficient of variation) is 109.07. The precipitation of the wettest quarter is 132.0 mm. The precipitation of the driest quarter is 2.0 mm. The precipitation of the warmest quarter is 56.0 mm. The precipitation of the coldest quarter is 2.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 23", + "(C) 266", + "(D) 270", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22790390_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0505", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.471482 and latitude -0.828351 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 134", + "(C) 1", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10343530_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0506", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.217718 and latitude -0.407208 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 59", + "(C) 221", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791987_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0507", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117899 and latitude -0.380129 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 68", + "(B) 376", + "(C) 17", + "(D) 32", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10746561_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0508", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493826 and latitude -0.574831 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 42", + "(C) 113", + "(D) 21", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20232869_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0509", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.207549 and latitude -0.387451 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 14", + "(C) 207", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20791984_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0510", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444822 and latitude -0.724114 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 32", + "(C) 83", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16776594_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0511", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.261919 and latitude -0.448123 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 89", + "(B) 26", + "(C) 49", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8442955_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0512", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419407 and latitude -0.591604 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 7", + "(C) 24", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6864111_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0513", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452536 and latitude -0.737041 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 61", + "(C) 249", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20290844_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0514", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.410863 and latitude -0.767313 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 146", + "(C) 29", + "(D) 132", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7725548_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0515", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.928646 and latitude 2.241613 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.99 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 81.08. The temperature seasonality (100 times the standard deviation) is 79.21. The max temperature of the warmest month is 30.29 degrees. The min temperature of the coldest month is 15.88 degrees. The temperature annual range is 14.40 degrees. The mean temperature of the wettest quarter is 23.83 degrees. The mean temperature of the driest quarter is 22.08 degrees. The mean temperature of the warmest quarter is 24.02 degrees. The mean temperature of the coldest quarter is 22.01 degrees. The annual precipitation is 347.0 mm. The precipitation of the wettest month is 81.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 78.03. The precipitation of the wettest quarter is 164.0 mm. The precipitation of the driest quarter is 27.0 mm. The precipitation of the warmest quarter is 139.0 mm. The precipitation of the coldest quarter is 31.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 19", + "(B) 271", + "(C) 38", + "(D) 78", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15234248_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0516", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.465658 and latitude -0.693972 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 77", + "(C) 16", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19436290_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0517", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425885 and latitude -0.750477 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 72", + "(C) 8", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5289638_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0518", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.758317 and latitude -3.569227 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 54", + "(C) 25", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12511852_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0519", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298536 and latitude -0.666360 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 88", + "(C) 32", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15283938_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0520", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125347 and latitude -0.311612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 89", + "(B) 159", + "(C) 16", + "(D) 61", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21097299_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0521", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952315 and latitude 0.009791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 28", + "(C) 17", + "(D) 249", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925707_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0522", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.298562 and latitude -0.665901 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 87", + "(C) 18", + "(D) 122", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15145101_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0523", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.187452 and latitude -0.499206 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 80", + "(C) 6", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284271_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0524", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.396730 and latitude -0.803697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 13", + "(B) 88", + "(C) 95", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12596376_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0525", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.377389 and latitude -0.820922 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 40", + "(C) 12", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17374004_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0526", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111946 and latitude -0.402734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 153", + "(C) 13", + "(D) 376", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20726818_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0527", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.131025 and latitude -0.310532 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 48", + "(C) 42", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7874277_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0528", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.449460 and latitude -0.717641 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 10", + "(C) 9", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19317171_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0529", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988431 and latitude -0.219000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 17", + "(C) 53", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119851_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0530", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444690 and latitude -0.716908 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 505", + "(C) 18", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15474902_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0531", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.577802 and latitude 0.334909 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 18", + "(C) 28", + "(D) 100", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5120073_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0532", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465083 and latitude -0.595619 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 134", + "(C) 28", + "(D) 12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21686375_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0533", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.616972 and latitude -0.559458 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 256", + "(C) 26", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15208954_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0534", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.400280 and latitude -0.772281 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 15", + "(C) 98", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17539501_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0535", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.113925 and latitude -0.438052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 15", + "(B) 365", + "(C) 55", + "(D) 121", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819665_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0536", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.333855 and latitude -0.830245 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 45", + "(C) 13", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3754839_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0537", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.736928 and latitude -3.980726 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 270", + "(C) 14", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14765490_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0538", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108072 and latitude -0.309220 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 1", + "(C) 16", + "(D) 271", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4304151_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0539", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.919813 and latitude 2.097865 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.41 degrees. The mean diurnal range is 10.92 degrees. The isothermality is 80.29. The temperature seasonality (100 times the standard deviation) is 79.33. The max temperature of the warmest month is 27.37 degrees. The min temperature of the coldest month is 13.77 degrees. The temperature annual range is 13.60 degrees. The mean temperature of the wettest quarter is 21.29 degrees. The mean temperature of the driest quarter is 19.51 degrees. The mean temperature of the warmest quarter is 21.46 degrees. The mean temperature of the coldest quarter is 19.45 degrees. The annual precipitation is 473.0 mm. The precipitation of the wettest month is 106.0 mm. The precipitation of the driest month is 9.0 mm. The precipitation seasonality (coefficient of variation) is 70.90. The precipitation of the wettest quarter is 212.0 mm. The precipitation of the driest quarter is 51.0 mm. The precipitation of the warmest quarter is 178.0 mm. The precipitation of the coldest quarter is 58.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 21", + "(C) 92", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3633236_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0540", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.354062 and latitude -0.563343 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 256", + "(B) 92", + "(C) 140", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22693049_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0541", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.522774 and latitude -0.671358 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.88 degrees. The mean diurnal range is 12.63 degrees. The isothermality is 77.21. The temperature seasonality (100 times the standard deviation) is 104.78. The max temperature of the warmest month is 21.80 degrees. The min temperature of the coldest month is 5.44 degrees. The temperature annual range is 16.36 degrees. The mean temperature of the wettest quarter is 13.82 degrees. The mean temperature of the driest quarter is 11.49 degrees. The mean temperature of the warmest quarter is 14.03 degrees. The mean temperature of the coldest quarter is 11.42 degrees. The annual precipitation is 1179.0 mm. The precipitation of the wettest month is 219.0 mm. The precipitation of the driest month is 49.0 mm. The precipitation seasonality (coefficient of variation) is 53.00. The precipitation of the wettest quarter is 500.0 mm. The precipitation of the driest quarter is 174.0 mm. The precipitation of the warmest quarter is 392.0 mm. The precipitation of the coldest quarter is 179.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 16", + "(C) 4", + "(D) 108", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22529478_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0542", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.398854 and latitude -0.801637 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 168", + "(C) 27", + "(D) 82", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19019798_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0543", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.798427 and latitude -3.808263 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 159", + "(C) 505", + "(D) 27", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7049464_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0544", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.323368 and latitude -0.815791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 44", + "(C) 23", + "(D) 108", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925737_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0545", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450879 and latitude -0.739549 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 27", + "(C) 58", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21073073_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0546", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.656872 and latitude -0.297796 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 22", + "(C) 84", + "(D) 135", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20348961_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0547", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285811 and latitude 0.491439 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 17", + "(C) 45", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4272139_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0548", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.964990 and latitude -0.167455 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 152", + "(B) 278", + "(C) 16", + "(D) 177", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12096559_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0549", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.320640 and latitude -0.669453 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 26", + "(C) 139", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3224252_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0550", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.428400 and latitude -0.725289 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 70", + "(C) 32", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19025953_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0551", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.852259 and latitude 1.065839 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 129", + "(C) 32", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6540695_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0552", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424205 and latitude -0.769019 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 26", + "(C) 376", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8279615_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0553", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.720935 and latitude -2.257880 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.40 degrees. The mean diurnal range is 11.22 degrees. The isothermality is 69.37. The temperature seasonality (100 times the standard deviation) is 144.94. The max temperature of the warmest month is 30.83 degrees. The min temperature of the coldest month is 14.66 degrees. The temperature annual range is 16.17 degrees. The mean temperature of the wettest quarter is 22.92 degrees. The mean temperature of the driest quarter is 20.33 degrees. The mean temperature of the warmest quarter is 23.99 degrees. The mean temperature of the coldest quarter is 20.33 degrees. The annual precipitation is 604.0 mm. The precipitation of the wettest month is 165.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 104.51. The precipitation of the wettest quarter is 316.0 mm. The precipitation of the driest quarter is 7.0 mm. The precipitation of the warmest quarter is 217.0 mm. The precipitation of the coldest quarter is 7.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 56", + "(C) 28", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7302297_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0554", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.281625 and latitude -0.758971 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.74 degrees. The mean diurnal range is 11.97 degrees. The isothermality is 82.02. The temperature seasonality (100 times the standard deviation) is 63.67. The max temperature of the warmest month is 29.20 degrees. The min temperature of the coldest month is 14.60 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.05 degrees. The mean temperature of the driest quarter is 20.89 degrees. The mean temperature of the warmest quarter is 22.52 degrees. The mean temperature of the coldest quarter is 20.89 degrees. The annual precipitation is 1230.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 39.0 mm. The precipitation seasonality (coefficient of variation) is 49.65. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 152.0 mm. The precipitation of the warmest quarter is 261.0 mm. The precipitation of the coldest quarter is 152.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 17", + "(D) 7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6563280_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0555", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.085625 and latitude -0.315834 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 27", + "(C) 47", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6610312_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0556", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.084123 and latitude -0.310148 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 173", + "(C) 26", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12667989_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0557", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952508 and latitude 0.009905 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 159", + "(C) 16", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925726_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0558", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.730919 and latitude -3.989027 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 51", + "(C) 31", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17760266_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0559", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.576116 and latitude -3.166533 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 168", + "(C) 21", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22550133_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0560", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120505 and latitude -0.313568 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 40", + "(B) 26", + "(C) 122", + "(D) 249", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683607_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0561", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.250511 and latitude -0.406276 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 114", + "(C) 4", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10900737_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0562", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285800 and latitude 0.491500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 67", + "(C) 57", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9205333_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0563", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.582116 and latitude 0.349416 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 13", + "(C) 95", + "(D) 85", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10223384_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0564", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.270378 and latitude -0.816443 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 99", + "(C) 16", + "(D) 259", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1770521_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0565", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.903004 and latitude -3.083243 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.19 degrees. The mean diurnal range is 7.97 degrees. The isothermality is 67.30. The temperature seasonality (100 times the standard deviation) is 123.33. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 19.64 degrees. The temperature annual range is 11.84 degrees. The mean temperature of the wettest quarter is 25.21 degrees. The mean temperature of the driest quarter is 26.43 degrees. The mean temperature of the warmest quarter is 26.64 degrees. The mean temperature of the coldest quarter is 23.57 degrees. The annual precipitation is 884.0 mm. The precipitation of the wettest month is 187.0 mm. The precipitation of the driest month is 12.0 mm. The precipitation seasonality (coefficient of variation) is 61.39. The precipitation of the wettest quarter is 385.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 183.0 mm. The precipitation of the coldest quarter is 188.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 91", + "(C) 7", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18990924_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0566", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.848626 and latitude -1.687800 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 80", + "(C) 8", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17121786_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0567", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.755376 and latitude 0.568924 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.52 degrees. The mean diurnal range is 12.84 degrees. The isothermality is 83.19. The temperature seasonality (100 times the standard deviation) is 74.64. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 16.30 degrees. The temperature annual range is 15.43 degrees. The mean temperature of the wettest quarter is 23.34 degrees. The mean temperature of the driest quarter is 22.72 degrees. The mean temperature of the warmest quarter is 24.38 degrees. The mean temperature of the coldest quarter is 22.72 degrees. The annual precipitation is 533.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 3.0 mm. The precipitation seasonality (coefficient of variation) is 108.08. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 199.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 75", + "(C) 139", + "(D) 29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22414217_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0568", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432900 and latitude -0.714300 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 49", + "(C) 150", + "(D) 1", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10608444_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0569", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492268 and latitude -0.572895 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 53", + "(C) 14", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10494075_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0570", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.291267 and latitude 0.498667 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 266", + "(C) 139", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7716763_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0571", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469527 and latitude -0.596445 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 37", + "(C) 20", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14258662_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0572", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.781843 and latitude -3.596470 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 95", + "(C) 20", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12531865_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0573", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.060133 and latitude -0.354307 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 34", + "(C) 110", + "(D) 311", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864288_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0574", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.114387 and latitude -0.286709 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 52", + "(C) 29", + "(D) 138", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19526025_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0575", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.091990 and latitude 0.537357 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.14 degrees. The mean diurnal range is 12.73 degrees. The isothermality is 82.07. The temperature seasonality (100 times the standard deviation) is 79.15. The max temperature of the warmest month is 26.58 degrees. The min temperature of the coldest month is 11.07 degrees. The temperature annual range is 15.51 degrees. The mean temperature of the wettest quarter is 17.14 degrees. The mean temperature of the driest quarter is 18.58 degrees. The mean temperature of the warmest quarter is 19.14 degrees. The mean temperature of the coldest quarter is 17.14 degrees. The annual precipitation is 1225.0 mm. The precipitation of the wettest month is 200.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 52.85. The precipitation of the wettest quarter is 491.0 mm. The precipitation of the driest quarter is 121.0 mm. The precipitation of the warmest quarter is 264.0 mm. The precipitation of the coldest quarter is 491.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 28", + "(C) 45", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15874060_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0576", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308579 and latitude -0.145117 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 33", + "(B) 3", + "(C) 23", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19266793_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0577", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474706 and latitude -0.554303 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 114", + "(C) 6", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21213112_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0578", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.648853 and latitude -0.508865 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 38", + "(C) 108", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22778924_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0579", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.106168 and latitude -0.403316 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 12", + "(B) 23", + "(C) 5", + "(D) 112", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4122705_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0580", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.373847 and latitude -0.802140 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.52 degrees. The mean diurnal range is 11.88 degrees. The isothermality is 81.03. The temperature seasonality (100 times the standard deviation) is 65.91. The max temperature of the warmest month is 29.10 degrees. The min temperature of the coldest month is 14.44 degrees. The temperature annual range is 14.66 degrees. The mean temperature of the wettest quarter is 21.88 degrees. The mean temperature of the driest quarter is 20.65 degrees. The mean temperature of the warmest quarter is 22.33 degrees. The mean temperature of the coldest quarter is 20.65 degrees. The annual precipitation is 1388.0 mm. The precipitation of the wettest month is 228.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 45.97. The precipitation of the wettest quarter is 550.0 mm. The precipitation of the driest quarter is 214.0 mm. The precipitation of the warmest quarter is 281.0 mm. The precipitation of the coldest quarter is 214.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 64", + "(B) 63", + "(C) 27", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6520979_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0581", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.430243 and latitude -0.629545 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 146", + "(C) 126", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5307845_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0582", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.401900 and latitude -0.767200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 38", + "(C) 278", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10561143_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0583", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.129222 and latitude -0.304008 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 22", + "(C) 249", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11887905_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0584", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.693575 and latitude -4.047847 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 27", + "(C) 278", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13608231_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0585", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490715 and latitude -0.595653 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 30", + "(C) 92", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10859569_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0586", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.034991 and latitude -0.269870 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 92", + "(C) 43", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5533753_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0587", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.263924 and latitude -0.821967 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 376", + "(C) 22", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756371_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0588", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425708 and latitude -0.720986 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 40", + "(B) 51", + "(C) 15", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20832213_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0589", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.108066 and latitude -0.306113 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 111", + "(C) 14", + "(D) 85", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5517500_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0590", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.467638 and latitude -0.595870 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 32", + "(B) 75", + "(C) 13", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11376055_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0591", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425924 and latitude -0.618675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 1", + "(C) 14", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L23520785_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0592", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.216155 and latitude -0.435056 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 102", + "(C) 278", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4283240_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0593", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.410694 and latitude -0.777785 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 70", + "(B) 62", + "(C) 28", + "(D) 112", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14289607_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0594", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.416544 and latitude -0.798903 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 259", + "(C) 64", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8692210_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0595", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.419316 and latitude 0.685222 in the state of Western, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.22 degrees. The mean diurnal range is 12.17 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.56. The max temperature of the warmest month is 29.24 degrees. The min temperature of the coldest month is 14.49 degrees. The temperature annual range is 14.75 degrees. The mean temperature of the wettest quarter is 21.12 degrees. The mean temperature of the driest quarter is 21.89 degrees. The mean temperature of the warmest quarter is 22.17 degrees. The mean temperature of the coldest quarter is 20.41 degrees. The annual precipitation is 1520.0 mm. The precipitation of the wettest month is 234.0 mm. The precipitation of the driest month is 52.0 mm. The precipitation seasonality (coefficient of variation) is 42.70. The precipitation of the wettest quarter is 580.0 mm. The precipitation of the driest quarter is 190.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 365.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 43", + "(C) 60", + "(D) 134", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15752435_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0596", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308712 and latitude -0.144087 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 13.76 degrees. The mean diurnal range is 13.15 degrees. The isothermality is 80.49. The temperature seasonality (100 times the standard deviation) is 73.29. The max temperature of the warmest month is 22.58 degrees. The min temperature of the coldest month is 6.24 degrees. The temperature annual range is 16.33 degrees. The mean temperature of the wettest quarter is 12.95 degrees. The mean temperature of the driest quarter is 14.02 degrees. The mean temperature of the warmest quarter is 14.71 degrees. The mean temperature of the coldest quarter is 12.86 degrees. The annual precipitation is 1107.0 mm. The precipitation of the wettest month is 158.0 mm. The precipitation of the driest month is 30.0 mm. The precipitation seasonality (coefficient of variation) is 47.17. The precipitation of the wettest quarter is 390.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 378.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 14", + "(B) 32", + "(C) 112", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20920735_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0597", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.417357 and latitude -0.667544 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 266", + "(C) 63", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19266636_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0598", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362797 and latitude -0.860224 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 88", + "(B) 29", + "(C) 64", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16367492_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0599", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.703054 and latitude -4.044854 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 153", + "(B) 85", + "(C) 185", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17029554_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0600", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489093 and latitude -0.625338 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 80", + "(C) 25", + "(D) 259", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11604894_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0601", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.733470 and latitude -3.989965 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 45", + "(C) 269", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12524048_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0602", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.282690 and latitude -0.734770 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 505", + "(B) 52", + "(C) 41", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4700360_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0603", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418351 and latitude -0.720677 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 90", + "(C) 38", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22239295_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0604", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.465223 and latitude -0.747529 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 95", + "(B) 249", + "(C) 112", + "(D) 56", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10061779_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0605", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411910 and latitude -0.763410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 278", + "(B) 38", + "(C) 16", + "(D) 505", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4929439_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0606", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.090260 and latitude -0.356779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 505", + "(B) 135", + "(C) 140", + "(D) 14", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L920937_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0607", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.822843 and latitude -3.824118 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 117", + "(B) 207", + "(C) 54", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6259752_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0608", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.379367 and latitude 0.303932 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.77 degrees. The mean diurnal range is 12.44 degrees. The isothermality is 82.15. The temperature seasonality (100 times the standard deviation) is 77.61. The max temperature of the warmest month is 24.11 degrees. The min temperature of the coldest month is 8.96 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 14.77 degrees. The mean temperature of the driest quarter is 16.24 degrees. The mean temperature of the warmest quarter is 16.72 degrees. The mean temperature of the coldest quarter is 14.76 degrees. The annual precipitation is 1204.0 mm. The precipitation of the wettest month is 189.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 50.25. The precipitation of the wettest quarter is 449.0 mm. The precipitation of the driest quarter is 137.0 mm. The precipitation of the warmest quarter is 289.0 mm. The precipitation of the coldest quarter is 441.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 74", + "(C) 88", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8123512_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0609", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334920 and latitude -0.825791 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 98", + "(C) 70", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16490176_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0610", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.122811 and latitude -0.414418 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 88", + "(B) 111", + "(C) 26", + "(D) 103", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20161142_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0611", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.597244 and latitude -3.122050 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.72 degrees. The mean diurnal range is 8.69 degrees. The isothermality is 67.94. The temperature seasonality (100 times the standard deviation) is 127.83. The max temperature of the warmest month is 32.41 degrees. The min temperature of the coldest month is 19.62 degrees. The temperature annual range is 12.80 degrees. The mean temperature of the wettest quarter is 26.09 degrees. The mean temperature of the driest quarter is 24.10 degrees. The mean temperature of the warmest quarter is 27.19 degrees. The mean temperature of the coldest quarter is 24.10 degrees. The annual precipitation is 736.0 mm. The precipitation of the wettest month is 109.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 51.22. The precipitation of the wettest quarter is 280.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 169.0 mm. The precipitation of the coldest quarter is 102.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 28", + "(C) 3", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14898277_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0612", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.124747 and latitude -0.388680 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 168", + "(B) 85", + "(C) 97", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20174419_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0613", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.306596 and latitude -0.885051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 25", + "(C) 27", + "(D) 271", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L989976_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0614", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.459984 and latitude -0.738214 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 35", + "(B) 57", + "(C) 4", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16767027_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0615", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726754 and latitude -3.999883 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 270", + "(C) 5", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14558153_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0616", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.312098 and latitude 0.584058 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 133", + "(C) 28", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5186646_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0617", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.221335 and latitude -0.406675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 63", + "(B) 87", + "(C) 11", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1793672_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0618", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.712955 and latitude -3.948034 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 123", + "(B) 62", + "(C) 64", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11436924_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0619", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116630 and latitude -0.410553 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 65", + "(C) 45", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17819859_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0620", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.571038 and latitude -0.607497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 31", + "(C) 58", + "(D) 100", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12629846_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0621", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.071567 and latitude -0.315449 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 82", + "(C) 31", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4213876_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0622", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491776 and latitude -0.573038 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 152", + "(C) 38", + "(D) 126", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9240465_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0623", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.119614 and latitude -0.371656 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 120", + "(B) 2", + "(C) 82", + "(D) 140", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2853940_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0624", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 40.109042 and latitude 0.388282 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.43 degrees. The mean diurnal range is 10.72 degrees. The isothermality is 73.81. The temperature seasonality (100 times the standard deviation) is 117.59. The max temperature of the warmest month is 36.23 degrees. The min temperature of the coldest month is 21.71 degrees. The temperature annual range is 14.53 degrees. The mean temperature of the wettest quarter is 28.48 degrees. The mean temperature of the driest quarter is 26.91 degrees. The mean temperature of the warmest quarter is 29.90 degrees. The mean temperature of the coldest quarter is 26.91 degrees. The annual precipitation is 337.0 mm. The precipitation of the wettest month is 98.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 107.78. The precipitation of the wettest quarter is 155.0 mm. The precipitation of the driest quarter is 14.0 mm. The precipitation of the warmest quarter is 132.0 mm. The precipitation of the coldest quarter is 14.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 92", + "(C) 65", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22298211_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0625", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606123 and latitude -2.982345 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 31", + "(B) 16", + "(C) 92", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12053795_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0626", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.695232 and latitude -3.994353 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 37", + "(C) 5", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12525001_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0627", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120086 and latitude -0.361313 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 51", + "(C) 150", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4929449_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0628", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.308900 and latitude 0.582214 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 271", + "(B) 90", + "(C) 17", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6311615_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0629", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.531521 and latitude -0.551474 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 259", + "(C) 98", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11329676_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0630", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444340 and latitude -0.722888 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 126", + "(B) 85", + "(C) 32", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11433400_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0631", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425569 and latitude -0.721061 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 35", + "(B) 37", + "(C) 1", + "(D) 134", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19024969_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0632", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.118175 and latitude -0.414585 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 88", + "(B) 99", + "(C) 87", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17025784_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0633", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262168 and latitude -0.444845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 69", + "(C) 11", + "(D) 82", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5135004_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0634", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.247386 and latitude -0.410272 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 123", + "(C) 46", + "(D) 10", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8829559_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0635", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.713939 and latitude -3.993058 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 259", + "(B) 365", + "(C) 204", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11354641_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0636", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.241899 and latitude -0.404983 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 54", + "(B) 376", + "(C) 91", + "(D) 73", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10006012_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0637", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.848792 and latitude -1.405414 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.05 degrees. The mean diurnal range is 10.94 degrees. The isothermality is 72.39. The temperature seasonality (100 times the standard deviation) is 124.71. The max temperature of the warmest month is 29.91 degrees. The min temperature of the coldest month is 14.80 degrees. The temperature annual range is 15.11 degrees. The mean temperature of the wettest quarter is 22.51 degrees. The mean temperature of the driest quarter is 20.24 degrees. The mean temperature of the warmest quarter is 23.37 degrees. The mean temperature of the coldest quarter is 20.24 degrees. The annual precipitation is 782.0 mm. The precipitation of the wettest month is 239.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 111.95. The precipitation of the wettest quarter is 424.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 275.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 22", + "(C) 87", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22120035_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0638", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486263 and latitude -0.610771 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 83", + "(C) 22", + "(D) 153", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347943_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0639", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.946107 and latitude -0.246093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 311", + "(C) 47", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1462528_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0640", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.365745 and latitude -0.856539 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 56", + "(B) 126", + "(C) 66", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925745_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0641", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.605857 and latitude -2.979885 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 74", + "(C) 30", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12079977_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0642", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.131107 and latitude -0.310540 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 107", + "(C) 42", + "(D) 137", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22962104_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0643", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.731551 and latitude -3.997904 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 137", + "(B) 30", + "(C) 91", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1120356_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0644", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.116701 and latitude -0.410734 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 117", + "(B) 24", + "(C) 6", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17114258_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0645", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.492965 and latitude -0.574878 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 66", + "(C) 33", + "(D) 89", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9952035_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0646", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.082220 and latitude -0.308115 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 36", + "(C) 7", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16475457_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0647", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.444473 and latitude -0.715818 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 82", + "(B) 17", + "(C) 140", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21447351_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0648", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.771205 and latitude -3.943753 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 68", + "(C) 129", + "(D) 97", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3884618_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0649", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.362967 and latitude -0.859180 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.57 degrees. The mean diurnal range is 14.37 degrees. The isothermality is 77.07. The temperature seasonality (100 times the standard deviation) is 120.74. The max temperature of the warmest month is 26.84 degrees. The min temperature of the coldest month is 8.20 degrees. The temperature annual range is 18.64 degrees. The mean temperature of the wettest quarter is 17.38 degrees. The mean temperature of the driest quarter is 15.05 degrees. The mean temperature of the warmest quarter is 17.85 degrees. The mean temperature of the coldest quarter is 14.86 degrees. The annual precipitation is 787.0 mm. The precipitation of the wettest month is 164.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 59.85. The precipitation of the wettest quarter is 349.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 105.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 22", + "(C) 35", + "(D) 113", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17135891_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0650", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.378136 and latitude -0.823002 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 110", + "(B) 1", + "(C) 132", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19744907_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0651", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.537733 and latitude -0.547081 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 67", + "(B) 14", + "(C) 91", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11361405_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0652", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.103821 and latitude -0.308474 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 40", + "(B) 14", + "(C) 15", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2864256_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0653", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.603577 and latitude -2.963005 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 126", + "(C) 58", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12031498_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0654", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.626243 and latitude -0.492575 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 10.81 degrees. The mean diurnal range is 11.68 degrees. The isothermality is 77.14. The temperature seasonality (100 times the standard deviation) is 82.24. The max temperature of the warmest month is 18.97 degrees. The min temperature of the coldest month is 3.82 degrees. The temperature annual range is 15.15 degrees. The mean temperature of the wettest quarter is 11.14 degrees. The mean temperature of the driest quarter is 11.01 degrees. The mean temperature of the warmest quarter is 11.79 degrees. The mean temperature of the coldest quarter is 9.75 degrees. The annual precipitation is 1357.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 42.0 mm. The precipitation seasonality (coefficient of variation) is 36.85. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 186.0 mm. The precipitation of the warmest quarter is 350.0 mm. The precipitation of the coldest quarter is 321.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 13", + "(C) 56", + "(D) 112", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16582946_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0655", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.578382 and latitude -0.608027 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 64", + "(C) 185", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12921572_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0656", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.398392 and latitude -0.765587 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 311", + "(B) 152", + "(C) 121", + "(D) 67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L961800_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0657", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.411198 and latitude -0.777333 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 48", + "(C) 72", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16416313_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0658", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.474390 and latitude -0.561497 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 185", + "(B) 72", + "(C) 38", + "(D) 271", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16228704_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0659", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450697 and latitude -0.741258 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 87", + "(B) 66", + "(C) 2", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20944652_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0660", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.099234 and latitude -0.303565 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 271", + "(C) 3", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4994948_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0661", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337650 and latitude -2.249473 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 31", + "(C) 77", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22572263_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0662", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.386633 and latitude -0.805065 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 68", + "(C) 29", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076206_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0663", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321579 and latitude -0.667457 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 61", + "(B) 36", + "(C) 159", + "(D) 137", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6102152_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0664", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.383973 and latitude -0.817318 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 46", + "(C) 70", + "(D) 259", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15039930_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0665", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.304110 and latitude 0.573945 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 59", + "(B) 43", + "(C) 70", + "(D) 139", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21379647_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0666", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.636223 and latitude -0.502958 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 505", + "(B) 69", + "(C) 83", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10716936_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0667", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.067732 and latitude -0.268997 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 112", + "(C) 13", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930250_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0668", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.338767 and latitude 0.158103 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.22 degrees. The mean diurnal range is 11.34 degrees. The isothermality is 81.65. The temperature seasonality (100 times the standard deviation) is 72.62. The max temperature of the warmest month is 22.82 degrees. The min temperature of the coldest month is 8.93 degrees. The temperature annual range is 13.88 degrees. The mean temperature of the wettest quarter is 14.26 degrees. The mean temperature of the driest quarter is 15.69 degrees. The mean temperature of the warmest quarter is 16.10 degrees. The mean temperature of the coldest quarter is 14.26 degrees. The annual precipitation is 1326.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 47.26. The precipitation of the wettest quarter is 486.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 307.0 mm. The precipitation of the coldest quarter is 486.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 25", + "(C) 8", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8137654_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0669", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.110792 and latitude -0.561781 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 107", + "(B) 58", + "(C) 70", + "(D) 152", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10902833_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0670", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490550 and latitude -0.589737 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 80", + "(B) 43", + "(C) 133", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9954043_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0671", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.351700 and latitude -0.771080 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 376", + "(C) 64", + "(D) 91", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1195069_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0672", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.380350 and latitude -0.804890 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 67", + "(B) 45", + "(C) 69", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3076105_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0673", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424234 and latitude -0.763541 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 49", + "(B) 137", + "(C) 135", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14509122_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0674", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063427 and latitude -0.325958 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 34", + "(C) 45", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6680855_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0675", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.590838 and latitude -2.919183 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 56", + "(C) 68", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060081_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0676", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391460 and latitude -0.810386 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 63", + "(B) 19", + "(C) 37", + "(D) 311", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13019591_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0677", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.587077 and latitude -0.576565 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 99", + "(C) 14", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14813987_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0678", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.489973 and latitude -0.590325 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 150", + "(C) 34", + "(D) 98", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11353714_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0679", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.018205 and latitude -1.424610 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 18", + "(B) 66", + "(C) 221", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16869306_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0680", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.010834 and latitude -0.237932 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 140", + "(C) 98", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17953479_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0681", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431565 and latitude -0.759218 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 126", + "(C) 34", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9905627_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0682", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.955154 and latitude 0.455048 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.43 degrees. The mean diurnal range is 14.77 degrees. The isothermality is 82.21. The temperature seasonality (100 times the standard deviation) is 64.30. The max temperature of the warmest month is 27.63 degrees. The min temperature of the coldest month is 9.67 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 19.26 degrees. The mean temperature of the driest quarter is 18.32 degrees. The mean temperature of the warmest quarter is 19.26 degrees. The mean temperature of the coldest quarter is 17.75 degrees. The annual precipitation is 812.0 mm. The precipitation of the wettest month is 171.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 65.48. The precipitation of the wettest quarter is 345.0 mm. The precipitation of the driest quarter is 90.0 mm. The precipitation of the warmest quarter is 345.0 mm. The precipitation of the coldest quarter is 146.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 68", + "(B) 159", + "(C) 77", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5276557_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0683", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.708925 and latitude -3.531405 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 135", + "(B) 122", + "(C) 10", + "(D) 168", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12801772_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0684", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610410 and latitude -2.982675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 80", + "(C) 177", + "(D) 63", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12021597_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0685", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.730080 and latitude -0.482860 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 134", + "(C) 108", + "(D) 56", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3830979_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0686", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.543245 and latitude -0.548779 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 50", + "(B) 36", + "(C) 19", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11538126_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0687", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.724135 and latitude -4.024563 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 16", + "(C) 61", + "(D) 140", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8930976_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0688", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.485187 and latitude -0.652962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 150", + "(B) 80", + "(C) 66", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12734170_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0689", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425533 and latitude -0.632287 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 63", + "(C) 112", + "(D) 150", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10989694_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0690", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493109 and latitude -0.570587 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 29", + "(B) 204", + "(C) 60", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11117640_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0691", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.803000 and latitude -3.870000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 10", + "(B) 111", + "(C) 38", + "(D) 91", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7738672_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0692", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.450859 and latitude -0.731743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 51", + "(C) 45", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17069045_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0693", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308674 and latitude -0.887838 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.28 degrees. The mean diurnal range is 13.70 degrees. The isothermality is 76.84. The temperature seasonality (100 times the standard deviation) is 115.36. The max temperature of the warmest month is 26.18 degrees. The min temperature of the coldest month is 8.35 degrees. The temperature annual range is 17.83 degrees. The mean temperature of the wettest quarter is 17.09 degrees. The mean temperature of the driest quarter is 14.83 degrees. The mean temperature of the warmest quarter is 17.54 degrees. The mean temperature of the coldest quarter is 14.67 degrees. The annual precipitation is 793.0 mm. The precipitation of the wettest month is 153.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 52.41. The precipitation of the wettest quarter is 340.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 268.0 mm. The precipitation of the coldest quarter is 136.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 4", + "(C) 140", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020812_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0694", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.337927 and latitude -2.245161 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 41", + "(B) 59", + "(C) 129", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18777803_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0695", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.334420 and latitude -0.828872 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 92", + "(B) 132", + "(C) 33", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8838554_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0696", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.634782 and latitude -0.301388 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 33", + "(B) 221", + "(C) 6", + "(D) 91", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20352740_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0697", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.094788 and latitude -0.325321 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 311", + "(C) 80", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22896641_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0698", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321090 and latitude -0.668276 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 107", + "(C) 152", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298525_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0699", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.073791 and latitude -0.334946 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 33", + "(B) 153", + "(C) 75", + "(D) 83", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17278719_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0700", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431027 and latitude -0.717178 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 138", + "(C) 134", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15684869_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0701", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.564085 and latitude -0.562197 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 14", + "(C) 18", + "(D) 57", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11134929_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0702", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490027 and latitude -0.587858 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 177", + "(B) 108", + "(C) 4", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294580_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0703", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.871250 and latitude -1.671304 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 5", + "(C) 64", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22138528_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0704", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.647223 and latitude -0.293334 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.81 degrees. The mean diurnal range is 12.40 degrees. The isothermality is 82.52. The temperature seasonality (100 times the standard deviation) is 69.24. The max temperature of the warmest month is 23.04 degrees. The min temperature of the coldest month is 8.01 degrees. The temperature annual range is 15.02 degrees. The mean temperature of the wettest quarter is 14.97 degrees. The mean temperature of the driest quarter is 15.25 degrees. The mean temperature of the warmest quarter is 15.66 degrees. The mean temperature of the coldest quarter is 13.92 degrees. The annual precipitation is 1264.0 mm. The precipitation of the wettest month is 181.0 mm. The precipitation of the driest month is 43.0 mm. The precipitation seasonality (coefficient of variation) is 44.59. The precipitation of the wettest quarter is 438.0 mm. The precipitation of the driest quarter is 156.0 mm. The precipitation of the warmest quarter is 303.0 mm. The precipitation of the coldest quarter is 428.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 34", + "(C) 87", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1437096_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0705", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.260674 and latitude -0.442675 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 63", + "(C) 46", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10658952_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0706", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.865608 and latitude -1.695195 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 53", + "(C) 140", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8196928_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0707", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.551894 and latitude -0.544869 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 69", + "(B) 49", + "(C) 82", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14509947_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0708", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.336411 and latitude -0.826705 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 5", + "(C) 56", + "(D) 87", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2366739_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0709", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.996090 and latitude 0.225545 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.27 degrees. The mean diurnal range is 11.79 degrees. The isothermality is 82.01. The temperature seasonality (100 times the standard deviation) is 77.54. The max temperature of the warmest month is 26.77 degrees. The min temperature of the coldest month is 12.40 degrees. The temperature annual range is 14.37 degrees. The mean temperature of the wettest quarter is 19.08 degrees. The mean temperature of the driest quarter is 19.91 degrees. The mean temperature of the warmest quarter is 20.18 degrees. The mean temperature of the coldest quarter is 18.29 degrees. The annual precipitation is 1839.0 mm. The precipitation of the wettest month is 253.0 mm. The precipitation of the driest month is 68.0 mm. The precipitation seasonality (coefficient of variation) is 38.12. The precipitation of the wettest quarter is 652.0 mm. The precipitation of the driest quarter is 243.0 mm. The precipitation of the warmest quarter is 306.0 mm. The precipitation of the coldest quarter is 531.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 365", + "(C) 27", + "(D) 117", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6355606_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0710", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433431 and latitude -0.723262 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 365", + "(C) 38", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17801432_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0711", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.560245 and latitude -0.553263 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 123", + "(B) 36", + "(C) 256", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11379808_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0712", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554973 and latitude -0.549678 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 24", + "(B) 28", + "(C) 44", + "(D) 150", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11363822_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0713", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.316827 and latitude -0.700020 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 70", + "(C) 23", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17115991_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0714", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.752254 and latitude -3.568972 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 71", + "(B) 95", + "(C) 33", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10807956_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0715", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.301133 and latitude -0.711030 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 17", + "(B) 69", + "(C) 53", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11401294_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0716", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425081 and latitude -0.721190 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 11", + "(B) 270", + "(C) 20", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21316833_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0717", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.691930 and latitude -3.990577 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 256", + "(C) 112", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3267612_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0718", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.078463 and latitude -0.573668 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 129", + "(B) 114", + "(C) 47", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3989563_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0719", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.413888 and latitude -0.792999 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 26", + "(C) 112", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18371916_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0720", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229546 and latitude -0.405126 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 153", + "(B) 97", + "(C) 117", + "(D) 86", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151970_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0721", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491962 and latitude -0.573307 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 25", + "(C) 45", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13374816_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0722", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.611015 and latitude -2.982577 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 129", + "(C) 23", + "(D) 110", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12023045_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0723", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267712 and latitude -0.814428 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 61", + "(C) 49", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6714321_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0724", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.491238 and latitude -0.636892 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 126", + "(C) 26", + "(D) 87", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6492845_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0725", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.635875 and latitude -0.502425 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 40", + "(C) 25", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16228684_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0726", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570261 and latitude -0.606583 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 47", + "(B) 37", + "(C) 59", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10075852_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0727", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.327839 and latitude -0.744303 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 140", + "(B) 47", + "(C) 207", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1219423_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0728", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308656 and latitude -0.816523 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 95", + "(C) 129", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1917524_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0729", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.325463 and latitude -0.891143 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.34 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 81.52. The temperature seasonality (100 times the standard deviation) is 63.49. The max temperature of the warmest month is 29.70 degrees. The min temperature of the coldest month is 15.11 degrees. The temperature annual range is 14.59 degrees. The mean temperature of the wettest quarter is 22.63 degrees. The mean temperature of the driest quarter is 21.47 degrees. The mean temperature of the warmest quarter is 23.09 degrees. The mean temperature of the coldest quarter is 21.47 degrees. The annual precipitation is 1140.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 38.0 mm. The precipitation seasonality (coefficient of variation) is 53.60. The precipitation of the wettest quarter is 480.0 mm. The precipitation of the driest quarter is 138.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 138.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 97", + "(B) 62", + "(C) 44", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9097664_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0730", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.277757 and latitude -0.813519 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 168", + "(B) 278", + "(C) 95", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1027936_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0731", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.326310 and latitude -0.717697 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 177", + "(C) 59", + "(D) 75", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11413533_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0732", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.845929 and latitude 1.034954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.44 degrees. The mean diurnal range is 13.48 degrees. The isothermality is 79.26. The temperature seasonality (100 times the standard deviation) is 93.12. The max temperature of the warmest month is 27.99 degrees. The min temperature of the coldest month is 10.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 18.47 degrees. The mean temperature of the driest quarter is 19.21 degrees. The mean temperature of the warmest quarter is 19.63 degrees. The mean temperature of the coldest quarter is 17.33 degrees. The annual precipitation is 1089.0 mm. The precipitation of the wettest month is 148.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 51.05. The precipitation of the wettest quarter is 400.0 mm. The precipitation of the driest quarter is 92.0 mm. The precipitation of the warmest quarter is 126.0 mm. The precipitation of the coldest quarter is 375.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 221", + "(C) 266", + "(D) 25", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279837_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0733", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.221202 and latitude 0.174242 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.00 degrees. The mean diurnal range is 11.80 degrees. The isothermality is 83.86. The temperature seasonality (100 times the standard deviation) is 62.05. The max temperature of the warmest month is 29.41 degrees. The min temperature of the coldest month is 15.34 degrees. The temperature annual range is 14.07 degrees. The mean temperature of the wettest quarter is 22.37 degrees. The mean temperature of the driest quarter is 22.51 degrees. The mean temperature of the warmest quarter is 22.77 degrees. The mean temperature of the coldest quarter is 21.19 degrees. The annual precipitation is 1701.0 mm. The precipitation of the wettest month is 262.0 mm. The precipitation of the driest month is 53.0 mm. The precipitation seasonality (coefficient of variation) is 41.56. The precipitation of the wettest quarter is 648.0 mm. The precipitation of the driest quarter is 247.0 mm. The precipitation of the warmest quarter is 293.0 mm. The precipitation of the coldest quarter is 357.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 25", + "(C) 15", + "(D) 52", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15479302_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0734", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.863928 and latitude -1.668777 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.28 degrees. The mean diurnal range is 12.11 degrees. The isothermality is 72.60. The temperature seasonality (100 times the standard deviation) is 128.56. The max temperature of the warmest month is 28.05 degrees. The min temperature of the coldest month is 11.37 degrees. The temperature annual range is 16.68 degrees. The mean temperature of the wettest quarter is 20.19 degrees. The mean temperature of the driest quarter is 17.76 degrees. The mean temperature of the warmest quarter is 20.66 degrees. The mean temperature of the coldest quarter is 17.41 degrees. The annual precipitation is 530.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 81.17. The precipitation of the wettest quarter is 253.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 90", + "(C) 88", + "(D) 40", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19048757_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0735", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.190270 and latitude -0.808495 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 26", + "(B) 365", + "(C) 6", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21155557_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0736", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426978 and latitude -0.765083 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 66", + "(C) 98", + "(D) 54", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20803961_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0737", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.455446 and latitude -0.735221 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 77", + "(C) 6", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16279479_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0738", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.300201 and latitude -0.821200 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 50", + "(C) 60", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1027894_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0739", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240434 and latitude -0.404942 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 505", + "(C) 33", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9997050_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0740", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.349719 and latitude -0.816269 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 126", + "(B) 52", + "(C) 6", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19129445_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0741", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612130 and latitude -2.985147 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 19", + "(C) 74", + "(D) 98", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12125053_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0742", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451718 and latitude -0.739879 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 76", + "(C) 87", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15614369_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0743", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120250 and latitude -0.376524 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 54", + "(C) 79", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17860014_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0744", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.245980 and latitude -0.410204 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 37", + "(B) 25", + "(C) 16", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10151885_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0745", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.348996 and latitude -0.826693 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 68", + "(C) 71", + "(D) 134", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4985917_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0746", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.135895 and latitude -0.613163 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 311", + "(C) 153", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2101438_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0747", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.375432 and latitude -0.662052 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 45", + "(B) 102", + "(C) 249", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298532_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0748", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610720 and latitude -2.980845 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 9", + "(B) 66", + "(C) 111", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12069484_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0749", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240989 and latitude -0.404745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 25", + "(C) 59", + "(D) 96", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9805701_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0750", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111939 and latitude -0.512160 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.16 degrees. The mean diurnal range is 13.78 degrees. The isothermality is 79.78. The temperature seasonality (100 times the standard deviation) is 82.46. The max temperature of the warmest month is 24.69 degrees. The min temperature of the coldest month is 7.41 degrees. The temperature annual range is 17.28 degrees. The mean temperature of the wettest quarter is 16.03 degrees. The mean temperature of the driest quarter is 15.64 degrees. The mean temperature of the warmest quarter is 16.23 degrees. The mean temperature of the coldest quarter is 14.18 degrees. The annual precipitation is 833.0 mm. The precipitation of the wettest month is 136.0 mm. The precipitation of the driest month is 32.0 mm. The precipitation seasonality (coefficient of variation) is 39.43. The precipitation of the wettest quarter is 295.0 mm. The precipitation of the driest quarter is 123.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 217.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 60", + "(B) 62", + "(C) 249", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10091419_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0751", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.064505 and latitude -0.294279 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 80", + "(C) 61", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18498216_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0752", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.803397 and latitude -3.847356 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 91", + "(B) 50", + "(C) 114", + "(D) 66", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16591200_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0753", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.267000 and latitude -0.391000 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 123", + "(C) 79", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9656777_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0754", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063727 and latitude 0.728790 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.77 degrees. The mean diurnal range is 13.96 degrees. The isothermality is 85.57. The temperature seasonality (100 times the standard deviation) is 65.85. The max temperature of the warmest month is 31.15 degrees. The min temperature of the coldest month is 14.83 degrees. The temperature annual range is 16.32 degrees. The mean temperature of the wettest quarter is 22.45 degrees. The mean temperature of the driest quarter is 22.88 degrees. The mean temperature of the warmest quarter is 23.64 degrees. The mean temperature of the coldest quarter is 22.00 degrees. The annual precipitation is 645.0 mm. The precipitation of the wettest month is 97.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 52.75. The precipitation of the wettest quarter is 249.0 mm. The precipitation of the driest quarter is 67.0 mm. The precipitation of the warmest quarter is 153.0 mm. The precipitation of the coldest quarter is 210.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 100", + "(C) 71", + "(D) 171", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13539972_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0755", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.710000 and latitude -4.049833 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 311", + "(B) 17", + "(C) 80", + "(D) 107", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2484720_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0756", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.864672 and latitude -1.666409 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.65 degrees. The mean diurnal range is 12.43 degrees. The isothermality is 72.64. The temperature seasonality (100 times the standard deviation) is 127.91. The max temperature of the warmest month is 28.72 degrees. The min temperature of the coldest month is 11.61 degrees. The temperature annual range is 17.11 degrees. The mean temperature of the wettest quarter is 20.57 degrees. The mean temperature of the driest quarter is 18.14 degrees. The mean temperature of the warmest quarter is 21.07 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 578.0 mm. The precipitation of the wettest month is 140.0 mm. The precipitation of the driest month is 6.0 mm. The precipitation seasonality (coefficient of variation) is 82.56. The precipitation of the wettest quarter is 281.0 mm. The precipitation of the driest quarter is 23.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 29.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 49", + "(B) 152", + "(C) 168", + "(D) 249", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6150442_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0757", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328739 and latitude -0.809682 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 84", + "(B) 33", + "(C) 311", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20974532_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0758", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.913344 and latitude 0.063140 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.97 degrees. The mean diurnal range is 11.67 degrees. The isothermality is 81.23. The temperature seasonality (100 times the standard deviation) is 72.48. The max temperature of the warmest month is 26.50 degrees. The min temperature of the coldest month is 12.14 degrees. The temperature annual range is 14.36 degrees. The mean temperature of the wettest quarter is 19.37 degrees. The mean temperature of the driest quarter is 19.54 degrees. The mean temperature of the warmest quarter is 19.80 degrees. The mean temperature of the coldest quarter is 18.05 degrees. The annual precipitation is 1927.0 mm. The precipitation of the wettest month is 277.0 mm. The precipitation of the driest month is 77.0 mm. The precipitation seasonality (coefficient of variation) is 36.56. The precipitation of the wettest quarter is 686.0 mm. The precipitation of the driest quarter is 279.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 505.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 140", + "(B) 48", + "(C) 67", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9160408_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0759", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.965087 and latitude -0.002546 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.41 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 83.04. The temperature seasonality (100 times the standard deviation) is 60.97. The max temperature of the warmest month is 27.74 degrees. The min temperature of the coldest month is 10.20 degrees. The temperature annual range is 17.53 degrees. The mean temperature of the wettest quarter is 18.72 degrees. The mean temperature of the driest quarter is 18.75 degrees. The mean temperature of the warmest quarter is 19.17 degrees. The mean temperature of the coldest quarter is 17.63 degrees. The annual precipitation is 971.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.31. The precipitation of the wettest quarter is 327.0 mm. The precipitation of the driest quarter is 129.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 311", + "(C) 108", + "(D) 15", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8291945_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0760", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418281 and latitude -0.769957 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 30", + "(B) 10", + "(C) 49", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17031906_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0761", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.225915 and latitude -0.375062 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 19", + "(C) 92", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3638713_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0762", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.243000 and latitude -0.436900 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 207", + "(B) 32", + "(C) 51", + "(D) 8", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10598574_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0763", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.440641 and latitude -0.723812 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 33", + "(B) 28", + "(C) 122", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18581685_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0764", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.224466 and latitude -0.451912 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 77", + "(B) 9", + "(C) 64", + "(D) 173", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16985203_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0765", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.284696 and latitude 0.521274 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 42", + "(B) 43", + "(C) 138", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6290833_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0766", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.283195 and latitude -0.716460 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 72", + "(B) 159", + "(C) 18", + "(D) 6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14798664_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0767", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.952315 and latitude 0.009622 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.68 degrees. The mean diurnal range is 14.73 degrees. The isothermality is 83.77. The temperature seasonality (100 times the standard deviation) is 60.26. The max temperature of the warmest month is 28.97 degrees. The min temperature of the coldest month is 11.38 degrees. The temperature annual range is 17.59 degrees. The mean temperature of the wettest quarter is 19.97 degrees. The mean temperature of the driest quarter is 19.98 degrees. The mean temperature of the warmest quarter is 20.44 degrees. The mean temperature of the coldest quarter is 18.92 degrees. The annual precipitation is 965.0 mm. The precipitation of the wettest month is 132.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 38.30. The precipitation of the wettest quarter is 317.0 mm. The precipitation of the driest quarter is 128.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 49", + "(B) 69", + "(C) 138", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17925698_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0768", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.493755 and latitude -0.589523 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 43", + "(B) 259", + "(C) 41", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10072386_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0769", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610542 and latitude -2.982743 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 112", + "(B) 54", + "(C) 42", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12045024_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0770", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437874 and latitude -0.712376 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 207", + "(C) 168", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279452_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0771", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420519 and latitude -0.775280 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 114", + "(C) 35", + "(D) 108", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284261_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0772", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.435263 and latitude -0.717722 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 249", + "(B) 96", + "(C) 40", + "(D) 269", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11682534_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0773", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.378083 and latitude -0.822826 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 168", + "(B) 89", + "(C) 41", + "(D) 278", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8051680_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0774", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.752829 and latitude -3.571346 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.77 degrees. The mean diurnal range is 10.28 degrees. The isothermality is 69.21. The temperature seasonality (100 times the standard deviation) is 151.70. The max temperature of the warmest month is 31.48 degrees. The min temperature of the coldest month is 16.64 degrees. The temperature annual range is 14.85 degrees. The mean temperature of the wettest quarter is 24.25 degrees. The mean temperature of the driest quarter is 21.84 degrees. The mean temperature of the warmest quarter is 25.45 degrees. The mean temperature of the coldest quarter is 21.81 degrees. The annual precipitation is 755.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 62.28. The precipitation of the wettest quarter is 298.0 mm. The precipitation of the driest quarter is 69.0 mm. The precipitation of the warmest quarter is 170.0 mm. The precipitation of the coldest quarter is 80.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 126", + "(B) 85", + "(C) 99", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14087004_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0775", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.090179 and latitude -0.613906 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 137", + "(C) 22", + "(D) 249", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3990989_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0776", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.125236 and latitude -0.361688 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 77", + "(C) 18", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5255397_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0777", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.229570 and latitude -0.461040 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 36", + "(C) 171", + "(D) 61", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21692520_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0778", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.570869 and latitude -0.572879 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 134", + "(B) 278", + "(C) 173", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6294587_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0779", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.442682 and latitude -0.721603 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 150", + "(B) 129", + "(C) 58", + "(D) 79", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10176494_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0780", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.303336 and latitude -0.676259 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 121", + "(B) 27", + "(C) 38", + "(D) 112", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11202841_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0781", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.117479 and latitude -0.478450 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 42", + "(B) 111", + "(C) 139", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6301196_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0782", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.106152 and latitude -0.401560 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 365", + "(B) 64", + "(C) 20", + "(D) 122", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16457239_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0783", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.068058 and latitude -0.390541 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 92", + "(C) 66", + "(D) 93", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6687369_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0784", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.554947 and latitude -0.549995 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 105", + "(C) 270", + "(D) 61", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12264886_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0785", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.425371 and latitude -0.720112 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 5", + "(B) 56", + "(C) 36", + "(D) 41", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13930747_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0786", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.060538 and latitude -1.357928 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.64 degrees. The mean diurnal range is 12.06 degrees. The isothermality is 72.91. The temperature seasonality (100 times the standard deviation) is 127.40. The max temperature of the warmest month is 28.49 degrees. The min temperature of the coldest month is 11.95 degrees. The temperature annual range is 16.54 degrees. The mean temperature of the wettest quarter is 20.60 degrees. The mean temperature of the driest quarter is 18.10 degrees. The mean temperature of the warmest quarter is 21.05 degrees. The mean temperature of the coldest quarter is 17.82 degrees. The annual precipitation is 636.0 mm. The precipitation of the wettest month is 139.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 85.66. The precipitation of the wettest quarter is 289.0 mm. The precipitation of the driest quarter is 19.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 23.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 39", + "(C) 98", + "(D) 152", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16196959_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0787", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.729631 and latitude -3.947831 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 1", + "(B) 69", + "(C) 48", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3857011_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0788", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.419010 and latitude -0.762516 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 111", + "(C) 83", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8092248_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0789", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.422257 and latitude -0.797786 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 102", + "(B) 49", + "(C) 126", + "(D) 66", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15541395_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0790", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.118768 and latitude -0.408528 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 79", + "(C) 53", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10214600_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0791", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.328096 and latitude -0.745032 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 37", + "(C) 22", + "(D) 100", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21760547_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0792", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.324620 and latitude -0.517466 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.90 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 79.70. The temperature seasonality (100 times the standard deviation) is 83.47. The max temperature of the warmest month is 25.75 degrees. The min temperature of the coldest month is 7.70 degrees. The temperature annual range is 18.05 degrees. The mean temperature of the wettest quarter is 16.75 degrees. The mean temperature of the driest quarter is 16.37 degrees. The mean temperature of the warmest quarter is 16.95 degrees. The mean temperature of the coldest quarter is 14.85 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 40.67. The precipitation of the wettest quarter is 265.0 mm. The precipitation of the driest quarter is 109.0 mm. The precipitation of the warmest quarter is 212.0 mm. The precipitation of the coldest quarter is 173.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 34", + "(B) 107", + "(C) 126", + "(D) 46", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1874608_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0793", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.247270 and latitude -0.411410 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 63", + "(B) 8", + "(C) 133", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6201096_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0794", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.291683 and latitude -0.713102 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 365", + "(B) 311", + "(C) 65", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14962292_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0795", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.239173 and latitude -0.403064 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 78", + "(B) 61", + "(C) 72", + "(D) 114", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10076522_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0796", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.223909 and latitude -0.457088 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 28", + "(B) 221", + "(C) 39", + "(D) 9", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4237255_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0797", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.016729 and latitude -1.424873 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.58 degrees. The mean diurnal range is 10.21 degrees. The isothermality is 71.79. The temperature seasonality (100 times the standard deviation) is 125.39. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 15.74 degrees. The temperature annual range is 14.23 degrees. The mean temperature of the wettest quarter is 23.08 degrees. The mean temperature of the driest quarter is 20.76 degrees. The mean temperature of the warmest quarter is 23.90 degrees. The mean temperature of the coldest quarter is 20.76 degrees. The annual precipitation is 790.0 mm. The precipitation of the wettest month is 235.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 112.32. The precipitation of the wettest quarter is 426.0 mm. The precipitation of the driest quarter is 11.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 11.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 121", + "(C) 24", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15691623_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0798", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.151949 and latitude -0.421988 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 126", + "(C) 123", + "(D) 99", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10031354_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0799", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.110418 and latitude -0.307472 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 27", + "(B) 80", + "(C) 107", + "(D) 185", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9863251_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0800", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.261497 and latitude -0.426087 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 108", + "(B) 23", + "(C) 33", + "(D) 150", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16054578_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0801", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.692246 and latitude -3.047183 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.87 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 68.99. The temperature seasonality (100 times the standard deviation) is 163.68. The max temperature of the warmest month is 31.18 degrees. The min temperature of the coldest month is 13.94 degrees. The temperature annual range is 17.23 degrees. The mean temperature of the wettest quarter is 22.60 degrees. The mean temperature of the driest quarter is 19.66 degrees. The mean temperature of the warmest quarter is 23.71 degrees. The mean temperature of the coldest quarter is 19.66 degrees. The annual precipitation is 781.0 mm. The precipitation of the wettest month is 196.0 mm. The precipitation of the driest month is 10.0 mm. The precipitation seasonality (coefficient of variation) is 89.27. The precipitation of the wettest quarter is 372.0 mm. The precipitation of the driest quarter is 32.0 mm. The precipitation of the warmest quarter is 204.0 mm. The precipitation of the coldest quarter is 32.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 100", + "(B) 20", + "(C) 18", + "(D) 69", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12038122_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0802", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.561378 and latitude -0.557328 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 111", + "(B) 207", + "(C) 135", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12677064_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0803", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 38.335490 and latitude -2.241674 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 24.56 degrees. The mean diurnal range is 9.77 degrees. The isothermality is 67.85. The temperature seasonality (100 times the standard deviation) is 142.75. The max temperature of the warmest month is 32.02 degrees. The min temperature of the coldest month is 17.63 degrees. The temperature annual range is 14.39 degrees. The mean temperature of the wettest quarter is 25.07 degrees. The mean temperature of the driest quarter is 22.56 degrees. The mean temperature of the warmest quarter is 26.15 degrees. The mean temperature of the coldest quarter is 22.56 degrees. The annual precipitation is 654.0 mm. The precipitation of the wettest month is 172.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 105.99. The precipitation of the wettest quarter is 346.0 mm. The precipitation of the driest quarter is 16.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 16.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 95", + "(C) 62", + "(D) 114", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13301310_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0804", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718151 and latitude -4.017357 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 139", + "(B) 39", + "(C) 108", + "(D) 31", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2070641_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0805", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.384507 and latitude -0.818119 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 110", + "(C) 28", + "(D) 16", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16756373_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0806", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.581487 and latitude -2.894942 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 92", + "(C) 70", + "(D) 51", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060089_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0807", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452243 and latitude -0.735218 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 72", + "(B) 59", + "(C) 96", + "(D) 43", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15770066_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0808", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.632589 and latitude -1.412630 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.42 degrees. The mean diurnal range is 11.13 degrees. The isothermality is 72.41. The temperature seasonality (100 times the standard deviation) is 126.48. The max temperature of the warmest month is 29.39 degrees. The min temperature of the coldest month is 14.02 degrees. The temperature annual range is 15.37 degrees. The mean temperature of the wettest quarter is 21.91 degrees. The mean temperature of the driest quarter is 19.88 degrees. The mean temperature of the warmest quarter is 22.75 degrees. The mean temperature of the coldest quarter is 19.57 degrees. The annual precipitation is 718.0 mm. The precipitation of the wettest month is 204.0 mm. The precipitation of the driest month is 1.0 mm. The precipitation seasonality (coefficient of variation) is 105.97. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 8.0 mm. The precipitation of the warmest quarter is 270.0 mm. The precipitation of the coldest quarter is 10.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 129", + "(B) 35", + "(C) 259", + "(D) 64", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10056690_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0809", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612393 and latitude -2.983073 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 9", + "(C) 117", + "(D) 49", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12071643_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0810", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456322 and latitude -0.730952 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 121", + "(B) 59", + "(C) 46", + "(D) 95", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18098985_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0811", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.262007 and latitude -0.782408 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 11", + "(C) 2", + "(D) 270", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1279523_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0812", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.579637 and latitude 0.338600 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 23.11 degrees. The mean diurnal range is 13.14 degrees. The isothermality is 81.39. The temperature seasonality (100 times the standard deviation) is 73.67. The max temperature of the warmest month is 31.74 degrees. The min temperature of the coldest month is 15.59 degrees. The temperature annual range is 16.14 degrees. The mean temperature of the wettest quarter is 22.79 degrees. The mean temperature of the driest quarter is 22.49 degrees. The mean temperature of the warmest quarter is 23.91 degrees. The mean temperature of the coldest quarter is 22.47 degrees. The annual precipitation is 676.0 mm. The precipitation of the wettest month is 177.0 mm. The precipitation of the driest month is 5.0 mm. The precipitation seasonality (coefficient of variation) is 97.62. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 17.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 277.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 75", + "(B) 266", + "(C) 60", + "(D) 123", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5638669_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0813", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.302593 and latitude -0.722962 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 6", + "(B) 51", + "(C) 113", + "(D) 204", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964191_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0814", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.718976 and latitude -4.014098 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 79", + "(B) 70", + "(C) 9", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14464425_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0815", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.716266 and latitude -0.454711 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 11.59 degrees. The mean diurnal range is 11.23 degrees. The isothermality is 79.30. The temperature seasonality (100 times the standard deviation) is 80.41. The max temperature of the warmest month is 19.07 degrees. The min temperature of the coldest month is 4.91 degrees. The temperature annual range is 14.16 degrees. The mean temperature of the wettest quarter is 12.48 degrees. The mean temperature of the driest quarter is 11.68 degrees. The mean temperature of the warmest quarter is 12.49 degrees. The mean temperature of the coldest quarter is 10.53 degrees. The annual precipitation is 1402.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 45.0 mm. The precipitation seasonality (coefficient of variation) is 45.34. The precipitation of the wettest quarter is 530.0 mm. The precipitation of the driest quarter is 204.0 mm. The precipitation of the warmest quarter is 407.0 mm. The precipitation of the coldest quarter is 264.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 117", + "(B) 100", + "(C) 90", + "(D) 146", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2688861_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0816", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.469995 and latitude -0.552480 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 256", + "(B) 111", + "(C) 266", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6428377_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0817", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.614320 and latitude -2.983500 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 137", + "(B) 278", + "(C) 57", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12018725_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0818", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.578122 and latitude -2.996700 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 16", + "(B) 71", + "(C) 34", + "(D) 61", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12116603_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0819", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.020203 and latitude -0.078163 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 53", + "(C) 101", + "(D) 113", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L8219781_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0820", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.240913 and latitude -0.404855 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 77", + "(B) 91", + "(C) 15", + "(D) 114", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9996816_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0821", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.087149 and latitude -0.265111 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 23", + "(B) 85", + "(C) 153", + "(D) 69", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10051579_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0822", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.721884 and latitude -4.029045 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 96", + "(B) 41", + "(C) 67", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10691981_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0823", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120769 and latitude -0.400954 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 37", + "(C) 80", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14106163_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0824", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.430247 and latitude -0.719660 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 107", + "(B) 90", + "(C) 91", + "(D) 24", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16104638_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0825", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426588 and latitude -0.759612 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 61", + "(B) 42", + "(C) 108", + "(D) 87", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10819022_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0826", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.285334 and latitude 0.501972 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.46 degrees. The mean diurnal range is 12.82 degrees. The isothermality is 81.66. The temperature seasonality (100 times the standard deviation) is 86.32. The max temperature of the warmest month is 25.99 degrees. The min temperature of the coldest month is 10.29 degrees. The temperature annual range is 15.70 degrees. The mean temperature of the wettest quarter is 16.33 degrees. The mean temperature of the driest quarter is 17.95 degrees. The mean temperature of the warmest quarter is 18.50 degrees. The mean temperature of the coldest quarter is 16.33 degrees. The annual precipitation is 1063.0 mm. The precipitation of the wettest month is 168.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 51.88. The precipitation of the wettest quarter is 421.0 mm. The precipitation of the driest quarter is 112.0 mm. The precipitation of the warmest quarter is 238.0 mm. The precipitation of the coldest quarter is 403.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 8", + "(B) 66", + "(C) 52", + "(D) 100", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7695066_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0827", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.420754 and latitude -0.776724 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 249", + "(C) 20", + "(D) 23", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4377528_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0828", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.460391 and latitude 1.492150 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 18.66 degrees. The mean diurnal range is 12.31 degrees. The isothermality is 82.42. The temperature seasonality (100 times the standard deviation) is 66.01. The max temperature of the warmest month is 26.50 degrees. The min temperature of the coldest month is 11.56 degrees. The temperature annual range is 14.94 degrees. The mean temperature of the wettest quarter is 17.89 degrees. The mean temperature of the driest quarter is 18.99 degrees. The mean temperature of the warmest quarter is 19.56 degrees. The mean temperature of the coldest quarter is 17.89 degrees. The annual precipitation is 945.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 20.0 mm. The precipitation seasonality (coefficient of variation) is 53.44. The precipitation of the wettest quarter is 358.0 mm. The precipitation of the driest quarter is 87.0 mm. The precipitation of the warmest quarter is 223.0 mm. The precipitation of the coldest quarter is 358.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 82", + "(B) 221", + "(C) 11", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2338173_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0829", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.988534 and latitude -0.219421 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.61 degrees. The mean diurnal range is 14.44 degrees. The isothermality is 81.62. The temperature seasonality (100 times the standard deviation) is 67.92. The max temperature of the warmest month is 26.15 degrees. The min temperature of the coldest month is 8.45 degrees. The temperature annual range is 17.69 degrees. The mean temperature of the wettest quarter is 16.93 degrees. The mean temperature of the driest quarter is 16.94 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 15.81 degrees. The annual precipitation is 940.0 mm. The precipitation of the wettest month is 142.0 mm. The precipitation of the driest month is 28.0 mm. The precipitation seasonality (coefficient of variation) is 43.80. The precipitation of the wettest quarter is 330.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 244.0 mm. The precipitation of the coldest quarter is 287.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 153", + "(C) 173", + "(D) 3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22119968_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0830", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.601350 and latitude -2.950138 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 69", + "(C) 171", + "(D) 13", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12060066_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0831", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.640961 and latitude -2.974739 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 259", + "(B) 376", + "(C) 48", + "(D) 83", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18597563_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0832", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.453385 and latitude -0.728857 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 108", + "(B) 42", + "(C) 62", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13758223_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0833", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.363400 and latitude -0.470640 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 14.83 degrees. The mean diurnal range is 14.23 degrees. The isothermality is 78.61. The temperature seasonality (100 times the standard deviation) is 80.44. The max temperature of the warmest month is 24.54 degrees. The min temperature of the coldest month is 6.44 degrees. The temperature annual range is 18.10 degrees. The mean temperature of the wettest quarter is 15.11 degrees. The mean temperature of the driest quarter is 15.15 degrees. The mean temperature of the warmest quarter is 15.85 degrees. The mean temperature of the coldest quarter is 13.83 degrees. The annual precipitation is 816.0 mm. The precipitation of the wettest month is 123.0 mm. The precipitation of the driest month is 29.0 mm. The precipitation seasonality (coefficient of variation) is 40.35. The precipitation of the wettest quarter is 296.0 mm. The precipitation of the driest quarter is 108.0 mm. The precipitation of the warmest quarter is 210.0 mm. The precipitation of the coldest quarter is 208.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 34", + "(C) 126", + "(D) 18", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21005691_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0834", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120347 and latitude -0.373093 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 278", + "(C) 17", + "(D) 87", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12794356_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0835", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.130841 and latitude -0.310531 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 137", + "(C) 40", + "(D) 59", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L18147093_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0836", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.786000 and latitude -3.908000 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.96 degrees. The mean diurnal range is 7.93 degrees. The isothermality is 65.60. The temperature seasonality (100 times the standard deviation) is 139.52. The max temperature of the warmest month is 32.38 degrees. The min temperature of the coldest month is 20.29 degrees. The temperature annual range is 12.09 degrees. The mean temperature of the wettest quarter is 25.97 degrees. The mean temperature of the driest quarter is 27.41 degrees. The mean temperature of the warmest quarter is 27.54 degrees. The mean temperature of the coldest quarter is 24.15 degrees. The annual precipitation is 1123.0 mm. The precipitation of the wettest month is 266.0 mm. The precipitation of the driest month is 17.0 mm. The precipitation seasonality (coefficient of variation) is 71.00. The precipitation of the wettest quarter is 535.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 246.0 mm. The precipitation of the coldest quarter is 218.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 221", + "(B) 38", + "(C) 126", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4561068_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0837", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.248771 and latitude -0.434102 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 159", + "(B) 12", + "(C) 57", + "(D) 42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3846997_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0838", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.124408 and latitude -0.423229 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 25", + "(B) 16", + "(C) 18", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21476921_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0839", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.418809 and latitude -0.772926 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 256", + "(B) 97", + "(C) 52", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20229590_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0840", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249894 and latitude -0.433598 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 269", + "(B) 70", + "(C) 97", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4235132_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0841", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.024926 and latitude -0.077162 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 173", + "(B) 29", + "(C) 1", + "(D) 19", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3074898_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0842", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.385322 and latitude -0.817636 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 58", + "(B) 269", + "(C) 53", + "(D) 70", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L21656097_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0843", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.426106 and latitude -0.714779 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 99", + "(B) 27", + "(C) 49", + "(D) 30", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919751_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0844", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088105 and latitude -0.404465 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 54", + "(B) 87", + "(C) 278", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7666090_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0845", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.242540 and latitude -0.405014 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 88", + "(B) 49", + "(C) 137", + "(D) 26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1926871_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0846", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432161 and latitude -0.742143 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 90", + "(B) 62", + "(C) 36", + "(D) 259", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6298492_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0847", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.433018 and latitude -0.719505 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 73", + "(C) 152", + "(D) 22", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9581283_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0848", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.432933 and latitude -0.745042 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 58", + "(C) 259", + "(D) 74", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5287529_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0849", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.616753 and latitude -2.969602 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 48", + "(B) 71", + "(C) 173", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12077587_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0850", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.486642 and latitude -0.586780 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 20", + "(B) 38", + "(C) 8", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9571885_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0851", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.536811 and latitude -0.548603 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 91", + "(B) 84", + "(C) 65", + "(D) 83", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11372449_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0852", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431218 and latitude -0.716916 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 67", + "(B) 129", + "(C) 83", + "(D) 57", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11763290_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0853", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.088687 and latitude -0.312322 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 69", + "(B) 40", + "(C) 271", + "(D) 71", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4074487_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0854", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.451435 and latitude -0.740282 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 129", + "(B) 37", + "(C) 6", + "(D) 2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L19693144_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0855", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.391852 and latitude -0.810876 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 2", + "(B) 72", + "(C) 57", + "(D) 266", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3645588_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0856", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.121000 and latitude -0.548000 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.88 degrees. The mean diurnal range is 9.51 degrees. The isothermality is 83.23. The temperature seasonality (100 times the standard deviation) is 59.33. The max temperature of the warmest month is 27.70 degrees. The min temperature of the coldest month is 16.28 degrees. The temperature annual range is 11.42 degrees. The mean temperature of the wettest quarter is 22.19 degrees. The mean temperature of the driest quarter is 21.08 degrees. The mean temperature of the warmest quarter is 22.57 degrees. The mean temperature of the coldest quarter is 21.08 degrees. The annual precipitation is 1132.0 mm. The precipitation of the wettest month is 195.0 mm. The precipitation of the driest month is 41.0 mm. The precipitation seasonality (coefficient of variation) is 50.98. The precipitation of the wettest quarter is 472.0 mm. The precipitation of the driest quarter is 141.0 mm. The precipitation of the warmest quarter is 253.0 mm. The precipitation of the coldest quarter is 141.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 99", + "(C) 132", + "(D) 113", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16433855_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0857", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.070350 and latitude -0.319439 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 75", + "(C) 10", + "(D) 60", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L5093141_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0858", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.291592 and latitude -0.723035 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 39", + "(B) 55", + "(C) 22", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20055767_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0859", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.431190 and latitude -0.718640 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 137", + "(B) 112", + "(C) 99", + "(D) 55", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12919755_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0860", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.181097 and latitude 0.921316 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.72 degrees. The mean diurnal range is 13.24 degrees. The isothermality is 81.34. The temperature seasonality (100 times the standard deviation) is 80.70. The max temperature of the warmest month is 26.64 degrees. The min temperature of the coldest month is 10.36 degrees. The temperature annual range is 16.28 degrees. The mean temperature of the wettest quarter is 16.74 degrees. The mean temperature of the driest quarter is 18.20 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 16.72 degrees. The annual precipitation is 1010.0 mm. The precipitation of the wettest month is 154.0 mm. The precipitation of the driest month is 21.0 mm. The precipitation seasonality (coefficient of variation) is 52.27. The precipitation of the wettest quarter is 389.0 mm. The precipitation of the driest quarter is 96.0 mm. The precipitation of the warmest quarter is 231.0 mm. The precipitation of the coldest quarter is 370.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 14", + "(C) 21", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L15854931_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0861", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 35.308395 and latitude 0.472096 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.31 degrees. The mean diurnal range is 12.66 degrees. The isothermality is 80.91. The temperature seasonality (100 times the standard deviation) is 90.32. The max temperature of the warmest month is 25.84 degrees. The min temperature of the coldest month is 10.19 degrees. The temperature annual range is 15.65 degrees. The mean temperature of the wettest quarter is 16.16 degrees. The mean temperature of the driest quarter is 17.85 degrees. The mean temperature of the warmest quarter is 18.41 degrees. The mean temperature of the coldest quarter is 16.13 degrees. The annual precipitation is 1212.0 mm. The precipitation of the wettest month is 184.0 mm. The precipitation of the driest month is 35.0 mm. The precipitation seasonality (coefficient of variation) is 50.38. The precipitation of the wettest quarter is 465.0 mm. The precipitation of the driest quarter is 130.0 mm. The precipitation of the warmest quarter is 280.0 mm. The precipitation of the coldest quarter is 449.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 7", + "(B) 60", + "(C) 34", + "(D) 45", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17886635_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0862", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437416 and latitude -0.740186 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 150", + "(B) 137", + "(C) 60", + "(D) 44", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12821674_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0863", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.775877 and latitude 0.935621 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.53 degrees. The mean diurnal range is 14.56 degrees. The isothermality is 82.89. The temperature seasonality (100 times the standard deviation) is 75.43. The max temperature of the warmest month is 26.48 degrees. The min temperature of the coldest month is 8.92 degrees. The temperature annual range is 17.57 degrees. The mean temperature of the wettest quarter is 18.61 degrees. The mean temperature of the driest quarter is 17.45 degrees. The mean temperature of the warmest quarter is 18.61 degrees. The mean temperature of the coldest quarter is 16.72 degrees. The annual precipitation is 660.0 mm. The precipitation of the wettest month is 119.0 mm. The precipitation of the driest month is 19.0 mm. The precipitation seasonality (coefficient of variation) is 52.81. The precipitation of the wettest quarter is 255.0 mm. The precipitation of the driest quarter is 80.0 mm. The precipitation of the warmest quarter is 255.0 mm. The precipitation of the coldest quarter is 144.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 57", + "(B) 122", + "(C) 33", + "(D) 259", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17875037_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0864", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.424516 and latitude -0.641202 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 270", + "(B) 43", + "(C) 14", + "(D) 111", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6833748_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0865", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.111486 and latitude -0.310105 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 4", + "(B) 48", + "(C) 159", + "(D) 256", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9354873_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0866", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.610318 and latitude -2.980595 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 66", + "(B) 42", + "(C) 21", + "(D) 92", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12055115_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0867", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.210594 and latitude -0.408207 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 365", + "(B) 97", + "(C) 168", + "(D) 77", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1284269_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0868", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.415048 and latitude -0.770567 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 95", + "(B) 110", + "(C) 44", + "(D) 62", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10207400_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0869", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.063208 and latitude -0.269197 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 38", + "(B) 49", + "(C) 22", + "(D) 36", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13929931_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0870", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.772658 and latitude -0.324769 in the state of Nyanza, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 22.69 degrees. The mean diurnal range is 10.64 degrees. The isothermality is 85.02. The temperature seasonality (100 times the standard deviation) is 65.57. The max temperature of the warmest month is 29.12 degrees. The min temperature of the coldest month is 16.61 degrees. The temperature annual range is 12.51 degrees. The mean temperature of the wettest quarter is 22.99 degrees. The mean temperature of the driest quarter is 23.26 degrees. The mean temperature of the warmest quarter is 23.46 degrees. The mean temperature of the coldest quarter is 21.80 degrees. The annual precipitation is 1185.0 mm. The precipitation of the wettest month is 183.0 mm. The precipitation of the driest month is 50.0 mm. The precipitation seasonality (coefficient of variation) is 39.91. The precipitation of the wettest quarter is 477.0 mm. The precipitation of the driest quarter is 217.0 mm. The precipitation of the warmest quarter is 259.0 mm. The precipitation of the coldest quarter is 238.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 204", + "(B) 53", + "(C) 153", + "(D) 47", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17105361_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0871", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 34.921171 and latitude 1.388938 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.18 degrees. The mean diurnal range is 12.89 degrees. The isothermality is 83.58. The temperature seasonality (100 times the standard deviation) is 63.80. The max temperature of the warmest month is 29.46 degrees. The min temperature of the coldest month is 14.03 degrees. The temperature annual range is 15.42 degrees. The mean temperature of the wettest quarter is 20.76 degrees. The mean temperature of the driest quarter is 21.64 degrees. The mean temperature of the warmest quarter is 22.01 degrees. The mean temperature of the coldest quarter is 20.44 degrees. The annual precipitation is 1049.0 mm. The precipitation of the wettest month is 150.0 mm. The precipitation of the driest month is 23.0 mm. The precipitation seasonality (coefficient of variation) is 51.07. The precipitation of the wettest quarter is 387.0 mm. The precipitation of the driest quarter is 93.0 mm. The precipitation of the warmest quarter is 247.0 mm. The precipitation of the coldest quarter is 371.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 83", + "(B) 70", + "(C) 47", + "(D) 117", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L20746627_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0872", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120543 and latitude -0.369930 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 35", + "(B) 249", + "(C) 69", + "(D) 80", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16683759_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0873", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.272914 and latitude -0.773269 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 36", + "(C) 62", + "(D) 34", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22260135_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0874", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.270547 and latitude -0.443776 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 62", + "(B) 108", + "(C) 185", + "(D) 20", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4463737_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0875", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.605042 and latitude -2.970730 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 122", + "(B) 70", + "(C) 256", + "(D) 84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12026564_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0876", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.308164 and latitude -0.721051 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 133", + "(B) 66", + "(C) 20", + "(D) 38", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L9956046_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0877", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.706267 and latitude -0.386098 in the state of North-Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 28.23 degrees. The mean diurnal range is 10.12 degrees. The isothermality is 72.16. The temperature seasonality (100 times the standard deviation) is 126.04. The max temperature of the warmest month is 35.74 degrees. The min temperature of the coldest month is 21.72 degrees. The temperature annual range is 14.02 degrees. The mean temperature of the wettest quarter is 28.40 degrees. The mean temperature of the driest quarter is 26.58 degrees. The mean temperature of the warmest quarter is 29.78 degrees. The mean temperature of the coldest quarter is 26.58 degrees. The annual precipitation is 358.0 mm. The precipitation of the wettest month is 95.0 mm. The precipitation of the driest month is 4.0 mm. The precipitation seasonality (coefficient of variation) is 103.10. The precipitation of the wettest quarter is 181.0 mm. The precipitation of the driest quarter is 15.0 mm. The precipitation of the warmest quarter is 125.0 mm. The precipitation of the coldest quarter is 15.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 98", + "(B) 68", + "(C) 77", + "(D) 35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12768672_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0878", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.452555 and latitude -0.745897 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 63", + "(B) 112", + "(C) 56", + "(D) 53", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14739048_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0879", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.606940 and latitude -2.983382 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 64", + "(B) 20", + "(C) 91", + "(D) 48", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12085520_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0880", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.437895 and latitude -0.727570 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 129", + "(B) 44", + "(C) 69", + "(D) 50", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L17974825_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0881", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490242 and latitude -0.589063 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 44", + "(B) 34", + "(C) 207", + "(D) 113", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11370815_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0882", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.321595 and latitude -0.666745 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.34 degrees. The mean diurnal range is 13.91 degrees. The isothermality is 78.25. The temperature seasonality (100 times the standard deviation) is 101.29. The max temperature of the warmest month is 26.26 degrees. The min temperature of the coldest month is 8.48 degrees. The temperature annual range is 17.78 degrees. The mean temperature of the wettest quarter is 17.21 degrees. The mean temperature of the driest quarter is 17.04 degrees. The mean temperature of the warmest quarter is 17.52 degrees. The mean temperature of the coldest quarter is 14.98 degrees. The annual precipitation is 705.0 mm. The precipitation of the wettest month is 127.0 mm. The precipitation of the driest month is 34.0 mm. The precipitation seasonality (coefficient of variation) is 45.72. The precipitation of the wettest quarter is 283.0 mm. The precipitation of the driest quarter is 120.0 mm. The precipitation of the warmest quarter is 222.0 mm. The precipitation of the coldest quarter is 147.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 36", + "(B) 49", + "(C) 21", + "(D) 17", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L22689728_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0883", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.726090 and latitude -4.013932 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.40 degrees. The mean diurnal range is 11.89 degrees. The isothermality is 76.06. The temperature seasonality (100 times the standard deviation) is 104.77. The max temperature of the warmest month is 28.69 degrees. The min temperature of the coldest month is 13.09 degrees. The temperature annual range is 15.60 degrees. The mean temperature of the wettest quarter is 20.93 degrees. The mean temperature of the driest quarter is 19.64 degrees. The mean temperature of the warmest quarter is 21.59 degrees. The mean temperature of the coldest quarter is 19.01 degrees. The annual precipitation is 930.5847266 mm. The precipitation of the wettest month is 185.98072 mm. The precipitation of the driest month is 22.29522518 mm. The precipitation seasonality (coefficient of variation) is 70.16. The precipitation of the wettest quarter is 406.8517849 mm. The precipitation of the driest quarter is 86.7220967 mm. The precipitation of the warmest quarter is 272.359994 mm. The precipitation of the coldest quarter is 138.7767736 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 74", + "(B) 112", + "(C) 44", + "(D) 159", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L3039691_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0884", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.555278 and latitude -2.041702 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 20.60 degrees. The mean diurnal range is 11.48 degrees. The isothermality is 72.45. The temperature seasonality (100 times the standard deviation) is 130.85. The max temperature of the warmest month is 28.91 degrees. The min temperature of the coldest month is 13.06 degrees. The temperature annual range is 15.85 degrees. The mean temperature of the wettest quarter is 21.40 degrees. The mean temperature of the driest quarter is 19.06 degrees. The mean temperature of the warmest quarter is 21.94 degrees. The mean temperature of the coldest quarter is 18.69 degrees. The annual precipitation is 523.0 mm. The precipitation of the wettest month is 119.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 81.52. The precipitation of the wettest quarter is 258.0 mm. The precipitation of the driest quarter is 10.0 mm. The precipitation of the warmest quarter is 235.0 mm. The precipitation of the coldest quarter is 14.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 55", + "(B) 150", + "(C) 221", + "(D) 68", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14837930_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0885", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 39.789798 and latitude -3.798998 in the state of Coast, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 25.48 degrees. The mean diurnal range is 8.00 degrees. The isothermality is 67.22. The temperature seasonality (100 times the standard deviation) is 132.96. The max temperature of the warmest month is 31.81 degrees. The min temperature of the coldest month is 19.91 degrees. The temperature annual range is 11.91 degrees. The mean temperature of the wettest quarter is 25.53 degrees. The mean temperature of the driest quarter is 26.84 degrees. The mean temperature of the warmest quarter is 27.02 degrees. The mean temperature of the coldest quarter is 23.76 degrees. The annual precipitation is 1113.0 mm. The precipitation of the wettest month is 258.0 mm. The precipitation of the driest month is 18.0 mm. The precipitation seasonality (coefficient of variation) is 68.75. The precipitation of the wettest quarter is 518.0 mm. The precipitation of the driest quarter is 102.0 mm. The precipitation of the warmest quarter is 239.0 mm. The precipitation of the coldest quarter is 219.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 65", + "(B) 11", + "(C) 35", + "(D) 138", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L4022409_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0886", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.059912 and latitude -0.317391 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.85 degrees. The mean diurnal range is 14.39 degrees. The isothermality is 81.41. The temperature seasonality (100 times the standard deviation) is 70.72. The max temperature of the warmest month is 26.33 degrees. The min temperature of the coldest month is 8.65 degrees. The temperature annual range is 17.68 degrees. The mean temperature of the wettest quarter is 17.13 degrees. The mean temperature of the driest quarter is 17.18 degrees. The mean temperature of the warmest quarter is 17.80 degrees. The mean temperature of the coldest quarter is 16.04 degrees. The annual precipitation is 888.0 mm. The precipitation of the wettest month is 135.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 44.78. The precipitation of the wettest quarter is 322.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 228.0 mm. The precipitation of the coldest quarter is 268.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 3", + "(C) 36", + "(D) 102", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L7833802_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0887", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.086678 and latitude -0.360487 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 52", + "(B) 122", + "(C) 107", + "(D) 37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11815420_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0888", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.115220 and latitude -0.411950 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 86", + "(B) 67", + "(C) 18", + "(D) 138", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L2663788_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0889", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.536243 and latitude -0.548666 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 12.40 degrees. The mean diurnal range is 12.38 degrees. The isothermality is 77.59. The temperature seasonality (100 times the standard deviation) is 91.05. The max temperature of the warmest month is 21.01 degrees. The min temperature of the coldest month is 5.05 degrees. The temperature annual range is 15.96 degrees. The mean temperature of the wettest quarter is 13.37 degrees. The mean temperature of the driest quarter is 12.70 degrees. The mean temperature of the warmest quarter is 13.45 degrees. The mean temperature of the coldest quarter is 11.19 degrees. The annual precipitation is 1141.0 mm. The precipitation of the wettest month is 182.0 mm. The precipitation of the driest month is 46.0 mm. The precipitation seasonality (coefficient of variation) is 42.72. The precipitation of the wettest quarter is 436.0 mm. The precipitation of the driest quarter is 176.0 mm. The precipitation of the warmest quarter is 336.0 mm. The precipitation of the coldest quarter is 221.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 266", + "(B) 33", + "(C) 44", + "(D) 28", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L10964149_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0890", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.490874 and latitude -0.575399 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 171", + "(C) 34", + "(D) 88", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L1235046_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0891", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.468400 and latitude -0.596197 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 51", + "(B) 137", + "(C) 117", + "(D) 365", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11118238_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0892", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.075629 and latitude -0.436018 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 77", + "(B) 146", + "(C) 60", + "(D) 88", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L13020563_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0893", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.612265 and latitude -2.983033 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 19.85 degrees. The mean diurnal range is 12.01 degrees. The isothermality is 70.60. The temperature seasonality (100 times the standard deviation) is 154.49. The max temperature of the warmest month is 28.99 degrees. The min temperature of the coldest month is 11.98 degrees. The temperature annual range is 17.01 degrees. The mean temperature of the wettest quarter is 20.58 degrees. The mean temperature of the driest quarter is 17.96 degrees. The mean temperature of the warmest quarter is 21.53 degrees. The mean temperature of the coldest quarter is 17.70 degrees. The annual precipitation is 1038.0 mm. The precipitation of the wettest month is 218.0 mm. The precipitation of the driest month is 15.0 mm. The precipitation seasonality (coefficient of variation) is 80.55. The precipitation of the wettest quarter is 451.0 mm. The precipitation of the driest quarter is 47.0 mm. The precipitation of the warmest quarter is 283.0 mm. The precipitation of the coldest quarter is 56.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 53", + "(B) 129", + "(C) 91", + "(D) 69", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12135116_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0894", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.249964 and latitude -0.432776 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.44 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 80.53. The temperature seasonality (100 times the standard deviation) is 74.88. The max temperature of the warmest month is 26.14 degrees. The min temperature of the coldest month is 8.09 degrees. The temperature annual range is 18.06 degrees. The mean temperature of the wettest quarter is 16.69 degrees. The mean temperature of the driest quarter is 16.79 degrees. The mean temperature of the warmest quarter is 17.42 degrees. The mean temperature of the coldest quarter is 15.55 degrees. The annual precipitation is 735.0 mm. The precipitation of the wettest month is 116.0 mm. The precipitation of the driest month is 25.0 mm. The precipitation seasonality (coefficient of variation) is 40.06. The precipitation of the wettest quarter is 264.0 mm. The precipitation of the driest quarter is 100.0 mm. The precipitation of the warmest quarter is 201.0 mm. The precipitation of the coldest quarter is 192.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 171", + "(B) 18", + "(C) 54", + "(D) 11", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12667927_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0895", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.429561 and latitude -0.719988 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 16.56 degrees. The mean diurnal range is 13.56 degrees. The isothermality is 78.32. The temperature seasonality (100 times the standard deviation) is 98.50. The max temperature of the warmest month is 26.11 degrees. The min temperature of the coldest month is 8.79 degrees. The temperature annual range is 17.32 degrees. The mean temperature of the wettest quarter is 17.43 degrees. The mean temperature of the driest quarter is 15.27 degrees. The mean temperature of the warmest quarter is 17.68 degrees. The mean temperature of the coldest quarter is 15.22 degrees. The annual precipitation is 697.0 mm. The precipitation of the wettest month is 131.0 mm. The precipitation of the driest month is 33.0 mm. The precipitation seasonality (coefficient of variation) is 50.75. The precipitation of the wettest quarter is 288.0 mm. The precipitation of the driest quarter is 114.0 mm. The precipitation of the warmest quarter is 229.0 mm. The precipitation of the coldest quarter is 115.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 71", + "(B) 259", + "(C) 135", + "(D) 82", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L16347346_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0896", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.120112 and latitude -0.411840 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.04 degrees. The mean diurnal range is 14.53 degrees. The isothermality is 80.89. The temperature seasonality (100 times the standard deviation) is 74.37. The max temperature of the warmest month is 26.72 degrees. The min temperature of the coldest month is 8.76 degrees. The temperature annual range is 17.96 degrees. The mean temperature of the wettest quarter is 17.30 degrees. The mean temperature of the driest quarter is 17.41 degrees. The mean temperature of the warmest quarter is 18.03 degrees. The mean temperature of the coldest quarter is 16.18 degrees. The annual precipitation is 766.0 mm. The precipitation of the wettest month is 124.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 41.30. The precipitation of the wettest quarter is 277.0 mm. The precipitation of the driest quarter is 106.0 mm. The precipitation of the warmest quarter is 215.0 mm. The precipitation of the coldest quarter is 204.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 111", + "(B) 505", + "(C) 44", + "(D) 65", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L6680860_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0897", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 37.618337 and latitude -0.963265 in the state of Eastern, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 21.81 degrees. The mean diurnal range is 11.52 degrees. The isothermality is 75.52. The temperature seasonality (100 times the standard deviation) is 113.42. The max temperature of the warmest month is 29.97 degrees. The min temperature of the coldest month is 14.71 degrees. The temperature annual range is 15.26 degrees. The mean temperature of the wettest quarter is 22.28 degrees. The mean temperature of the driest quarter is 20.19 degrees. The mean temperature of the warmest quarter is 22.99 degrees. The mean temperature of the coldest quarter is 20.19 degrees. The annual precipitation is 777.0 mm. The precipitation of the wettest month is 203.0 mm. The precipitation of the driest month is 2.0 mm. The precipitation seasonality (coefficient of variation) is 104.94. The precipitation of the wettest quarter is 357.0 mm. The precipitation of the driest quarter is 13.0 mm. The precipitation of the warmest quarter is 305.0 mm. The precipitation of the coldest quarter is 13.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 64", + "(C) 15", + "(D) 105", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L14860959_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0898", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.456055 and latitude -0.569332 in the state of Central, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 15.66 degrees. The mean diurnal range is 14.48 degrees. The isothermality is 78.35. The temperature seasonality (100 times the standard deviation) is 87.54. The max temperature of the warmest month is 25.70 degrees. The min temperature of the coldest month is 7.22 degrees. The temperature annual range is 18.48 degrees. The mean temperature of the wettest quarter is 16.52 degrees. The mean temperature of the driest quarter is 16.13 degrees. The mean temperature of the warmest quarter is 16.73 degrees. The mean temperature of the coldest quarter is 14.51 degrees. The annual precipitation is 728.0 mm. The precipitation of the wettest month is 121.0 mm. The precipitation of the driest month is 31.0 mm. The precipitation seasonality (coefficient of variation) is 41.51. The precipitation of the wettest quarter is 274.0 mm. The precipitation of the driest quarter is 118.0 mm. The precipitation of the warmest quarter is 216.0 mm. The precipitation of the coldest quarter is 154.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 21", + "(B) 111", + "(C) 72", + "(D) 39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L11347994_visual.jpg" + ] + }, + { + "Question_id": "Species richness estimation/0899", + "Question Type": "Single Choice", + "Text": "This image shows the satellite view of a bird hotspot, which is located at longitude 36.032394 and latitude -0.058795 in the state of Rift Valley, Kenya. The 19 bioclimatic variables at this hotspot are as follows: The annual mean temperature is 17.84 degrees. The mean diurnal range is 14.54 degrees. The isothermality is 82.33. The temperature seasonality (100 times the standard deviation) is 67.72. The max temperature of the warmest month is 27.24 degrees. The min temperature of the coldest month is 9.59 degrees. The temperature annual range is 17.66 degrees. The mean temperature of the wettest quarter is 18.15 degrees. The mean temperature of the driest quarter is 18.15 degrees. The mean temperature of the warmest quarter is 18.75 degrees. The mean temperature of the coldest quarter is 17.04 degrees. The annual precipitation is 1005.0 mm. The precipitation of the wettest month is 152.0 mm. The precipitation of the driest month is 26.0 mm. The precipitation seasonality (coefficient of variation) is 45.79. The precipitation of the wettest quarter is 363.0 mm. The precipitation of the driest quarter is 116.0 mm. The precipitation of the warmest quarter is 254.0 mm. The precipitation of the coldest quarter is 306.0 mm. How many species of birds are likely to be present at this hotspot?", + "L1-task": "Cross-sphere", + "L2-task": "Bird species prediction", + "L3-task": "Reasoning", + "L4-task": "Species richness estimation", + "Dataset": "SatBird", + "Answer Choices": [ + "(A) 22", + "(B) 50", + "(C) 256", + "(D) 33", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Bird species prediction/images_visual_jpg/L12143078_visual.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Carbon_flux_monitoring/Reasoning/Carbon_flux_estimation.json b/jsons/Cross-sphere/Carbon_flux_monitoring/Reasoning/Carbon_flux_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..2d222259d959fb48511e9bd94d845814eec181ea --- /dev/null +++ b/jsons/Cross-sphere/Carbon_flux_monitoring/Reasoning/Carbon_flux_estimation.json @@ -0,0 +1,8912 @@ +[ + { + "Question_id": "Carbon flux estimation/0000", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -15.4391, longitude 23.2525. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.133384375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3483925 W/m^2. Vapor pressure deficit was -0.3630590909090909 kPa. Air pressure was 0.0350384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.469085 m/s. Wind direction was -0.4912499999999999 decimal degrees. Relative humidity was -0.0928664999999999 percent. Net radiation was -0.1708316666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3020428571428571 W/m^2. CO2 concentration was -0.298486 μmol CO2/mol. Soil heat flux was -0.1730999999999999 W/m^2. Latent heat flux was -0.1671447933333333 W/m^2. Sensible heat flux was -0.1795017166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -15.87", + "(B) 3.06", + "(C) 1.34", + "(D) 3.67", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ZM-Mon_2007-09-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0001", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -54.9733, longitude -66.7335. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.067384375 degrees Celsius. Incoming shortwave radiation was -0.4012845 W/m^2. Vapor pressure deficit was -0.4875090909090909 kPa. Air pressure was 0.1100653846153845 kPa. Wind speed was -0.47476 m/s. Wind direction was -0.315005 decimal degrees. Relative humidity was 0.3938575 percent. Incoming photosynthetic photon flux density was -0.324591328125 μmol Photon/m^2/s. CO2 concentration was -0.3051975 μmol CO2/mol. Latent heat flux was -0.1533744 W/m^2. Sensible heat flux was -0.1594795666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.75", + "(B) 0.11", + "(C) -6.89", + "(D) -3.34", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-TF1_2016-02-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0002", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -28.2395, longitude -56.1886. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1559375 degrees Celsius. Incoming shortwave radiation was 0.0093399999999999 W/m^2. Vapor pressure deficit was -0.4038136363636364 kPa. Air pressure was 0.1140730769230768 kPa. Wind speed was -0.47168 m/s. Wind direction was 0.1225055555555554 decimal degrees. Relative humidity was 0.1656149999999999 percent. Net radiation was 0.0511698333333333 W/m^2. Incoming photosynthetic photon flux density was 0.1746875 μmol Photon/m^2/s. CO2 concentration was -0.301863 μmol CO2/mol. Latent heat flux was -0.073971 W/m^2. Sensible heat flux was -0.0886716666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 6.65", + "(B) -9.34", + "(C) -26.13", + "(D) 0.79", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-Vir_2010-11-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0003", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.1167, longitude 11.3175. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.03460625 degrees Celsius. Incoming shortwave radiation was -0.3872925 W/m^2. Incoming longwave radiation was -0.34912 W/m^2. Vapor pressure deficit was -0.4843227272727273 kPa. Air pressure was 0.0353846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48951 m/s. Wind direction was -0.0130972222222223 decimal degrees. Relative humidity was 0.310355 percent. Net radiation was -0.1109595 W/m^2. Incoming photosynthetic photon flux density was -0.30094453125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.424226046875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4359818571428571 W/m^2. Outgoing longwave radiation was -0.2973261904761904 W/m^2. CO2 concentration was -0.28506925 μmol CO2/mol. Soil heat flux was -0.1660067456666666 W/m^2. Latent heat flux was -0.1615649166666666 W/m^2. Sensible heat flux was -0.16632267 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 8.54", + "(B) 8.62", + "(C) -0.45", + "(D) 4.34", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AT-Neu_2007-03-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0004", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -13.0769, longitude 131.1178. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.183 degrees Celsius. Incoming shortwave radiation was -0.40775 W/m^2. Incoming longwave radiation was -0.288 W/m^2. Vapor pressure deficit was -0.3759681818181818 kPa. Air pressure was 0.1124230769230768 kPa. Wind speed was -0.4816499999999999 m/s. Wind direction was 0.3916666666666666 decimal degrees. Relative humidity was 0.165 percent. Net radiation was -0.1295 W/m^2. Outgoing shortwave radiation was -0.4421428571428571 W/m^2. Outgoing longwave radiation was -0.2264285714285714 W/m^2. CO2 concentration was -0.3153 μmol CO2/mol. Soil heat flux was -0.18030555 W/m^2. Latent heat flux was -0.1308333333333333 W/m^2. Sensible heat flux was -0.1658333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.62", + "(B) 0.76", + "(C) -2.55", + "(D) -3.71", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ade_2007-11-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0005", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -22.283, longitude 133.249. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1065 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32675 W/m^2. Vapor pressure deficit was -0.4876363636363636 kPa. Air pressure was 0.070576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4882999999999999 m/s. Wind direction was 0.1444444444444444 decimal degrees. Relative humidity was 0.43 percent. Net radiation was -0.1836666666666666 W/m^2. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2630952380952381 W/m^2. CO2 concentration was -0.2993 μmol CO2/mol. Soil heat flux was -0.1796666666666666 W/m^2. Latent heat flux was -0.1655087716666666 W/m^2. Sensible heat flux was -0.1699736833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.66", + "(B) 0.1", + "(C) 0.28", + "(D) -0.26", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-ASM_2010-09-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0006", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -34.0021, longitude 140.5891. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0755 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3205 W/m^2. Vapor pressure deficit was -0.4619136363636363 kPa. Air pressure was 0.1212307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46165 m/s. Wind direction was 0.3527777777777778 decimal degrees. Relative humidity was 0.21 percent. Net radiation was -0.1716666666666666 W/m^2. Outgoing shortwave radiation was -0.4526190476190476 W/m^2. Outgoing longwave radiation was -0.2752380952380952 W/m^2. CO2 concentration was -0.30871225 μmol CO2/mol. Soil heat flux was -0.1656666666666666 W/m^2. Latent heat flux was -0.1635844699999999 W/m^2. Sensible heat flux was -0.1814503999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.72", + "(B) 0.27", + "(C) 0.86", + "(D) -0.85", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cpr_2010-08-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0007", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -33.6152, longitude 150.7236. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10115625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33275 W/m^2. Vapor pressure deficit was -0.4623409090909091 kPa. Air pressure was 0.1231153846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4911 m/s. Wind direction was 0.6861111111111111 decimal degrees. Relative humidity was 0.275 percent. Net radiation was -0.1855 W/m^2. Outgoing shortwave radiation was -0.4519047619047619 W/m^2. Outgoing longwave radiation was -0.2680952380952381 W/m^2. CO2 concentration was -0.29675 μmol CO2/mol. Soil heat flux was -0.1708333333333333 W/m^2. Latent heat flux was -0.1675 W/m^2. Sensible heat flux was -0.1665 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -8.39", + "(B) 2.09", + "(C) -5.85", + "(D) 3.88", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Cum_2012-10-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0008", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -15.2588, longitude 132.3706. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.12940625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3355 W/m^2. Vapor pressure deficit was -0.3745227272727273 kPa. Air pressure was 0.1113461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48435 m/s. Wind direction was -0.0861111111111111 decimal degrees. Relative humidity was -0.065 percent. Net radiation was -0.1936666666666666 W/m^2. Outgoing shortwave radiation was -0.4509523809523809 W/m^2. Outgoing longwave radiation was -0.2538095238095238 W/m^2. CO2 concentration was -0.308725 μmol CO2/mol. Soil heat flux was -0.1829234166666666 W/m^2. Latent heat flux was -0.1646666666666666 W/m^2. Sensible heat flux was -0.178 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.26", + "(B) 1.29", + "(C) -0.29", + "(D) 2.64", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Dry_2009-06-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0009", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -23.8587, longitude 148.4746. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0510625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32475 W/m^2. Vapor pressure deficit was -0.4876636363636363 kPa. Air pressure was 0.1129615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45575 m/s. Wind direction was -0.1166666666666666 decimal degrees. Relative humidity was 0.375 percent. Net radiation was -0.1686666666666666 W/m^2. Outgoing shortwave radiation was -0.4519047619047619 W/m^2. Outgoing longwave radiation was -0.2828571428571428 W/m^2. CO2 concentration was -0.309 μmol CO2/mol. Soil heat flux was -0.1774840499999999 W/m^2. Latent heat flux was -0.1566666666666666 W/m^2. Sensible heat flux was -0.1655 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.24", + "(B) 0.6", + "(C) 2.47", + "(D) -2.77", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Emr_2011-06-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0010", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -12.5452, longitude 131.3072. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15675 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.305 W/m^2. Vapor pressure deficit was -0.4782863636363636 kPa. Air pressure was 0.1191538461538461 kPa. Wind speed was -0.48 m/s. Wind direction was -0.3416666666666667 decimal degrees. Relative humidity was 0.425 percent. Net radiation was -0.178 W/m^2. Outgoing shortwave radiation was -0.4514285714285714 W/m^2. Outgoing longwave radiation was -0.2514285714285714 W/m^2. CO2 concentration was -0.30095 μmol CO2/mol. Soil heat flux was -0.1688333333333333 W/m^2. Latent heat flux was -0.1321666666666666 W/m^2. Sensible heat flux was -0.1638333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.86", + "(B) 0.45", + "(C) -2.49", + "(D) -6.67", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Fog_2006-02-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0011", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -31.3764, longitude 115.7138. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1260312499999999 degrees Celsius. Incoming shortwave radiation was -0.12575 W/m^2. Incoming longwave radiation was -0.31625 W/m^2. Vapor pressure deficit was -0.3872409090909091 kPa. Air pressure was 0.1204615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4511 m/s. Wind direction was 0.1694444444444444 decimal degrees. Relative humidity was -0.02 percent. Net radiation was 0.023 W/m^2. Outgoing shortwave radiation was -0.4028571428571428 W/m^2. Outgoing longwave radiation was -0.2416666666666666 W/m^2. CO2 concentration was -0.3122625 μmol CO2/mol. Soil heat flux was -0.1471388833333333 W/m^2. Latent heat flux was -0.1145 W/m^2. Sensible heat flux was -0.0715 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.37", + "(B) -5.98", + "(C) 0.33", + "(D) 1.9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Gin_2011-10-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0012", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -30.1913, longitude 120.6541. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1964375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.31075 W/m^2. Vapor pressure deficit was -0.1545545454545454 kPa. Air pressure was 0.0801538461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46545 m/s. Wind direction was -0.9472222222222222 decimal degrees. Relative humidity was -0.325 percent. Net radiation was -0.1941666666666666 W/m^2. Outgoing shortwave radiation was -0.4511904761904762 W/m^2. Outgoing longwave radiation was -0.2361904761904762 W/m^2. CO2 concentration was -0.3066 μmol CO2/mol. Soil heat flux was -0.179 W/m^2. Latent heat flux was -0.1668333333333333 W/m^2. Sensible heat flux was -0.1665 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.53", + "(B) -2.92", + "(C) 0.21", + "(D) 1.13", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-GWW_2013-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0013", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -34.4704, longitude 140.6551. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.095875 degrees Celsius. Incoming shortwave radiation was -0.4605 W/m^2. Incoming longwave radiation was -0.35025 W/m^2. Vapor pressure deficit was -0.4135454545454545 kPa. Air pressure was 0.130076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47005 m/s. Wind direction was 0.5 decimal degrees. Relative humidity was -0.045 percent. Net radiation was -0.1735 W/m^2. Outgoing shortwave radiation was -0.445 W/m^2. Outgoing longwave radiation was -0.2695238095238095 W/m^2. CO2 concentration was -0.32135 μmol CO2/mol. Soil heat flux was -0.17475 W/m^2. Latent heat flux was -0.157 W/m^2. Sensible heat flux was -0.1675 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -9.8", + "(B) 2.3", + "(C) 0.32", + "(D) -20.54", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Lox_2008-08-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0014", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -14.5636, longitude 132.4776. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.21553125 degrees Celsius. Incoming shortwave radiation was -0.1845 W/m^2. Incoming longwave radiation was -0.2875 W/m^2. Vapor pressure deficit was -0.1297863636363636 kPa. Air pressure was 0.1034999999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.473 m/s. Wind direction was -0.325 decimal degrees. Relative humidity was -0.245 percent. Net radiation was -0.024 W/m^2. Outgoing shortwave radiation was -0.4080952380952381 W/m^2. Outgoing longwave radiation was -0.1978571428571428 W/m^2. CO2 concentration was -0.3111 μmol CO2/mol. Soil heat flux was -0.1486666666666666 W/m^2. Latent heat flux was -0.0748333333333333 W/m^2. Sensible heat flux was -0.1141666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.57", + "(B) -0.65", + "(C) 7.08", + "(D) 1.61", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-RDF_2011-10-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0015", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -36.6499, longitude 145.5759. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.156375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.289 W/m^2. Vapor pressure deficit was -0.3672454545454545 kPa. Air pressure was 0.1074615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49335 m/s. Wind direction was -0.3055555555555556 decimal degrees. Relative humidity was 0.04 percent. Net radiation was -0.1723333333333333 W/m^2. Outgoing shortwave radiation was -0.4526190476190476 W/m^2. Outgoing longwave radiation was -0.2438095238095238 W/m^2. CO2 concentration was -0.277925 μmol CO2/mol. Soil heat flux was -0.172 W/m^2. Latent heat flux was -0.1663333333333333 W/m^2. Sensible heat flux was -0.1678333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.74", + "(B) -0.68", + "(C) 3.83", + "(D) 2.39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rig_2011-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0016", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -17.1175, longitude 145.6301. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.170375 degrees Celsius. Incoming shortwave radiation was -0.373 W/m^2. Incoming longwave radiation was -0.30625 W/m^2. Vapor pressure deficit was -0.4324454545454546 kPa. Air pressure was 0.0569615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4804 m/s. Wind direction was -0.8972222222222223 decimal degrees. Relative humidity was 0.295 percent. Net radiation was -0.114 W/m^2. Outgoing shortwave radiation was -0.435 W/m^2. Outgoing longwave radiation was -0.239047619047619 W/m^2. CO2 concentration was -0.32285 μmol CO2/mol. Soil heat flux was -0.1544166666666666 W/m^2. Latent heat flux was -0.1481666666666666 W/m^2. Sensible heat flux was -0.149 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.63", + "(B) -3.74", + "(C) 2.74", + "(D) 3.55", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Rob_2014-01-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0017", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -17.1507, longitude 133.3502. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.233625 degrees Celsius. Incoming shortwave radiation was -0.1455 W/m^2. Incoming longwave radiation was -0.30225 W/m^2. Vapor pressure deficit was 0.0184181818181818 kPa. Air pressure was 0.1011923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47485 m/s. Wind direction was -0.1805555555555555 decimal degrees. Relative humidity was -0.39 percent. Net radiation was -0.0608333333333333 W/m^2. Outgoing shortwave radiation was -0.3764285714285714 W/m^2. Outgoing longwave radiation was -0.1652380952380952 W/m^2. CO2 concentration was -0.3026999999999999 μmol CO2/mol. Soil heat flux was -0.1366666666666666 W/m^2. Latent heat flux was -0.1588333333333333 W/m^2. Sensible heat flux was -0.09 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.75", + "(B) 0.46", + "(C) -0.24", + "(D) 0.42", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Stp_2009-10-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0018", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -22.287, longitude 133.64. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0572812499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.36325 W/m^2. Vapor pressure deficit was -0.42765 kPa. Air pressure was 0.0823846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48195 m/s. Wind direction was -0.1722222222222222 decimal degrees. Relative humidity was -0.185 percent. Net radiation was -0.1893333333333333 W/m^2. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2895238095238095 W/m^2. CO2 concentration was -0.309625 μmol CO2/mol. Soil heat flux was -0.1801666666666666 W/m^2. Latent heat flux was -0.1666666666666666 W/m^2. Sensible heat flux was -0.1693333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.12", + "(B) 1.39", + "(C) -0.3", + "(D) 0.79", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-TTE_2012-07-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0019", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -37.4259, longitude 145.1878. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0577812499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32275 W/m^2. Vapor pressure deficit was -0.4893863636363637 kPa. Air pressure was 0.0481923076923076 kPa. Precipitation was recorded at -0.4906666666666666 mm. Wind speed was -0.3954999999999999 m/s. Wind direction was 0.4027777777777778 decimal degrees. Relative humidity was 0.4 percent. Net radiation was -0.172 W/m^2. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2757142857142857 W/m^2. CO2 concentration was -0.2865749999999999 μmol CO2/mol. Soil heat flux was -0.1673333333333333 W/m^2. Latent heat flux was -0.1098333333333333 W/m^2. Sensible heat flux was -0.2091666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -8.59", + "(B) 3.33", + "(C) 0.29", + "(D) -9.26", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wac_2005-08-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0020", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -36.6732, longitude 145.0294. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10734375 degrees Celsius. Incoming shortwave radiation was -0.261875 W/m^2. Incoming longwave radiation was -0.32875 W/m^2. Vapor pressure deficit was -0.40735 kPa. Air pressure was 0.1169615384615384 kPa. Wind speed was -0.45255 m/s. Wind direction was -0.0833333333333333 decimal degrees. Relative humidity was -0.02 percent. Net radiation was -0.0453333333333333 W/m^2. Outgoing shortwave radiation was -0.4221428571428571 W/m^2. Outgoing longwave radiation was -0.2509523809523809 W/m^2. CO2 concentration was -0.318975 μmol CO2/mol. Soil heat flux was -0.1331666666666666 W/m^2. Latent heat flux was -0.124 W/m^2. Sensible heat flux was -0.0711666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -10.14", + "(B) -3.16", + "(C) 2.08", + "(D) -6.74", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Whr_2011-12-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0021", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -37.4222, longitude 144.0944. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0883125 degrees Celsius. Incoming shortwave radiation was -0.147 W/m^2. Incoming longwave radiation was -0.3405 W/m^2. Vapor pressure deficit was -0.4625318181818182 kPa. Air pressure was 0.0656923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46255 m/s. Wind direction was -0.5722222222222222 decimal degrees. Relative humidity was 0.245 percent. Net radiation was 0.0183333333333333 W/m^2. Outgoing shortwave radiation was -0.4145238095238095 W/m^2. Outgoing longwave radiation was -0.2664285714285714 W/m^2. CO2 concentration was -0.31095 μmol CO2/mol. Soil heat flux was -0.1645 W/m^2. Latent heat flux was -0.1088333333333333 W/m^2. Sensible heat flux was -0.0865 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -8.99", + "(B) -19.9", + "(C) 0.87", + "(D) 3.73", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Wom_2010-03-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0022", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -34.9893, longitude 146.2907. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1639999999999999 degrees Celsius. Incoming shortwave radiation was -0.18375 W/m^2. Incoming longwave radiation was -0.32525 W/m^2. Vapor pressure deficit was -0.2442227272727272 kPa. Air pressure was 0.1163461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47005 m/s. Wind direction was -0.2055555555555555 decimal degrees. Relative humidity was -0.325 percent. Net radiation was -0.0483333333333333 W/m^2. Outgoing shortwave radiation was -0.3959523809523809 W/m^2. Outgoing longwave radiation was -0.2102380952380952 W/m^2. CO2 concentration was -0.31525 μmol CO2/mol. Soil heat flux was -0.1391666666666666 W/m^2. Latent heat flux was -0.1519166666666666 W/m^2. Sensible heat flux was -0.0766666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.11", + "(B) -1.96", + "(C) 0.21", + "(D) 0.33", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AU-Ync_2012-10-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0023", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 51.3076, longitude 4.5198. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1086562499999999 degrees Celsius. Incoming shortwave radiation was -0.4266825 W/m^2. Incoming longwave radiation was -0.3099595 W/m^2. Vapor pressure deficit was -0.4588772727272727 kPa. Air pressure was 0.1224999999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47515 m/s. Wind direction was 0.4091666666666667 decimal degrees. Relative humidity was 0.2722499999999999 percent. Net radiation was -0.1195233333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3456828125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4346984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4468380952380952 W/m^2. Outgoing longwave radiation was -0.2599761904761904 W/m^2. CO2 concentration was -0.2915225 μmol CO2/mol. Soil heat flux was -0.1655166666666666 W/m^2. Latent heat flux was -0.1364333333333333 W/m^2. Sensible heat flux was -0.1642201666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.13", + "(B) -15.95", + "(C) 0.51", + "(D) -6.61", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Bra_2021-08-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0024", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.5516, longitude 4.7462. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06759375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3306 W/m^2. Vapor pressure deficit was -0.4903090909090908 kPa. Air pressure was 0.1138461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4942049999999999 m/s. Wind direction was -0.3272222222222222 decimal degrees. Relative humidity was 0.4178 percent. Net radiation was -0.1765166666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4513333333333333 W/m^2. Outgoing longwave radiation was -0.2783095238095238 W/m^2. CO2 concentration was -0.288781 μmol CO2/mol. Soil heat flux was -0.1725016666666666 W/m^2. Latent heat flux was -0.1661870833333333 W/m^2. Sensible heat flux was -0.1669152049999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.61", + "(B) -14.62", + "(C) 0.96", + "(D) 11.56", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Lon_2014-08-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0025", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.979868, longitude 5.631851. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.04553125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3634 W/m^2. Vapor pressure deficit was -0.4772454545454545 kPa. Air pressure was 0.1233846153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4778 m/s. Wind direction was -0.863611111111111 decimal degrees. Relative humidity was 0.2550999999999999 percent. Net radiation was -0.1912833333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43765 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4524714285714286 W/m^2. Outgoing longwave radiation was -0.2891857142857142 W/m^2. CO2 concentration was -0.2892575 μmol CO2/mol. Soil heat flux was -0.175065 W/m^2. Latent heat flux was -0.16891 W/m^2. Sensible heat flux was -0.1838216666666667 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.74", + "(B) -3.34", + "(C) 1.09", + "(D) 2.41", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BE-Maa_2020-05-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0026", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -7.9682, longitude -38.3842. This site belongs to the Deciduous Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of seasonal needleleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.172428125 degrees Celsius. Incoming shortwave radiation was -0.29475 W/m^2. Vapor pressure deficit was -0.3252772727272727 kPa. Air pressure was 0.092926923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48353 m/s. Wind direction was 0.3293236852524916 decimal degrees. Relative humidity was -0.020661869681941 percent. Net radiation was -0.00975 W/m^2. CO2 concentration was -0.3272575 μmol CO2/mol. Latent heat flux was -0.1564982333333333 W/m^2. Sensible heat flux was -0.0838785 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -5.77", + "(B) -0.46", + "(C) 7.51", + "(D) -0.8", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-CST_2014-06-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0027", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -16.498, longitude -56.412. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1440625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.2916069999999999 W/m^2. Vapor pressure deficit was -0.4909090909090909 kPa. Air pressure was 0.1127692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4882 m/s. Wind direction was 0.0281388888888888 decimal degrees. Relative humidity was 0.4645 percent. Net radiation was -0.17587 W/m^2. Outgoing shortwave radiation was -0.4518022642857143 W/m^2. Outgoing longwave radiation was -0.2417619761904762 W/m^2. CO2 concentration was -0.2878825 μmol CO2/mol. Latent heat flux was -0.16672 W/m^2. Sensible heat flux was -0.167855 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -13.79", + "(B) -15.56", + "(C) 5.06", + "(D) -6.65", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Npw_2013-12-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0028", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -3.018, longitude -54.9714. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.17675 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.29618 W/m^2. Vapor pressure deficit was -0.3672272727272727 kPa. Air pressure was 0.1041153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4796 m/s. Wind direction was -0.4323333333333333 decimal degrees. Relative humidity was 0.123055 percent. Net radiation was -0.1766266666666666 W/m^2. Incoming photosynthetic photon flux density was -0.438790625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437415625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523738095238095 W/m^2. Outgoing longwave radiation was -0.2345523809523809 W/m^2. CO2 concentration was -0.3092899999999999 μmol CO2/mol. Soil heat flux was -0.1672116666666666 W/m^2. Latent heat flux was -0.1655800483333333 W/m^2. Sensible heat flux was -0.1670416666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.58", + "(B) -14.53", + "(C) 5.59", + "(D) 9.5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/BR-Sa3_2001-08-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0029", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 52.695, longitude -83.9452. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.01828125 degrees Celsius. Incoming shortwave radiation was -0.15179925 W/m^2. Incoming longwave radiation was -0.3954864999999999 W/m^2. Vapor pressure deficit was -0.4739727272727272 kPa. Air pressure was 0.1253846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4686 m/s. Wind direction was 0.74333335 decimal degrees. Relative humidity was -0.080750005 percent. Outgoing shortwave radiation was -0.2157767014285714 W/m^2. Outgoing longwave radiation was -0.3102407473809523 W/m^2. CO2 concentration was -0.3006447499999999 μmol CO2/mol. Soil heat flux was -0.1671197216666666 W/m^2. Latent heat flux was -0.14775505 W/m^2. Sensible heat flux was -0.1615366506666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARB_2011-03-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0030", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 52.7008, longitude -83.955. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0918124999999999 degrees Celsius. Incoming shortwave radiation was -0.1286999999999999 W/m^2. Incoming longwave radiation was -0.3402034999999999 W/m^2. Vapor pressure deficit was -0.4451409090909091 kPa. Air pressure was 0.1103846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.446945 m/s. Wind direction was -0.4619444527777778 decimal degrees. Relative humidity was 0.13959999 percent. Outgoing shortwave radiation was -0.4082619038095238 W/m^2. Outgoing longwave radiation was -0.2546676561904761 W/m^2. CO2 concentration was -0.3115035 μmol CO2/mol. Soil heat flux was -0.1658108916666666 W/m^2. Latent heat flux was -0.1080481666666666 W/m^2. Sensible heat flux was -0.1142178333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.6", + "(B) -5.27", + "(C) -0.59", + "(D) -1.11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ARF_2011-07-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0031", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.8705, longitude -125.2909. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15059375 degrees Celsius. Incoming shortwave radiation was -0.2396 W/m^2. Vapor pressure deficit was -0.3702545454545454 kPa. Air pressure was 0.1128846153846153 kPa. Wind speed was -0.484295 m/s. Wind direction was -0.7431666666666668 decimal degrees. Relative humidity was 0.0246999999999999 percent. Net radiation was -0.0575999999999999 W/m^2. Incoming photosynthetic photon flux density was -0.1107968749999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.413778125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4170261904761905 W/m^2. CO2 concentration was -0.31436675 μmol CO2/mol. Soil heat flux was -0.15764935 W/m^2. Latent heat flux was -0.15442105 W/m^2. Sensible heat flux was -0.1047604999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.53", + "(B) -6.3", + "(C) -6.34", + "(D) 2.93", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Ca2_2000-07-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0032", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.3167, longitude -79.9333. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.133021875 degrees Celsius. Incoming shortwave radiation was -0.20649 W/m^2. Incoming longwave radiation was -0.3445674999999999 W/m^2. Vapor pressure deficit was -0.3222772727272728 kPa. Air pressure was 0.1102384615384615 kPa. Wind speed was -0.474735 m/s. Wind direction was -0.0305246286111112 decimal degrees. Relative humidity was -0.27229 percent. Net radiation was -0.0327993383333333 W/m^2. Incoming photosynthetic photon flux density was -0.07621875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4181367187499999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4246319047619047 W/m^2. Outgoing longwave radiation was -0.2438047642857143 W/m^2. CO2 concentration was -0.305377 μmol CO2/mol. Soil heat flux was -0.1592554 W/m^2. Latent heat flux was -0.1466332666666666 W/m^2. Sensible heat flux was -0.0962941666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 11.03", + "(B) 1.32", + "(C) 0.66", + "(D) 11.69", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Cbo_2005-04-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0033", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 58.6658, longitude -93.83. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.041075 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4753318181818182 kPa. Air pressure was 0.1161538461538461 kPa. Wind speed was -0.46593 m/s. Wind direction was 0.0850169444444445 decimal degrees. Relative humidity was 0.2211499999999999 percent. Net radiation was -0.1829749999999999 W/m^2. Incoming photosynthetic photon flux density was -0.4374403125 μmol Photon/m^2/s. CO2 concentration was -0.304314 μmol CO2/mol. Latent heat flux was -0.1610301499999999 W/m^2. Sensible heat flux was -0.1717063999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.49", + "(B) 1.01", + "(C) -1.44", + "(D) -0.56", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-CF1_2007-06-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0034", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.119, longitude -122.9951. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.047065625 degrees Celsius. Incoming shortwave radiation was -0.499973 W/m^2. Incoming longwave radiation was -0.33513225 W/m^2. Vapor pressure deficit was -0.4862636363636363 kPa. Air pressure was 0.1177576923076922 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4604749999999999 m/s. Wind direction was 0.5399225888888888 decimal degrees. Relative humidity was 0.3544405 percent. Net radiation was -0.1718480031666666 W/m^2. Outgoing shortwave radiation was -0.4519856273809524 W/m^2. Outgoing longwave radiation was -0.2884462338095238 W/m^2. CO2 concentration was -0.301066 μmol CO2/mol. Soil heat flux was -0.1684782333333333 W/m^2. Latent heat flux was -0.1633223933333333 W/m^2. Sensible heat flux was -0.1771899166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.18", + "(B) 2.49", + "(C) -2.65", + "(D) 0.57", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DB2_2020-01-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0035", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.1293, longitude -122.9849. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0729749999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32575125 W/m^2. Vapor pressure deficit was -0.4758409090909091 kPa. Air pressure was 0.1234807692307691 kPa. Precipitation was recorded at -0.4973333333333333 mm. Wind speed was -0.4819449999999999 m/s. Wind direction was 0.5515583333333335 decimal degrees. Relative humidity was 0.30735 percent. Net radiation was -0.1708716666666666 W/m^2. Outgoing shortwave radiation was -0.4518701307142856 W/m^2. Outgoing longwave radiation was -0.2769952380952381 W/m^2. CO2 concentration was -0.29610725 μmol CO2/mol. Soil heat flux was -0.1719731166666666 W/m^2. Latent heat flux was -0.16707532 W/m^2. Sensible heat flux was -0.169667785 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.37", + "(B) 0.03", + "(C) 0.49", + "(D) 1.26", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-DBB_2016-06-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0036", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.6405, longitude -80.4123. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1019781249999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4722454545454546 kPa. Air pressure was 0.0944153846153846 kPa. Wind speed was -0.49522 m/s. Wind direction was 0.5861683944444445 decimal degrees. Relative humidity was 0.33554831 percent. CO2 concentration was -0.24341975 μmol CO2/mol. Latent heat flux was -0.16609348 W/m^2. Sensible heat flux was -0.1666395375 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-ER1_2015-06-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0037", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 48.2167, longitude -82.1556. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1100125 degrees Celsius. Incoming shortwave radiation was -0.4995032499999999 W/m^2. Incoming longwave radiation was -0.34153975 W/m^2. Vapor pressure deficit was -0.4296863636363636 kPa. Air pressure was 0.0977807692307692 kPa. Precipitation was recorded at -0.49978 mm. Wind speed was -0.465245 m/s. Wind direction was 0.33475 decimal degrees. Relative humidity was 0.1163 percent. Net radiation was -0.1917215 W/m^2. Incoming photosynthetic photon flux density was -0.436064375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374471874999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522788095238095 W/m^2. Outgoing longwave radiation was -0.2653028571428571 W/m^2. CO2 concentration was -0.3003207499999999 μmol CO2/mol. Soil heat flux was -0.1748521666666666 W/m^2. Latent heat flux was -0.15777 W/m^2. Sensible heat flux was -0.1803116666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.56", + "(B) 1.02", + "(C) 0.79", + "(D) 0.27", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Gro_2003-08-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0038", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.1119, longitude -122.8414. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0596624999999999 degrees Celsius. Incoming shortwave radiation was -0.343125 W/m^2. Incoming longwave radiation was -0.36022275 W/m^2. Vapor pressure deficit was -0.4436 kPa. Air pressure was 0.0511423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48682 m/s. Wind direction was 0.7975000000000001 decimal degrees. Relative humidity was -0.0207 percent. Net radiation was -0.0979466666666666 W/m^2. Incoming photosynthetic photon flux density was -0.2385 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.420134375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4353547619047619 W/m^2. Outgoing longwave radiation was -0.285052619047619 W/m^2. CO2 concentration was -0.30107425 μmol CO2/mol. Soil heat flux was -0.1669825556666666 W/m^2. Latent heat flux was -0.1568655666666666 W/m^2. Sensible heat flux was -0.132984 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.15", + "(B) -2.44", + "(C) 0.41", + "(D) -4.32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-LP1_2007-05-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0039", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.1645, longitude -97.8762. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1266375 degrees Celsius. Incoming shortwave radiation was -0.0265659999999999 W/m^2. Vapor pressure deficit was -0.3489909090909091 kPa. Air pressure was 0.102576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.476325 m/s. Wind direction was -0.0948333333333333 decimal degrees. Relative humidity was -0.1987 percent. Incoming photosynthetic photon flux density was 0.13153125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3960546875 μmol Photon/m^2/s. CO2 concentration was -0.30237225 μmol CO2/mol. Soil heat flux was -0.13821825 W/m^2. Latent heat flux was -0.1288921666666666 W/m^2. Sensible heat flux was -0.070112 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.43", + "(B) 0.08", + "(C) 5.22", + "(D) 3.23", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA1_2009-05-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0040", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.171, longitude -97.8762. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0069875 degrees Celsius. Incoming shortwave radiation was -0.4254825 W/m^2. Incoming longwave radiation was -0.3391142499999999 W/m^2. Vapor pressure deficit was -0.4954318181818182 kPa. Air pressure was 0.0899230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.43993 m/s. Wind direction was -0.2529444444444444 decimal degrees. Relative humidity was 0.42423 percent. Net radiation was -0.12772545 W/m^2. Incoming photosynthetic photon flux density was -0.3208234375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42442421875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4384383333333333 W/m^2. Outgoing longwave radiation was -0.2977601428571428 W/m^2. CO2 concentration was -0.2974985 μmol CO2/mol. Soil heat flux was -0.1672728116666667 W/m^2. Latent heat flux was -0.16110755 W/m^2. Sensible heat flux was -0.1586631333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.08", + "(B) 2.04", + "(C) -1.21", + "(D) 2.84", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA2_2009-05-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0041", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.1774, longitude -97.8686. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.085359375 degrees Celsius. Incoming shortwave radiation was -0.1321875 W/m^2. Incoming longwave radiation was -0.29644475 W/m^2. Vapor pressure deficit was -0.4162681818181818 kPa. Air pressure was 0.1076153846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.447985 m/s. Wind direction was -0.3881666666666667 decimal degrees. Relative humidity was -0.0889399999999999 percent. Net radiation was -0.0117623333333333 W/m^2. Incoming photosynthetic photon flux density was 0.06859375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.398790625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.368947619047619 W/m^2. Outgoing longwave radiation was -0.2129465238095237 W/m^2. CO2 concentration was -0.30281125 μmol CO2/mol. Soil heat flux was -0.15942325 W/m^2. Latent heat flux was -0.11658 W/m^2. Sensible heat flux was -0.1182246666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -16.3", + "(B) -10.55", + "(C) 1.32", + "(D) 1.42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-MA3_2009-06-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0042", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.8792, longitude -98.4839. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.176375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.2941 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4791899999999999 m/s. Wind direction was -0.8353611111111111 decimal degrees. Relative humidity was -0.123335 percent. Net radiation was -0.183293 W/m^2. Incoming photosynthetic photon flux density was -0.4339859375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375325 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4529557142857143 W/m^2. CO2 concentration was -0.3281415 μmol CO2/mol. Latent heat flux was -0.16550575 W/m^2. Sensible heat flux was -0.1714714166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS1_2002-06-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0043", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.9117, longitude -98.3822. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.02741875 degrees Celsius. Incoming shortwave radiation was -0.37514425 W/m^2. Vapor pressure deficit was -0.4642045454545455 kPa. Precipitation was recorded at -0.4932233333333334 mm. Wind speed was -0.47293 m/s. Wind direction was 0.0455333333333334 decimal degrees. Relative humidity was 0.028965 percent. Net radiation was -0.126233 W/m^2. Incoming photosynthetic photon flux density was -0.31297171875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42991046875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4364290476190476 W/m^2. CO2 concentration was -0.309257 μmol CO2/mol. Latent heat flux was -0.1599305 W/m^2. Sensible heat flux was -0.1430247666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 6.49", + "(B) 1.61", + "(C) 0.77", + "(D) -2.42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS3_2001-09-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0044", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.8631, longitude -98.485. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.063690625 degrees Celsius. Incoming shortwave radiation was -0.37681725 W/m^2. Vapor pressure deficit was -0.4331090909090909 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46942 m/s. Wind direction was -0.0550722222222222 decimal degrees. Relative humidity was -0.091015 percent. Net radiation was -0.1228308333333333 W/m^2. Incoming photosynthetic photon flux density was -0.26397140625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42587921875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4288152380952381 W/m^2. CO2 concentration was -0.30622 μmol CO2/mol. Latent heat flux was -0.1638350833333333 W/m^2. Sensible heat flux was -0.1417065 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.32", + "(B) -4.03", + "(C) 0.05", + "(D) -4.36", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS5_2001-09-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0045", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.9167, longitude -98.9644. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07284375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4320409090909091 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.470175 m/s. Wind direction was 0.3670888888888888 decimal degrees. Relative humidity was -0.0450249999999999 percent. Net radiation was -0.1897658333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4364096875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43752 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4526959523809524 W/m^2. CO2 concentration was -0.30550175 μmol CO2/mol. Latent heat flux was -0.1625595 W/m^2. Sensible heat flux was -0.2006281666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.63", + "(B) 0.12", + "(C) 0.01", + "(D) 1.45", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS6_2001-10-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0046", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.6358, longitude -99.9483. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06703125 degrees Celsius. Incoming shortwave radiation was -0.441044 W/m^2. Vapor pressure deficit was -0.4946409090909091 kPa. Precipitation was recorded at -0.49915 mm. Wind speed was -0.478235 m/s. Wind direction was 0.2093722222222223 decimal degrees. Relative humidity was 0.45429 percent. Net radiation was -0.1376613333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3499928125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43440796875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.447927380952381 W/m^2. CO2 concentration was -0.3217915 μmol CO2/mol. Latent heat flux was -0.1562181333333333 W/m^2. Sensible heat flux was -0.1641389833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.78", + "(B) 0.34", + "(C) 0.26", + "(D) -6.85", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-NS7_2002-07-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0047", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.6925, longitude -74.3421. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.041371875 degrees Celsius. Incoming shortwave radiation was -0.339275 W/m^2. Incoming longwave radiation was -0.3547975 W/m^2. Vapor pressure deficit was -0.4670863636363636 kPa. Air pressure was 0.0838461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.446525 m/s. Wind direction was -0.0669444444444445 decimal degrees. Relative humidity was 0.12945 percent. Net radiation was -0.0857466666666666 W/m^2. Incoming photosynthetic photon flux density was -0.24512046875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4223757812499999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4383880952380952 W/m^2. Outgoing longwave radiation was -0.2906166666666667 W/m^2. CO2 concentration was -0.3078424999999999 μmol CO2/mol. Soil heat flux was -0.1670663333333333 W/m^2. Latent heat flux was -0.163626 W/m^2. Sensible heat flux was -0.140605 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.34", + "(B) 0.04", + "(C) 0.12", + "(D) 0.83", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-Qfo_2004-04-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0048", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 54.485, longitude -105.8176. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0946875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.344925 W/m^2. Vapor pressure deficit was -0.4653272727272727 kPa. Air pressure was 0.0776923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4791499999999999 m/s. Wind direction was -0.3054722222222222 decimal degrees. Relative humidity was 0.2795 percent. Net radiation was -0.19354 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4517285714285714 W/m^2. Outgoing longwave radiation was -0.2682142857142857 W/m^2. CO2 concentration was -0.31872125 μmol CO2/mol. Soil heat flux was -0.1644833333333333 W/m^2. Latent heat flux was -0.1660333333333333 W/m^2. Sensible heat flux was -0.18048 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.09", + "(B) 5.99", + "(C) -4.17", + "(D) 0.58", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF1_2003-07-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0049", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 54.2539, longitude -105.8775. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0021874999999999 degrees Celsius. Incoming shortwave radiation was -0.3438 W/m^2. Incoming longwave radiation was -0.36365 W/m^2. Vapor pressure deficit was -0.4948590909090909 kPa. Air pressure was 0.0807692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4831 m/s. Wind direction was 0.0797499999999999 decimal degrees. Relative humidity was 0.4155 percent. Net radiation was -0.0951266666666666 W/m^2. Incoming photosynthetic photon flux density was -0.303075 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43014375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4251761904761905 W/m^2. Outgoing longwave radiation was -0.3031666666666666 W/m^2. CO2 concentration was -0.30899175 μmol CO2/mol. Soil heat flux was -0.1701833333333333 W/m^2. Latent heat flux was -0.14685 W/m^2. Sensible heat flux was -0.1559966666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF2_2002-10-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0050", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 54.0916, longitude -106.0053. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0482625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.331425 W/m^2. Vapor pressure deficit was -0.4879727272727273 kPa. Air pressure was 0.0738461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.44935 m/s. Wind direction was 0.6623055555555554 decimal degrees. Relative humidity was 0.402 percent. Net radiation was -0.1701083333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4525952380952381 W/m^2. Outgoing longwave radiation was -0.2868809523809524 W/m^2. CO2 concentration was -0.3221725 μmol CO2/mol. Soil heat flux was -0.1709466666666666 W/m^2. Latent heat flux was -0.162996855 W/m^2. Sensible heat flux was -0.1698266666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.62", + "(B) 1.53", + "(C) 0.35", + "(D) -5.72", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-SF3_2002-08-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0051", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.6609, longitude -80.5595. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15496875 degrees Celsius. Incoming shortwave radiation was -0.0041965 W/m^2. Vapor pressure deficit was -0.3546636363636363 kPa. Air pressure was 0.11365 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4718299999999999 m/s. Wind direction was 0.2377777777777778 decimal degrees. Relative humidity was -0.0103 percent. Net radiation was 0.0322666666666666 W/m^2. Incoming photosynthetic photon flux density was 0.15841796875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.375859375 μmol Photon/m^2/s. CO2 concentration was -0.305056 μmol CO2/mol. Soil heat flux was -0.1429966666666666 W/m^2. Latent heat flux was -0.1435461666666666 W/m^2. Sensible heat flux was -0.1098946666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.53", + "(B) 1.35", + "(C) 3.89", + "(D) 0.63", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP1_2003-07-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0052", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.7744, longitude -80.4588. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.155890625 degrees Celsius. Incoming shortwave radiation was -0.4709069999999999 W/m^2. Vapor pressure deficit was -0.422 kPa. Air pressure was 0.1042923076923077 kPa. Wind speed was -0.482015 m/s. Wind direction was 0.2727777777777777 decimal degrees. Relative humidity was 0.22834 percent. Net radiation was -0.16754 W/m^2. Incoming photosynthetic photon flux density was -0.4025321875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.32552225 μmol CO2/mol. Soil heat flux was -0.1634346666666666 W/m^2. Latent heat flux was -0.1413195 W/m^2. Sensible heat flux was -0.1834203333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 12.32", + "(B) 4.39", + "(C) 2.81", + "(D) -0.1", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TP2_2002-07-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0053", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.6353, longitude -80.5577. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1024375 degrees Celsius. Incoming shortwave radiation was -0.44882425 W/m^2. Incoming longwave radiation was -0.31360425 W/m^2. Vapor pressure deficit was -0.4386227272727273 kPa. Air pressure was 0.125 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.429165 m/s. Wind direction was 0.2138888888888888 decimal degrees. Relative humidity was 0.1379 percent. Net radiation was -0.1438365 W/m^2. Incoming photosynthetic photon flux density was -0.37655015625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.433454375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4466340476190476 W/m^2. Outgoing longwave radiation was -0.2644840476190476 W/m^2. CO2 concentration was -0.2948044999999999 μmol CO2/mol. Soil heat flux was -0.1631036666666666 W/m^2. Latent heat flux was -0.1670665 W/m^2. Sensible heat flux was -0.1665498333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CA-TPD_2012-11-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0054", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 0.814444, longitude 24.502472. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.133065625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.293701 W/m^2. Vapor pressure deficit was -0.4999681818181818 kPa. Air pressure was 0.0806461538461538 kPa. Precipitation was recorded at -0.4853333333333333 mm. Wind speed was -0.47247 m/s. Wind direction was -0.752011388888889 decimal degrees. Relative humidity was 0.499859 percent. Incoming photosynthetic photon flux density was -0.4375990878124999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43759994375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521312085714286 W/m^2. Outgoing longwave radiation was -0.2490219047619047 W/m^2. CO2 concentration was -0.2905605 μmol CO2/mol. Latent heat flux was -0.1637228733333333 W/m^2. Sensible heat flux was -0.1361212981833333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 9.94", + "(B) 0.02", + "(C) -16.28", + "(D) -23.2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CD-Ygb_2020-10-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0055", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.2102, longitude 8.4104. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.062646875 degrees Celsius. Incoming shortwave radiation was -0.3812255 W/m^2. Incoming longwave radiation was -0.3487889999999999 W/m^2. Vapor pressure deficit was -0.4637 kPa. Air pressure was 0.0987192307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4943 m/s. Wind direction was 0.1443888888888889 decimal degrees. Relative humidity was 0.1758799999999999 percent. Net radiation was -0.1301816666666666 W/m^2. Incoming photosynthetic photon flux density was -0.29454171875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42676303125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4304446904761905 W/m^2. Outgoing longwave radiation was -0.2781223809523809 W/m^2. CO2 concentration was -0.274336 μmol CO2/mol. Soil heat flux was -0.1650930166666666 W/m^2. Latent heat flux was -0.1550592666666666 W/m^2. Sensible heat flux was -0.1528030333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.88", + "(B) -23.08", + "(C) -8.19", + "(D) 6.06", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Cha_2016-01-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0056", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.8153, longitude 9.8559. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.070625 degrees Celsius. Incoming shortwave radiation was -0.41483825 W/m^2. Incoming longwave radiation was -0.3598505 W/m^2. Vapor pressure deficit was -0.4429318181818181 kPa. Air pressure was -0.0078423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.467885 m/s. Wind direction was -0.822608611111111 decimal degrees. Relative humidity was 0.0318334999999999 percent. Net radiation was -0.1326475 W/m^2. Incoming photosynthetic photon flux density was -0.33009890625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4506345238095238 W/m^2. Outgoing longwave radiation was -0.2844066666666667 W/m^2. CO2 concentration was -0.3182825 μmol CO2/mol. Soil heat flux was -0.1647185 W/m^2. Latent heat flux was -0.1539260166666666 W/m^2. Sensible heat flux was -0.1619265666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.39", + "(B) -4.84", + "(C) -24.25", + "(D) 8.53", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Dav_2007-07-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0057", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.1158, longitude 8.5378. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.012875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3394985 W/m^2. Vapor pressure deficit was -0.4936227272727272 kPa. Precipitation was recorded at -0.4986666666666666 mm. Wind speed was -0.49186 m/s. Wind direction was 0.2809416666666667 decimal degrees. Relative humidity was 0.401225 percent. Net radiation was -0.1657416666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375368625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4528547619047619 W/m^2. Outgoing longwave radiation was -0.3021097619047618 W/m^2. CO2 concentration was -0.30079875 μmol CO2/mol. Soil heat flux was -0.1683925 W/m^2. Latent heat flux was -0.1730721766666667 W/m^2. Sensible heat flux was -0.1717156 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.35", + "(B) 0.39", + "(C) -7.51", + "(D) 9.01", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Fru_2006-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0058", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.4783, longitude 8.3644. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1405 degrees Celsius. Incoming shortwave radiation was -0.41687525 W/m^2. Incoming longwave radiation was -0.32191725 W/m^2. Vapor pressure deficit was -0.3722136363636363 kPa. Air pressure was 0.0630346153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.472715 m/s. Wind direction was 0.4873611111111112 decimal degrees. Relative humidity was -0.0164 percent. Incoming photosynthetic photon flux density was -0.327359375 μmol Photon/m^2/s. CO2 concentration was -0.322135 μmol CO2/mol. Latent heat flux was -0.0982176666666666 W/m^2. Sensible heat flux was -0.148151165 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.69", + "(B) -14.52", + "(C) -3.67", + "(D) 5.3", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Lae_2005-09-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0059", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.2858, longitude 7.7319. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06215625 degrees Celsius. Incoming shortwave radiation was -0.4987635 W/m^2. Incoming longwave radiation was -0.3723645 W/m^2. Vapor pressure deficit was -0.4392272727272727 kPa. Air pressure was 0.0961923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.477325 m/s. Wind direction was -0.6905555555555556 decimal degrees. Relative humidity was -0.0458499999999999 percent. Net radiation was -0.19741575 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4512592857142857 W/m^2. Outgoing longwave radiation was -0.28684 W/m^2. CO2 concentration was -0.3087175 μmol CO2/mol. Latent heat flux was -0.1603845666666666 W/m^2. Sensible heat flux was -0.1844762666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.8", + "(B) 1.79", + "(C) 2.1", + "(D) 10.11", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CH-Oe1_2003-04-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0060", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.5934, longitude 123.5092. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13390625 degrees Celsius. Incoming shortwave radiation was -0.49987025 W/m^2. Incoming longwave radiation was -0.2964425 W/m^2. Vapor pressure deficit was -0.4847272727272727 kPa. Air pressure was 0.1021230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4944599999999999 m/s. Wind direction was -0.1463888888888888 decimal degrees. Relative humidity was 0.4345 percent. Net radiation was -0.1718115833333333 W/m^2. Incoming photosynthetic photon flux density was -0.43750734375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4518069642857142 W/m^2. Outgoing longwave radiation was -0.2516171428571428 W/m^2. CO2 concentration was -0.2958625 μmol CO2/mol. Soil heat flux was -0.1670697783333333 W/m^2. Latent heat flux was -0.1667302366666666 W/m^2. Sensible heat flux was -0.1665932799999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.37", + "(B) -0.92", + "(C) 2.53", + "(D) -0.36", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Cng_2007-07-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0061", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 30.4978, longitude 91.0664. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.027740625 degrees Celsius. Incoming shortwave radiation was -0.1894499999999999 W/m^2. Incoming longwave radiation was -0.423525 W/m^2. Vapor pressure deficit was -0.4691136363636363 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4894449999999999 m/s. Relative humidity was -0.2720499999999999 percent. Net radiation was -0.0815666666666666 W/m^2. Latent heat flux was -0.1571651333333333 W/m^2. Sensible heat flux was -0.1356672 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Dan_2004-01-11_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0062", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 23.1733, longitude 112.5361. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.061875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.322625 W/m^2. Vapor pressure deficit was -0.4756090909090909 kPa. Air pressure was 0.1038461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48936 m/s. Relative humidity was 0.28015 percent. Net radiation was -0.1687436666666666 W/m^2. Latent heat flux was -0.1656382383333333 W/m^2. Sensible heat flux was -0.167304795 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.35", + "(B) 1.11", + "(C) -13.2", + "(D) 2.61", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Din_2003-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0063", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.0551, longitude 116.2809. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1508999999999999 degrees Celsius. Incoming shortwave radiation was -0.04575675 W/m^2. Vapor pressure deficit was -0.3333181818181818 kPa. Air pressure was 0.0131230769230768 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48914 m/s. Wind direction was -0.2510861111111112 decimal degrees. Relative humidity was -0.1083449999999999 percent. Net radiation was 0.0405173333333333 W/m^2. Incoming photosynthetic photon flux density was 0.1084656249999999 μmol Photon/m^2/s. CO2 concentration was -0.31597 μmol CO2/mol. Soil heat flux was -0.1218515 W/m^2. Latent heat flux was -0.0997441666666666 W/m^2. Sensible heat flux was -0.1374288333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.26", + "(B) -0.04", + "(C) 0.05", + "(D) -0.09", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Du3_2009-08-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0064", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.6086, longitude 101.3269. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0362875 degrees Celsius. Incoming shortwave radiation was -0.424325 W/m^2. Incoming longwave radiation was -0.4103 W/m^2. Vapor pressure deficit was -0.4685090909090909 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46594 m/s. Relative humidity was -0.3738 percent. Net radiation was -0.1602608333333333 W/m^2. Latent heat flux was -0.16129945 W/m^2. Sensible heat flux was -0.1248658666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Ha2_2003-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0065", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.37, longitude 101.18. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0254437499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4896318181818181 kPa. Air pressure was -0.1153692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4817349999999999 m/s. Wind direction was -0.1081666666666666 decimal degrees. Relative humidity was 0.360685 percent. Net radiation was -0.1722296666666666 W/m^2. Incoming photosynthetic photon flux density was -0.43730953125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4514380952380952 W/m^2. CO2 concentration was -0.33544725 μmol CO2/mol. Soil heat flux was -0.1717388333333333 W/m^2. Latent heat flux was -0.1631181666666666 W/m^2. Sensible heat flux was -0.1681196666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.71", + "(B) 5.03", + "(C) -0.09", + "(D) 2.97", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-HaM_2002-09-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0066", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.7902, longitude 111.8971. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.063009375 degrees Celsius. Incoming shortwave radiation was -0.499633 W/m^2. Incoming longwave radiation was -0.3889465 W/m^2. Vapor pressure deficit was -0.4892227272727273 kPa. Air pressure was 0.0025769230769231 kPa. Precipitation was recorded at -0.4956666666666666 mm. Wind speed was -0.474895 m/s. Wind direction was -0.9243194444444444 decimal degrees. Relative humidity was 0.4040125 percent. Net radiation was -0.1717039666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4370588203125 μmol Photon/m^2/s. Outgoing longwave radiation was -0.4512517619047619 W/m^2. Latent heat flux was -0.1395637833333333 W/m^2. Sensible heat flux was -0.1678479998333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.36", + "(B) -0.68", + "(C) -0.43", + "(D) -0.85", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CN-Sw2_2011-09-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0067", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.5021, longitude 18.5369. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.048725 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3282365 W/m^2. Vapor pressure deficit was -0.4991272727272727 kPa. Air pressure was 0.0487884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47312 m/s. Wind direction was 0.1074138888888888 decimal degrees. Relative humidity was 0.4909385 percent. Net radiation was -0.168378325 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2863514285714285 W/m^2. CO2 concentration was -0.30315575 μmol CO2/mol. Soil heat flux was -0.1669275933333333 W/m^2. Latent heat flux was -0.16545643 W/m^2. Sensible heat flux was -0.1705721016666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.53", + "(B) 1.1", + "(C) -0.3", + "(D) 2.6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK1_2015-10-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0068", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.4944, longitude 18.5429. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.073584375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3422247499999999 W/m^2. Vapor pressure deficit was -0.4284636363636364 kPa. Air pressure was 0.0452923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4830899999999999 m/s. Wind direction was -0.6344897222222222 decimal degrees. Relative humidity was -0.0693155 percent. Net radiation was -0.1756079666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2893454761904762 W/m^2. CO2 concentration was -0.299018 μmol CO2/mol. Latent heat flux was -0.1624232183333333 W/m^2. Sensible heat flux was -0.1782419333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.6", + "(B) -7.23", + "(C) -6.24", + "(D) 4.49", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-BK2_2009-04-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0069", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.573257, longitude 15.078773. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.021471875 degrees Celsius. Incoming shortwave radiation was -0.353751 W/m^2. Incoming longwave radiation was -0.35611175 W/m^2. Vapor pressure deficit was -0.4682227272727273 kPa. Air pressure was 0.0733230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4458749999999999 m/s. Wind direction was 0.4138916666666666 decimal degrees. Relative humidity was 0.0529325 percent. Net radiation was -0.1025731666666666 W/m^2. Incoming photosynthetic photon flux density was -0.26043015625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4316556904761904 W/m^2. Outgoing longwave radiation was -0.2883469047619048 W/m^2. CO2 concentration was -0.299988 μmol CO2/mol. Soil heat flux was -0.16535302 W/m^2. Latent heat flux was -0.1450803 W/m^2. Sensible heat flux was -0.1423828833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.04", + "(B) -15.54", + "(C) 0.58", + "(D) 0.19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-KrP_2016-04-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0070", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 48.6815483, longitude 16.9463317. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.03198125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.35379475 W/m^2. Vapor pressure deficit was -0.4890590909090909 kPa. Air pressure was 0.1283384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.479935 m/s. Wind direction was -0.2013138888888887 decimal degrees. Relative humidity was 0.211825 percent. Net radiation was -0.1671051831666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3125114285714285 W/m^2. CO2 concentration was -0.294495 μmol CO2/mol. Latent heat flux was -0.16351233 W/m^2. Sensible heat flux was -0.0647163333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.79", + "(B) 1.66", + "(C) 3.21", + "(D) -17.72", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Lnz_2015-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0071", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.035975, longitude 17.9699. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.051353125 degrees Celsius. Incoming shortwave radiation was -0.4009515 W/m^2. Incoming longwave radiation was -0.3541105 W/m^2. Vapor pressure deficit was -0.4646 kPa. Air pressure was 0.0737961538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4393849999999999 m/s. Wind direction was -0.12765 decimal degrees. Relative humidity was 0.142408 percent. Net radiation was -0.1288605 W/m^2. Incoming photosynthetic photon flux density was -0.312339375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42452275 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4380780714285714 W/m^2. Outgoing longwave radiation was -0.2874183333333334 W/m^2. CO2 concentration was -0.3036622499999999 μmol CO2/mol. Latent heat flux was -0.1677217366666666 W/m^2. Sensible heat flux was -0.1595433166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -16.64", + "(B) -0.42", + "(C) 1.68", + "(D) 0.82", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-Stn_2013-03-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0072", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.0247, longitude 14.7704. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0621874999999999 degrees Celsius. Incoming shortwave radiation was -0.0784099999999999 W/m^2. Incoming longwave radiation was -0.3530749999999999 W/m^2. Vapor pressure deficit was -0.4426272727272727 kPa. Air pressure was 0.0946153846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.482665 m/s. Wind direction was 0.8782055555555556 decimal degrees. Relative humidity was -0.0154999999999999 percent. Net radiation was 0.0394599999999999 W/m^2. Incoming photosynthetic photon flux density was 0.0531734374999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3951874999999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3983095238095238 W/m^2. Outgoing longwave radiation was -0.2594761904761904 W/m^2. CO2 concentration was -0.30516375 μmol CO2/mol. Soil heat flux was -0.1618833333333333 W/m^2. Latent heat flux was -0.1331792 W/m^2. Sensible heat flux was -0.0587398333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.84", + "(B) 0.35", + "(C) 0.28", + "(D) 4.28", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/CZ-wet_2011-05-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0073", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 53.8662, longitude 13.6834. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.068053125 degrees Celsius. Incoming shortwave radiation was -0.4107735 W/m^2. Incoming longwave radiation was -0.35912225 W/m^2. Vapor pressure deficit was -0.4711954545454545 kPa. Wind speed was -0.4699799999999999 m/s. Wind direction was 0.4341388888888888 decimal degrees. Relative humidity was 0.2568999999999999 percent. Net radiation was -0.1453394166666666 W/m^2. Incoming photosynthetic photon flux density was -0.3385128125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42684465625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4351811428571429 W/m^2. Outgoing longwave radiation was -0.2809014285714286 W/m^2. CO2 concentration was -0.3100115 μmol CO2/mol. Latent heat flux was -0.1605897 W/m^2. Sensible heat flux was -0.1582273666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.28", + "(B) 0.14", + "(C) -20.46", + "(D) 0.65", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Akm_2009-11-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0074", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 51.0997, longitude 10.9146. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07203125 degrees Celsius. Incoming shortwave radiation was -0.1500699999999999 W/m^2. Incoming longwave radiation was -0.37589 W/m^2. Vapor pressure deficit was -0.4293181818181818 kPa. Air pressure was 0.1118499999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4681499999999999 m/s. Wind direction was -0.5138055555555555 decimal degrees. Relative humidity was -0.07155 percent. Net radiation was -0.04199 W/m^2. Incoming photosynthetic photon flux density was -0.03319375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3941875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3864023809523809 W/m^2. Outgoing longwave radiation was -0.245 W/m^2. CO2 concentration was -0.3084027499999999 μmol CO2/mol. Soil heat flux was -0.140855 W/m^2. Latent heat flux was -0.1378163833333333 W/m^2. Sensible heat flux was -0.0981536666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.58", + "(B) 0.89", + "(C) 0.81", + "(D) -5.52", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Geb_2004-03-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0075", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.95, longitude 13.5126. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.048940625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.397675 W/m^2. Vapor pressure deficit was -0.4969090909090908 kPa. Air pressure was 0.0985807692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49615 m/s. Wind direction was -0.1427805555555555 decimal degrees. Relative humidity was 0.3996665 percent. Net radiation was -0.1857277833333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3276985714285714 W/m^2. CO2 concentration was -0.2903175 μmol CO2/mol. Soil heat flux was -0.16874 W/m^2. Latent heat flux was -0.1664232666666666 W/m^2. Sensible heat flux was -0.1672568133333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -10.7", + "(B) 0.46", + "(C) 5.8", + "(D) 0.14", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Gri_2009-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0076", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 51.0792, longitude 10.4522. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0746874999999999 degrees Celsius. Incoming shortwave radiation was -0.303825 W/m^2. Incoming longwave radiation was -0.3396074999999999 W/m^2. Vapor pressure deficit was -0.4311863636363636 kPa. Air pressure was 0.0789230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46835 m/s. Wind direction was 0.2349444444444444 decimal degrees. Relative humidity was -0.0411999999999999 percent. Net radiation was -0.0683021666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1859640625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4278437499999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4355880952380952 W/m^2. Outgoing longwave radiation was -0.2701071428571429 W/m^2. CO2 concentration was -0.309575 μmol CO2/mol. Soil heat flux was -0.1626433333333333 W/m^2. Latent heat flux was -0.14425 W/m^2. Sensible heat flux was -0.100935 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.4", + "(B) -18.4", + "(C) -16.57", + "(D) -1.68", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hai_2004-04-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0077", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.933, longitude 7.5981. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0105937499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3475749999999999 W/m^2. Vapor pressure deficit was -0.5 kPa. Air pressure was 0.1222461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49455 m/s. Wind direction was 0.1005555555555555 decimal degrees. Relative humidity was 0.5 percent. Net radiation was -0.1684 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3047380952380952 W/m^2. CO2 concentration was -0.26035 μmol CO2/mol. Latent heat flux was -0.1666054726666666 W/m^2. Sensible heat flux was -0.1680333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -12.2", + "(B) -3.19", + "(C) 5.12", + "(D) 1.69", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Har_2020-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0078", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 52.08656, longitude 11.22235. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0171875 degrees Celsius. Incoming shortwave radiation was -0.499355 W/m^2. Incoming longwave radiation was -0.3624675 W/m^2. Vapor pressure deficit was -0.4858818181818182 kPa. Air pressure was 0.0939999999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4539 m/s. Wind direction was 0.2789722222222222 decimal degrees. Relative humidity was 0.29145 percent. Net radiation was -0.1850583333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375187499999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4528190476190476 W/m^2. Outgoing longwave radiation was -0.2964238095238095 W/m^2. CO2 concentration was -0.2935149999999999 μmol CO2/mol. Soil heat flux was -0.168185 W/m^2. Latent heat flux was -0.1657016666666666 W/m^2. Sensible heat flux was -0.1834916666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.42", + "(B) 2.52", + "(C) 8.06", + "(D) 0.62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-HoH_2019-01-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0079", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.96381, longitude 13.48978. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.14246875 degrees Celsius. Incoming shortwave radiation was -0.2637224999999999 W/m^2. Incoming longwave radiation was -0.3120475 W/m^2. Vapor pressure deficit was -0.3702818181818182 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4868 m/s. Wind direction was -0.075 decimal degrees. Relative humidity was -0.01405 percent. Net radiation was -0.0592216666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1402640625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.417203125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4168357142857143 W/m^2. Outgoing longwave radiation was -0.2373904761904761 W/m^2. CO2 concentration was -0.319658 μmol CO2/mol. Soil heat flux was -0.1535083333333333 W/m^2. Latent heat flux was -0.0385666666666666 W/m^2. Sensible heat flux was -0.1418916666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.45", + "(B) 7.2", + "(C) -6.99", + "(D) -15.9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Hzd_2010-08-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0080", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.8931, longitude 13.5224. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.078646875 degrees Celsius. Incoming shortwave radiation was -0.4699785 W/m^2. Incoming longwave radiation was -0.32929175 W/m^2. Vapor pressure deficit was -0.4700136363636364 kPa. Air pressure was 0.0819692307692308 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46392 m/s. Wind direction was -0.0529555555555554 decimal degrees. Relative humidity was 0.2738735 percent. Net radiation was -0.1632360633333333 W/m^2. Incoming photosynthetic photon flux density was -0.399684375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4359659374999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4462849928571428 W/m^2. Outgoing longwave radiation was -0.2722061904761905 W/m^2. CO2 concentration was -0.2961605 μmol CO2/mol. Soil heat flux was -0.1660728328333333 W/m^2. Latent heat flux was -0.1657664166666666 W/m^2. Sensible heat flux was -0.1660283333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.06", + "(B) -0.74", + "(C) 0.48", + "(D) 1.06", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Kli_2009-05-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0081", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.0996, longitude 13.3047. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0141249999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.37961 W/m^2. Vapor pressure deficit was -0.4948909090909091 kPa. Air pressure was 0.0207692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4866499999999999 m/s. Wind direction was -0.9086111111111111 decimal degrees. Relative humidity was 0.4218 percent. Net radiation was -0.1939533333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4374625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3006357142857143 W/m^2. CO2 concentration was -0.307858 μmol CO2/mol. Soil heat flux was -0.169613945 W/m^2. Latent heat flux was -0.1563844666666666 W/m^2. Sensible heat flux was -0.1667147488333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.09", + "(B) 4.47", + "(C) 1.07", + "(D) 2.21", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lkb_2009-05-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0082", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 51.3282, longitude 10.3678. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.03821875 degrees Celsius. Incoming shortwave radiation was -0.3191675 W/m^2. Incoming longwave radiation was -0.3508025 W/m^2. Vapor pressure deficit was -0.4817318181818181 kPa. Air pressure was 0.0812846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4817 m/s. Wind direction was 0.0245277777777777 decimal degrees. Relative humidity was 0.28765 percent. Net radiation was -0.07701 W/m^2. Incoming photosynthetic photon flux density was -0.200009375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4336523809523809 W/m^2. Outgoing longwave radiation was -0.2848761904761905 W/m^2. CO2 concentration was -0.3085925 μmol CO2/mol. Soil heat flux was -0.16104678 W/m^2. Latent heat flux was -0.14769 W/m^2. Sensible heat flux was -0.1183766666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Lnf_2002-04-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0083", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.809181, longitude 11.456168. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06870625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33595625 W/m^2. Vapor pressure deficit was -0.4623272727272727 kPa. Air pressure was 0.0767961538461539 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.486505 m/s. Wind direction was -0.7233977777777778 decimal degrees. Relative humidity was 0.1844679999999999 percent. Net radiation was -0.1785508666666666 W/m^2. Incoming photosynthetic photon flux density was -0.43749628125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519811602380952 W/m^2. Outgoing longwave radiation was -0.2803680952380952 W/m^2. CO2 concentration was -0.2965195 μmol CO2/mol. Soil heat flux was -0.1676681866666666 W/m^2. Latent heat flux was -0.16336216 W/m^2. Sensible heat flux was -0.1736822 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.63", + "(B) 0.12", + "(C) 6.74", + "(D) -5.21", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Msr_2020-06-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0084", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.7867, longitude 13.7213. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11471875 degrees Celsius. Incoming shortwave radiation was -0.1019365 W/m^2. Incoming longwave radiation was -0.334454 W/m^2. Vapor pressure deficit was -0.404990909090909 kPa. Air pressure was 0.0696230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47167 m/s. Wind direction was 0.6902194444444446 decimal degrees. Relative humidity was 0.0657999999999999 percent. Net radiation was 0.0537805 W/m^2. Incoming photosynthetic photon flux density was 0.0572937499999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4249440625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4285714285714285 W/m^2. Outgoing longwave radiation was -0.2543440476190476 W/m^2. CO2 concentration was -0.314465 μmol CO2/mol. Soil heat flux was -0.1619106166666666 W/m^2. Latent heat flux was -0.1034383333333333 W/m^2. Sensible heat flux was -0.0708866666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.58", + "(B) 0.16", + "(C) 2.71", + "(D) -14.31", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Obe_2009-05-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0085", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.6219, longitude 6.3041. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.086925 degrees Celsius. Incoming shortwave radiation was -0.3638417499999999 W/m^2. Incoming longwave radiation was -0.35595875 W/m^2. Vapor pressure deficit was -0.4286318181818182 kPa. Air pressure was 0.0950653846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46451 m/s. Wind direction was -0.9570366666666668 decimal degrees. Relative humidity was 0.0062445 percent. Net radiation was -0.1286790166666666 W/m^2. Incoming photosynthetic photon flux density was -0.26916328125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4231776904761904 W/m^2. Outgoing longwave radiation was -0.2689957142857143 W/m^2. CO2 concentration was -0.3000175 μmol CO2/mol. Soil heat flux was -0.1527409 W/m^2. Latent heat flux was -0.1385204833333333 W/m^2. Sensible heat flux was -0.1660326666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.84", + "(B) -6.53", + "(C) -26.24", + "(D) 3.34", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuR_2012-03-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0086", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.8659, longitude 6.4471. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.02296875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3492975 W/m^2. Vapor pressure deficit was -0.4997181818181818 kPa. Air pressure was 0.0945384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49345 m/s. Wind direction was -0.28 decimal degrees. Relative humidity was 0.49605 percent. Net radiation was -0.1781283333333333 W/m^2. Incoming photosynthetic photon flux density was -0.437671875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43775 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4537904761904762 W/m^2. Outgoing longwave radiation was -0.2949404761904762 W/m^2. CO2 concentration was -0.24034 μmol CO2/mol. Soil heat flux was -0.17847615 W/m^2. Latent heat flux was -0.1661360766666666 W/m^2. Sensible heat flux was -0.16662487825 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.19", + "(B) 3.34", + "(C) -4.99", + "(D) 2.06", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuS_2019-04-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0087", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.5049268531233, longitude 6.33096247542595. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0732625 degrees Celsius. Incoming shortwave radiation was -0.396675 W/m^2. Incoming longwave radiation was -0.3126395 W/m^2. Vapor pressure deficit was -0.4919590909090909 kPa. Air pressure was 0.0630807692307692 kPa. Precipitation was recorded at -0.4983333333333333 mm. Wind speed was -0.492575 m/s. Wind direction was -0.1655999999999999 decimal degrees. Relative humidity was 0.4356669999999999 percent. Incoming photosynthetic photon flux density was -0.29222390625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4505937285714286 W/m^2. Outgoing longwave radiation was -0.2739169047619048 W/m^2. CO2 concentration was -0.275244 μmol CO2/mol. Soil heat flux was -0.16536839 W/m^2. Latent heat flux was -0.1367976666666666 W/m^2. Sensible heat flux was -0.1545226333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -5.2", + "(B) 0.25", + "(C) 1.13", + "(D) -2.83", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-RuW_2012-06-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0088", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.8706, longitude 6.4497. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07609375 degrees Celsius. Incoming shortwave radiation was -0.4828874999999999 W/m^2. Vapor pressure deficit was -0.4813545454545454 kPa. Air pressure was 0.1227346153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.485575 m/s. Wind direction was 0.5032111111111109 decimal degrees. Relative humidity was 0.3555000000000001 percent. Net radiation was -0.158555 W/m^2. CO2 concentration was -0.2983547499999999 μmol CO2/mol. Soil heat flux was -0.1657305 W/m^2. Latent heat flux was -0.1629929916666666 W/m^2. Sensible heat flux was -0.1682308133333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.18", + "(B) 1.56", + "(C) 3.19", + "(D) 0.2", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Seh_2007-11-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0089", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.8064, longitude 11.3275. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.01559375 degrees Celsius. Incoming shortwave radiation was -0.43671 W/m^2. Incoming longwave radiation was -0.3605 W/m^2. Vapor pressure deficit was -0.4893818181818182 kPa. Air pressure was 0.0628384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.457555 m/s. Wind direction was 0.3765249999999999 decimal degrees. Relative humidity was 0.3404079999999999 percent. Net radiation was -0.1407166666666666 W/m^2. Outgoing shortwave radiation was -0.4505730166666666 W/m^2. Outgoing longwave radiation was -0.2981261904761905 W/m^2. CO2 concentration was -0.324409 μmol CO2/mol. Soil heat flux was -0.1675988883333333 W/m^2. Latent heat flux was -0.1610269 W/m^2. Sensible heat flux was -0.1617151 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.8", + "(B) -1.76", + "(C) 4.02", + "(D) -1.06", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-SfN_2013-03-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0090", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 51.8922, longitude 14.0337. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1695625 degrees Celsius. Incoming shortwave radiation was -0.09611 W/m^2. Incoming longwave radiation was -0.299245 W/m^2. Vapor pressure deficit was -0.3738 kPa. Air pressure was 0.1308076923076922 kPa. Wind speed was -0.47115 m/s. Wind direction was -0.5433611111111112 decimal degrees. Relative humidity was 0.11465 percent. Net radiation was 0.0479833333333333 W/m^2. Incoming photosynthetic photon flux density was 0.0222703125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.425278125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4030404761904761 W/m^2. Outgoing longwave radiation was -0.2325142857142857 W/m^2. CO2 concentration was -0.308625 μmol CO2/mol. Latent heat flux was -0.0544933333333333 W/m^2. Sensible heat flux was -0.1122266666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.34", + "(B) 3.23", + "(C) -6.76", + "(D) -21.02", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Spw_2014-07-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0091", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 50.9626, longitude 13.5651. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.02089375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3907855 W/m^2. Vapor pressure deficit was -0.4962545454545454 kPa. Air pressure was 0.0987730769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.462885 m/s. Wind direction was 0.4269444444444445 decimal degrees. Relative humidity was 0.4136584999999999 percent. Net radiation was -0.1924522 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3115307142857143 W/m^2. CO2 concentration was -0.293435 μmol CO2/mol. Soil heat flux was -0.1706793333333333 W/m^2. Latent heat flux was -0.1669383333333333 W/m^2. Sensible heat flux was -0.1726816666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.27", + "(B) 0.15", + "(C) -10.1", + "(D) 0.72", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Tha_2009-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0092", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 53.8759, longitude 12.889. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.101715625 degrees Celsius. Incoming shortwave radiation was -0.491153 W/m^2. Incoming longwave radiation was -0.31669575 W/m^2. Vapor pressure deficit was -0.4635681818181818 kPa. Air pressure was 0.1281307692307692 kPa. Wind speed was -0.49199 m/s. Wind direction was 0.5565305555555555 decimal degrees. Relative humidity was 0.283476 percent. Net radiation was -0.1749116833333333 W/m^2. Incoming photosynthetic photon flux density was -0.4277631890625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43673785390625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4506731285714286 W/m^2. Outgoing longwave radiation was -0.2593092857142857 W/m^2. CO2 concentration was -0.3064115 μmol CO2/mol. Soil heat flux was -0.1725245666666666 W/m^2. Latent heat flux was -0.1593287 W/m^2. Sensible heat flux was -0.165772855 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.52", + "(B) -5.82", + "(C) 2.12", + "(D) 6.61", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DE-Zrk_2013-06-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0093", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.6905, longitude 12.1918. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08846875 degrees Celsius. Incoming shortwave radiation was -0.26002 W/m^2. Vapor pressure deficit was -0.4183227272727273 kPa. Air pressure was 0.1323076923076923 kPa. Wind speed was -0.466165 m/s. Wind direction was 0.7502777777777775 decimal degrees. Relative humidity was -0.0561 percent. Net radiation was -0.093314 W/m^2. Incoming photosynthetic photon flux density was -0.1490625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4086234375 μmol Photon/m^2/s. CO2 concentration was -0.3091332499999999 μmol CO2/mol. Soil heat flux was -0.1552733333333333 W/m^2. Latent heat flux was -0.1385077833333333 W/m^2. Sensible heat flux was -0.1460410999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Eng_2005-05-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0094", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.4842, longitude 9.5872. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.01405 degrees Celsius. Incoming shortwave radiation was -0.4884307499999999 W/m^2. Vapor pressure deficit was -0.4829090909090909 kPa. Air pressure was 0.1247423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.476565 m/s. Wind direction was 0.6714027777777779 decimal degrees. Relative humidity was 0.2387314999999999 percent. Net radiation was -0.1812134333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4321203125 μmol Photon/m^2/s. CO2 concentration was -0.31034425 μmol CO2/mol. Soil heat flux was -0.1690137733333333 W/m^2. Latent heat flux was -0.166548635 W/m^2. Sensible heat flux was -0.1708242833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.21", + "(B) -17.49", + "(C) 0.55", + "(D) 0.44", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Fou_2005-02-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0095", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.0737, longitude 9.3341. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.067234375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4946136363636363 kPa. Air pressure was 0.1024038461538461 kPa. Precipitation was recorded at -0.4976666666666667 mm. Wind speed was -0.4318099999999999 m/s. Wind direction was 0.2669583333333334 decimal degrees. Relative humidity was 0.469809 percent. CO2 concentration was -0.271352 μmol CO2/mol. Latent heat flux was -0.1549551833333333 W/m^2. Sensible heat flux was -0.1351245833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 8.17", + "(B) -0.24", + "(C) -15.42", + "(D) -7.4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Gds_2020-11-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0096", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.91273, longitude 8.40481. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09560625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4946363636363636 kPa. Air pressure was 0.1261076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48302 m/s. Wind direction was 0.8075749999999999 decimal degrees. Relative humidity was 0.466045 percent. CO2 concentration was -0.2984054999999999 μmol CO2/mol. Latent heat flux was -0.162205 W/m^2. Sensible heat flux was -0.1683048383333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.76", + "(B) 0.76", + "(C) -18.56", + "(D) 8.79", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Skj_2020-08-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0097", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.4859, longitude 11.6446. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13828125 degrees Celsius. Incoming shortwave radiation was -0.245375 W/m^2. Incoming longwave radiation was -0.30915 W/m^2. Vapor pressure deficit was -0.4298636363636363 kPa. Air pressure was 0.1199999999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4537 m/s. Wind direction was -0.7694444444444445 decimal degrees. Relative humidity was 0.21055 percent. Net radiation was -0.0413333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.131171875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4144047619047619 W/m^2. Outgoing longwave radiation was -0.2451428571428571 W/m^2. CO2 concentration was -0.3038524999999999 μmol CO2/mol. Soil heat flux was -0.1621083333333333 W/m^2. Latent heat flux was -0.0663166666666666 W/m^2. Sensible heat flux was -0.1405166666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.89", + "(B) 11.26", + "(C) -24.76", + "(D) 3.84", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Sor_2007-08-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0098", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.0374765, longitude 9.16070962. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07478125 degrees Celsius. Incoming shortwave radiation was -0.4989425 W/m^2. Incoming longwave radiation was -0.314055 W/m^2. Vapor pressure deficit was -0.4957318181818182 kPa. Air pressure was 0.1205 kPa. Precipitation was recorded at -0.4996666666666667 mm. Wind speed was -0.4503999999999999 m/s. Wind direction was 0.2966666666666667 decimal degrees. Relative humidity was 0.46645 percent. Net radiation was -0.1668016666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437496875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4546619047619047 W/m^2. Outgoing longwave radiation was -0.2753261904761904 W/m^2. CO2 concentration was -0.2931925 μmol CO2/mol. Soil heat flux was -0.164025 W/m^2. Latent heat flux was -0.1672583333333333 W/m^2. Sensible heat flux was -0.1732016666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -9.72", + "(B) 2.5", + "(C) -1.67", + "(D) 0.9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/DK-Vng_2020-11-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0099", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.701839, longitude -6.785881. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10546875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.30661825 W/m^2. Vapor pressure deficit was -0.4761681818181818 kPa. Air pressure was 0.1050153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4731 m/s. Wind direction was 0.1826472222222221 decimal degrees. Relative humidity was 0.36367 percent. Net radiation was -0.1711043333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2618666666666667 W/m^2. CO2 concentration was -0.2972145 μmol CO2/mol. Soil heat flux was -0.17050265 W/m^2. Latent heat flux was -0.1642025 W/m^2. Sensible heat flux was -0.1688286666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.04", + "(B) 0.61", + "(C) 3.31", + "(D) -7.26", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Abr_2015-11-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0100", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.940046, longitude -2.033208. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.141034375 degrees Celsius. Incoming shortwave radiation was -0.28063725 W/m^2. Vapor pressure deficit was -0.4143272727272727 kPa. Air pressure was 0.1095384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4400099999999999 m/s. Wind direction was -0.5620777777777778 decimal degrees. Relative humidity was 0.1557025 percent. Net radiation was -0.085918 W/m^2. Incoming photosynthetic photon flux density was -0.17384296875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.413132109375 μmol Photon/m^2/s. CO2 concentration was -0.32109075 μmol CO2/mol. Soil heat flux was -0.1444459666666666 W/m^2. Latent heat flux was -0.163829725 W/m^2. Sensible heat flux was -0.1215418333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.62", + "(B) -4.0", + "(C) 0.9", + "(D) -5.44", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Agu_2006-10-09_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0101", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.8336, longitude -2.2523. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.162821875 degrees Celsius. Incoming shortwave radiation was 0.0376612499999999 W/m^2. Vapor pressure deficit was -0.3636681818181818 kPa. Air pressure was 0.1221730769230768 kPa. Precipitation was recorded at -0.4984666666666666 mm. Wind speed was -0.45641 m/s. Wind direction was 0.2644638888888889 decimal degrees. Relative humidity was 0.0557325 percent. Net radiation was -0.0075816666666666 W/m^2. Incoming photosynthetic photon flux density was 0.207703125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.34320625 μmol Photon/m^2/s. CO2 concentration was -0.3080075 μmol CO2/mol. Soil heat flux was -0.1309375 W/m^2. Latent heat flux was -0.1573136166666666 W/m^2. Sensible heat flux was -0.0491204999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.49", + "(B) 0.98", + "(C) 4.39", + "(D) 0.63", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Amo_2007-07-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0102", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.914998, longitude -3.227659. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.172896875 degrees Celsius. Incoming shortwave radiation was -0.3219975 W/m^2. Incoming longwave radiation was -0.323321 W/m^2. Vapor pressure deficit was -0.2063272727272727 kPa. Air pressure was 0.0872961538461538 kPa. Wind speed was -0.490275 m/s. Wind direction was 0.3903555555555556 decimal degrees. Relative humidity was -0.3713114999999999 percent. Net radiation was -0.1010601666666666 W/m^2. Incoming photosynthetic photon flux density was -0.23355546875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.419347609375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4277229047619048 W/m^2. Outgoing longwave radiation was -0.2329685714285714 W/m^2. CO2 concentration was -0.30560725 μmol CO2/mol. Soil heat flux was -0.14816075 W/m^2. Latent heat flux was -0.1545693666666666 W/m^2. Sensible heat flux was -0.1495738833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.35", + "(B) -4.59", + "(C) -0.88", + "(D) -2.38", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Cnd_2014-10-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0103", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.0979, longitude -2.9658. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0105624999999999 degrees Celsius. Incoming shortwave radiation was -0.49816325 W/m^2. Vapor pressure deficit was -0.4611272727272728 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48715 m/s. Wind direction was 0.1158333333333333 decimal degrees. Relative humidity was -0.11685 percent. Net radiation was -0.1804566666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4352921875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43535625 μmol Photon/m^2/s. CO2 concentration was -0.30646 μmol CO2/mol. Soil heat flux was -0.167515 W/m^2. Latent heat flux was -0.1609670833333333 W/m^2. Sensible heat flux was -0.1818431966666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.23", + "(B) -1.6", + "(C) 0.11", + "(D) 0.62", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LgS_2007-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0104", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.9266, longitude -2.7521. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.034228125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4488999999999999 kPa. Air pressure was -0.0002230769230768 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4943099999999999 m/s. Wind direction was -0.2656641666666666 decimal degrees. Relative humidity was -0.1217499999999999 percent. Net radiation was -0.166666515 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.31560775 μmol CO2/mol. Soil heat flux was -0.1687830583333333 W/m^2. Latent heat flux was -0.1664797683333333 W/m^2. Sensible heat flux was -0.1683992233333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.04", + "(B) 0.18", + "(C) 1.78", + "(D) 0.17", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LJu_2005-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0105", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.94269, longitude -5.778683. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07346875 degrees Celsius. Incoming shortwave radiation was -0.4433924999999999 W/m^2. Incoming longwave radiation was -0.320229 W/m^2. Vapor pressure deficit was -0.48255 kPa. Air pressure was 0.1013230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4728 m/s. Wind direction was 0.3625666666666666 decimal degrees. Relative humidity was 0.3609999999999999 percent. Net radiation was -0.1389211666666666 W/m^2. Incoming photosynthetic photon flux density was -0.35465515625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4333265625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4462119047619047 W/m^2. Outgoing longwave radiation was -0.2730642857142857 W/m^2. CO2 concentration was -0.3038245 μmol CO2/mol. Soil heat flux was -0.165593415 W/m^2. Latent heat flux was -0.1626906666666666 W/m^2. Sensible heat flux was -0.160951 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.4", + "(B) -13.92", + "(C) 1.86", + "(D) 5.27", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM1_2014-11-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0106", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.934592, longitude -5.775881. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0721875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3296074999999999 W/m^2. Vapor pressure deficit was -0.4806272727272727 kPa. Air pressure was 0.1006 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48567 m/s. Wind direction was 0.4841722222222223 decimal degrees. Relative humidity was 0.343665 percent. Net radiation was -0.1767516666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2756966666666666 W/m^2. CO2 concentration was -0.3009597499999999 μmol CO2/mol. Soil heat flux was -0.1713660833333333 W/m^2. Latent heat flux was -0.1663387588333333 W/m^2. Sensible heat flux was -0.1686566666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.84", + "(B) 2.68", + "(C) 0.99", + "(D) -7.32", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-LM2_2014-11-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0107", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.9695, longitude -3.4758. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11375 degrees Celsius. Incoming shortwave radiation was 0.0143224999999999 W/m^2. Vapor pressure deficit was -0.3660363636363636 kPa. Air pressure was -0.0556538461538461 kPa. Wind speed was -0.4284 m/s. Wind direction was 0.3752777777777778 decimal degrees. Relative humidity was -0.20485 percent. Incoming photosynthetic photon flux density was 0.180678125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.367884375 μmol Photon/m^2/s. CO2 concentration was -0.321405 μmol CO2/mol. Soil heat flux was -0.1346898666666666 W/m^2. Latent heat flux was -0.1505177166666666 W/m^2. Sensible heat flux was -0.040275 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.03", + "(B) 0.28", + "(C) -0.46", + "(D) 0.2", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/ES-Ln2_2009-06-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0108", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 61.8474, longitude 24.2948. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.01240625 degrees Celsius. Incoming shortwave radiation was -0.4590675 W/m^2. Incoming longwave radiation was -0.3533435 W/m^2. Vapor pressure deficit was -0.4814045454545455 kPa. Air pressure was 0.107626923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4539999999999999 m/s. Wind direction was -0.8353611111111111 decimal degrees. Relative humidity was 0.20995 percent. Net radiation was -0.1498783333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3843625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43614375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4480071428571429 W/m^2. Outgoing longwave radiation was -0.2948409523809523 W/m^2. CO2 concentration was -0.3077749999999999 μmol CO2/mol. Soil heat flux was -0.1685271666666666 W/m^2. Latent heat flux was -0.1582535 W/m^2. Sensible heat flux was -0.1533308333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.62", + "(B) 0.72", + "(C) 2.48", + "(D) 1.6", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Hyy_2009-10-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0109", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 60.6418, longitude 23.9595. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0625 degrees Celsius. Incoming shortwave radiation was -0.4972725 W/m^2. Incoming longwave radiation was -0.31483175 W/m^2. Vapor pressure deficit was -0.4916772727272727 kPa. Air pressure was 0.0998192307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.472845 m/s. Wind direction was 0.8666666666666667 decimal degrees. Relative humidity was 0.4255 percent. Incoming photosynthetic photon flux density was -0.4305 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437046875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2740211904761904 W/m^2. CO2 concentration was -0.29150975 μmol CO2/mol. Soil heat flux was -0.1663938888333333 W/m^2. Latent heat flux was -0.163211 W/m^2. Sensible heat flux was -0.1894566666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.85", + "(B) 1.62", + "(C) 7.37", + "(D) 0.91", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Let_2019-07-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0110", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 60.295242, longitude 22.391607. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10775 degrees Celsius. Incoming shortwave radiation was -0.1925799999999999 W/m^2. Vapor pressure deficit was -0.4145272727272727 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.482775 m/s. Wind direction was -0.1583333333333333 decimal degrees. Relative humidity was 0.0225 percent. Net radiation was -0.0525366666666666 W/m^2. Incoming photosynthetic photon flux density was -0.0680046875 μmol Photon/m^2/s. CO2 concentration was -0.2930965 μmol CO2/mol. Latent heat flux was -0.1223833333333333 W/m^2. Sensible heat flux was -0.1403216666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -9.91", + "(B) 1.08", + "(C) 1.59", + "(D) 1.27", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FI-Qvd_2018-05-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0111", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.549649, longitude 1.106103. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.125190625 degrees Celsius. Incoming shortwave radiation was -0.4029225 W/m^2. Incoming longwave radiation was -0.3437525 W/m^2. Vapor pressure deficit was -0.4338909090909091 kPa. Air pressure was 0.1047923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46471 m/s. Wind direction was -0.3797222222222222 decimal degrees. Relative humidity was 0.189679 percent. Net radiation was -0.1517387833333333 W/m^2. Incoming photosynthetic photon flux density was -0.33465625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.37614703125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4386259523809523 W/m^2. Outgoing longwave radiation was -0.2601857142857143 W/m^2. CO2 concentration was -0.3098215 μmol CO2/mol. Soil heat flux was -0.1590383333333333 W/m^2. Latent heat flux was -0.1603328833333333 W/m^2. Sensible heat flux was -0.1726885333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.35", + "(B) 5.03", + "(C) 4.18", + "(D) 0.61", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Aur_2005-10-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0112", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.493653, longitude -0.956092. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0944375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3197224999999999 W/m^2. Vapor pressure deficit was -0.4954136363636364 kPa. Air pressure was 0.124 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48735 m/s. Wind direction was -0.6527777777777778 decimal degrees. Relative humidity was 0.4706499999999999 percent. Net radiation was -0.1760983333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4374406249999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43749375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2672142857142857 W/m^2. CO2 concentration was -0.2810749999999999 μmol CO2/mol. Soil heat flux was -0.1685433333333333 W/m^2. Latent heat flux was -0.1680915283333333 W/m^2. Sensible heat flux was -0.1700374166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.82", + "(B) -10.35", + "(C) 2.2", + "(D) 5.52", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Bil_2019-10-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0113", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 49.8721083, longitude 3.02065. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.00045 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.37581325 W/m^2. Vapor pressure deficit was -0.4977636363636363 kPa. Air pressure was 0.1315384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48272 m/s. Wind direction was -0.2292833333333332 decimal degrees. Relative humidity was 0.460235 percent. Net radiation was -0.1908863333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4372878125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437515 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4550947619047619 W/m^2. Outgoing longwave radiation was -0.3010561904761905 W/m^2. CO2 concentration was -0.27538025 μmol CO2/mol. Soil heat flux was -0.1751289333333333 W/m^2. Latent heat flux was -0.1671732193333333 W/m^2. Sensible heat flux was -0.1696768466666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.17", + "(B) 0.85", + "(C) 4.71", + "(D) 1.71", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-EM2_2019-12-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0114", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.24079, longitude 5.67865. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0725 degrees Celsius. Incoming shortwave radiation was -0.30923 W/m^2. Incoming longwave radiation was -0.3650625 W/m^2. Vapor pressure deficit was -0.4267727272727272 kPa. Air pressure was 0.0977692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47955 m/s. Wind direction was -0.2052777777777777 decimal degrees. Relative humidity was -0.0895 percent. Net radiation was -0.0772916666666666 W/m^2. Incoming photosynthetic photon flux density was -0.2261640624999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.426484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4346285714285714 W/m^2. Outgoing longwave radiation was -0.2759619047619047 W/m^2. CO2 concentration was -0.3051275 μmol CO2/mol. Latent heat flux was -0.14508 W/m^2. Sensible heat flux was -0.1402749999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.02", + "(B) 1.54", + "(C) -9.96", + "(D) 1.73", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-FBn_2013-12-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0115", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 48.8442, longitude 1.9519. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.087125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3260249999999999 W/m^2. Vapor pressure deficit was -0.4734772727272727 kPa. Air pressure was 0.1176923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4236399999999999 m/s. Wind direction was 0.3541666666666667 decimal degrees. Relative humidity was 0.3169999999999999 percent. Net radiation was -0.1744616666666666 W/m^2. Incoming photosynthetic photon flux density was -0.437359375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43798125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523504761904762 W/m^2. Outgoing longwave radiation was -0.2759021428571429 W/m^2. CO2 concentration was -0.315106 μmol CO2/mol. Soil heat flux was -0.161995 W/m^2. Latent heat flux was -0.1561898166666666 W/m^2. Sensible heat flux was -0.1843394833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.7", + "(B) 7.71", + "(C) -3.7", + "(D) -0.52", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Gri_2007-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0116", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 48.6741, longitude 7.06465. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0348906249999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33503 W/m^2. Vapor pressure deficit was -0.4954863636363636 kPa. Air pressure was 0.0972076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46465 m/s. Wind direction was 0.1604555555555555 decimal degrees. Relative humidity was 0.4453834999999999 percent. Net radiation was -0.1711160666666666 W/m^2. Incoming photosynthetic photon flux density was -0.437484375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375129375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4533174523809523 W/m^2. Outgoing longwave radiation was -0.2901066666666667 W/m^2. CO2 concentration was -0.3112912499999999 μmol CO2/mol. Soil heat flux was -0.167532395 W/m^2. Latent heat flux was -0.1681182 W/m^2. Sensible heat flux was -0.1801124 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.96", + "(B) 0.62", + "(C) 2.39", + "(D) 1.2", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Hes_2014-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0117", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.496438, longitude 1.237878. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07115625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3432324999999999 W/m^2. Vapor pressure deficit was -0.4897636363636364 kPa. Air pressure was 0.1103923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4957 m/s. Wind direction was 0.2116666666666666 decimal degrees. Relative humidity was 0.41645 percent. Net radiation was -0.1833983333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2791761904761904 W/m^2. CO2 concentration was -0.3177335 μmol CO2/mol. Soil heat flux was -0.1829233333333333 W/m^2. Latent heat flux was -0.1668750876666666 W/m^2. Sensible heat flux was -0.1689959066666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -20.39", + "(B) -17.2", + "(C) 3.25", + "(D) -0.47", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Lam_2005-08-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0118", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.7171, longitude -0.7693. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.051125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3680879999999999 W/m^2. Vapor pressure deficit was -0.4545545454545454 kPa. Air pressure was 0.1223846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.458115 m/s. Wind direction was -0.7928061111111112 decimal degrees. Relative humidity was 0.04 percent. Net radiation was -0.1934983333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2896054761904761 W/m^2. CO2 concentration was -0.30900425 μmol CO2/mol. Soil heat flux was -0.1723012166666666 W/m^2. Latent heat flux was -0.1656531746666666 W/m^2. Sensible heat flux was -0.1760466566666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LBr_2003-03-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0119", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.3229, longitude 2.2841. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.087878125 degrees Celsius. Incoming shortwave radiation was -0.49958725 W/m^2. Incoming longwave radiation was -0.30837775 W/m^2. Vapor pressure deficit was -0.4985090909090909 kPa. Air pressure was 0.1158192307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49705 m/s. Wind direction was -0.0602372222222222 decimal degrees. Relative humidity was 0.4897884999999999 percent. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521079711904762 W/m^2. Outgoing longwave radiation was -0.269907619047619 W/m^2. CO2 concentration was -0.2725675 μmol CO2/mol. Soil heat flux was -0.1680719533333333 W/m^2. Latent heat flux was -0.1664287509999999 W/m^2. Sensible heat flux was -0.16719385 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.83", + "(B) 1.08", + "(C) -8.12", + "(D) 3.21", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-LGt_2017-09-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0120", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 48.1184, longitude -1.79635. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0811875 degrees Celsius. Incoming shortwave radiation was -0.2958959999999999 W/m^2. Incoming longwave radiation was -0.340038 W/m^2. Vapor pressure deficit was -0.4573636363636363 kPa. Air pressure was 0.1240423076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4368 m/s. Wind direction was 0.1506499999999999 decimal degrees. Relative humidity was 0.1868995000000001 percent. Net radiation was -0.0797575 W/m^2. Incoming photosynthetic photon flux density was -0.187176875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.418423328125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4112685476190476 W/m^2. Outgoing longwave radiation was -0.2709197619047619 W/m^2. CO2 concentration was -0.3021705 μmol CO2/mol. Soil heat flux was -0.1474784166666666 W/m^2. Latent heat flux was -0.1458933333333333 W/m^2. Sensible heat flux was -0.1549657666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.4", + "(B) 4.66", + "(C) -14.26", + "(D) -4.36", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Mej_2021-02-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0121", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.7413, longitude 3.5957. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1176874999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32053175 W/m^2. Vapor pressure deficit was -0.4139681818181818 kPa. Air pressure was 0.0934615384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4515999999999999 m/s. Wind direction was 0.7484333333333334 decimal degrees. Relative humidity was 0.0647999999999999 percent. Net radiation was -0.17541 W/m^2. Incoming photosynthetic photon flux density was -0.4375015625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452022619047619 W/m^2. Outgoing longwave radiation was -0.2577157142857142 W/m^2. CO2 concentration was -0.309322 μmol CO2/mol. Soil heat flux was -0.1690440483333333 W/m^2. Latent heat flux was -0.1642976983333333 W/m^2. Sensible heat flux was -0.1776109833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.23", + "(B) 5.83", + "(C) -1.78", + "(D) 2.1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Pue_2005-07-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0122", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.572855, longitude 1.37474. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.053478125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.34367125 W/m^2. Vapor pressure deficit was -0.4783318181818182 kPa. Air pressure was 0.1180653846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.452425 m/s. Wind direction was 0.3915222222222221 decimal degrees. Relative humidity was 0.2861295000000001 percent. Net radiation was -0.1793843 W/m^2. Outgoing shortwave radiation was -0.4524200476190476 W/m^2. Outgoing longwave radiation was -0.2863480952380952 W/m^2. CO2 concentration was -0.2974885 μmol CO2/mol. Soil heat flux was -0.1684508616666666 W/m^2. Latent heat flux was -0.1595257166666666 W/m^2. Sensible heat flux was -0.1768871166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 7.25", + "(B) 1.92", + "(C) 6.42", + "(D) -5.58", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/FR-Tou_2018-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0123", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 64.1308, longitude -51.3861. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0315125 degrees Celsius. Incoming shortwave radiation was -0.43876575 W/m^2. Vapor pressure deficit was -0.4892272727272727 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48235 m/s. Wind direction was 0.4885305555555555 decimal degrees. Relative humidity was 0.3650759999999999 percent. Net radiation was -0.1390845 W/m^2. Incoming photosynthetic photon flux density was -0.35239578125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4458522619047619 W/m^2. CO2 concentration was -0.30542325 μmol CO2/mol. Latent heat flux was -0.1619304666666666 W/m^2. Sensible heat flux was -0.1544152166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.72", + "(B) 3.78", + "(C) 0.07", + "(D) -5.22", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-NuF_2012-06-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0124", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 74.4814, longitude -20.5545. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0470625 degrees Celsius. Incoming shortwave radiation was -0.30316675 W/m^2. Vapor pressure deficit was -0.4862636363636363 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4803949999999999 m/s. Wind direction was -0.0970472222222222 decimal degrees. Relative humidity was 0.355 percent. Net radiation was -0.0468333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.1459375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.415625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4066666666666667 W/m^2. CO2 concentration was -0.30846875 μmol CO2/mol. Soil heat flux was -0.1808333333333333 W/m^2. Latent heat flux was -0.1492824333333333 W/m^2. Sensible heat flux was -0.1358775833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.56", + "(B) -2.17", + "(C) 0.04", + "(D) 0.02", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaF_2011-08-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0125", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 74.4733, longitude -20.5503. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0059375 degrees Celsius. Incoming shortwave radiation was -0.3083999999999999 W/m^2. Vapor pressure deficit was -0.4762136363636363 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48363 m/s. Wind direction was -0.2787575000000001 decimal degrees. Relative humidity was 0.0425 percent. Net radiation was -0.17345 W/m^2. Incoming photosynthetic photon flux density was -0.21609375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3070714285714286 W/m^2. CO2 concentration was -0.2998357499999999 μmol CO2/mol. Latent heat flux was -0.1650689833333333 W/m^2. Sensible heat flux was -0.1724388166666667 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.3", + "(B) -0.25", + "(C) 0.02", + "(D) -1.19", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/GL-ZaH_2011-05-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0126", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 53.32309, longitude -7.641774. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.044240625 degrees Celsius. Incoming shortwave radiation was -0.4999975 W/m^2. Vapor pressure deficit was -0.4891318181818181 kPa. Wind speed was -0.468615 m/s. Wind direction was -0.0141666666666667 decimal degrees. Relative humidity was 0.3815 percent. Net radiation was -0.1703733333333333 W/m^2. Incoming photosynthetic photon flux density was -0.437496875 μmol Photon/m^2/s. CO2 concentration was -0.2785125 μmol CO2/mol. Soil heat flux was -0.1668856106666666 W/m^2. Latent heat flux was -0.1665591221666666 W/m^2. Sensible heat flux was -0.1713715166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.44", + "(B) 0.38", + "(C) 0.89", + "(D) 1.5", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IE-Cra_2020-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0127", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.345044585655, longitude 35.0519885122776. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.12203125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3429 W/m^2. Vapor pressure deficit was -0.4071363636363636 kPa. Air pressure was 0.0642807692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4755 m/s. Wind direction was -0.8466666666666667 decimal degrees. Relative humidity was 0.0501955 percent. Net radiation was -0.19645 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2558333333333333 W/m^2. CO2 concentration was -0.3098 μmol CO2/mol. Soil heat flux was -0.1687081933333333 W/m^2. Latent heat flux was -0.16770731 W/m^2. Sensible heat flux was -0.1709333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.74", + "(B) 1.23", + "(C) -4.77", + "(D) -3.84", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IL-Yat_2010-07-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0128", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.5237, longitude 14.9574. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1653125 degrees Celsius. Incoming shortwave radiation was -0.12425 W/m^2. Incoming longwave radiation was -0.31605 W/m^2. Vapor pressure deficit was -0.3813772727272727 kPa. Air pressure was 0.1215384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.465305 m/s. Wind direction was 0.4535277777777777 decimal degrees. Relative humidity was 0.1221 percent. Net radiation was -0.0062999999999999 W/m^2. Incoming photosynthetic photon flux density was 0.0425 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.400859375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4142619047619048 W/m^2. Outgoing longwave radiation was -0.1867619047619048 W/m^2. CO2 concentration was -0.3197115 μmol CO2/mol. Soil heat flux was -0.1465045833333333 W/m^2. Latent heat flux was -0.1435178666666666 W/m^2. Sensible heat flux was -0.066105 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.68", + "(B) 6.57", + "(C) 2.93", + "(D) 11.11", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BCi_2006-09-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0129", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.197755, longitude 10.741966. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.02321875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4999272727272727 kPa. Air pressure was 0.1323076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.463205 m/s. Wind direction was -0.6138977777777778 decimal degrees. Relative humidity was 0.499 percent. Net radiation was -0.1787643333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.2757075 μmol CO2/mol. Soil heat flux was -0.1699204166666666 W/m^2. Latent heat flux was -0.1645980633333333 W/m^2. Sensible heat flux was -0.1817510833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -13.78", + "(B) 3.39", + "(C) 8.2", + "(D) -3.54", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-BFt_2019-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0130", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.3804, longitude 12.0266. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.117625 degrees Celsius. Incoming shortwave radiation was -0.317075 W/m^2. Incoming longwave radiation was -0.3428327499999999 W/m^2. Vapor pressure deficit was -0.3735818181818182 kPa. Air pressure was 0.1084615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.43366 m/s. Wind direction was -0.7685680555555556 decimal degrees. Relative humidity was -0.13965 percent. Net radiation was -0.1065833333333333 W/m^2. Incoming photosynthetic photon flux density was -0.256984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4212214285714286 W/m^2. Outgoing longwave radiation was -0.2531514285714285 W/m^2. CO2 concentration was -0.3116879999999999 μmol CO2/mol. Soil heat flux was -0.1620125 W/m^2. Latent heat flux was -0.1406312666666666 W/m^2. Sensible heat flux was -0.1438921833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.13", + "(B) -6.45", + "(C) 3.86", + "(D) 2.15", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA1_2011-10-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0131", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.3772, longitude 12.026. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.215 degrees Celsius. Incoming shortwave radiation was -0.047 W/m^2. Incoming longwave radiation was -0.281641 W/m^2. Vapor pressure deficit was -0.137440909090909 kPa. Air pressure was 0.1084615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.480325 m/s. Wind direction was 0.477086111111111 decimal degrees. Relative humidity was -0.23285 percent. Net radiation was -0.005478 W/m^2. Incoming photosynthetic photon flux density was 0.09953125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3599088095238095 W/m^2. Outgoing longwave radiation was -0.1491811904761905 W/m^2. CO2 concentration was -0.311726 μmol CO2/mol. Soil heat flux was -0.14617705 W/m^2. Latent heat flux was -0.127705 W/m^2. Sensible heat flux was -0.0781958333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -6.86", + "(B) 2.24", + "(C) 0.62", + "(D) 2.4", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA2_2012-06-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0132", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.38, longitude 12.0222. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.196328125 degrees Celsius. Incoming shortwave radiation was -0.09725 W/m^2. Incoming longwave radiation was -0.3075805 W/m^2. Vapor pressure deficit was -0.2356954545454545 kPa. Air pressure was 0.1098423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.461445 m/s. Wind direction was 0.3132777777777777 decimal degrees. Relative humidity was -0.131948 percent. Net radiation was -0.0262421666666666 W/m^2. Incoming photosynthetic photon flux density was 0.0467890624999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3940535714285714 W/m^2. Outgoing longwave radiation was -0.1990190476190476 W/m^2. CO2 concentration was -0.309125 μmol CO2/mol. Soil heat flux was -0.1401518166666666 W/m^2. Latent heat flux was -0.1312287499999999 W/m^2. Sensible heat flux was -0.0697888333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.75", + "(B) 0.84", + "(C) -3.2", + "(D) 0.41", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-CA3_2012-08-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0133", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.8494, longitude 13.5881. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0265437499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.40193975 W/m^2. Vapor pressure deficit was -0.4996045454545454 kPa. Air pressure was 0.0014307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4838949999999999 m/s. Wind direction was -0.5378638888888889 decimal degrees. Relative humidity was 0.4902415 percent. Net radiation was -0.1975780166666666 W/m^2. Incoming photosynthetic photon flux density was -0.4372111796875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4507947071428572 W/m^2. Outgoing longwave radiation was -0.3177628571428572 W/m^2. CO2 concentration was -0.31554375 μmol CO2/mol. Soil heat flux was -0.1659365066666666 W/m^2. Latent heat flux was -0.1653016 W/m^2. Sensible heat flux was -0.1761924333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.3", + "(B) 1.56", + "(C) 0.1", + "(D) -14.76", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Col_2005-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0134", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.7043, longitude 12.3573. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.119 degrees Celsius. Incoming shortwave radiation was -0.499505 W/m^2. Incoming longwave radiation was -0.3242825 W/m^2. Vapor pressure deficit was -0.4792454545454545 kPa. Air pressure was 0.1264615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47885 m/s. Wind direction was -0.1066666666666666 decimal degrees. Relative humidity was 0.3964 percent. Net radiation was -0.1886733333333333 W/m^2. Incoming photosynthetic photon flux density was -0.435315625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4368890625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4516761904761904 W/m^2. Outgoing longwave radiation was -0.2542571428571429 W/m^2. CO2 concentration was -0.2711775 μmol CO2/mol. Soil heat flux was -0.1655191666666666 W/m^2. Latent heat flux was -0.1670430883333333 W/m^2. Sensible heat flux was -0.1765548 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.96", + "(B) -18.25", + "(C) 4.24", + "(D) -5.53", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cp2_2021-10-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0135", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.7052, longitude 12.3761. This site belongs to the Evergreen Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.054940625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4671772727272727 kPa. Air pressure was 0.1144115384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.480935 m/s. Wind direction was 0.4357083333333333 decimal degrees. Relative humidity was 0.195 percent. Net radiation was -0.1822633333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.29481275 μmol CO2/mol. Soil heat flux was -0.1673090816666666 W/m^2. Latent heat flux was -0.1672883333333333 W/m^2. Sensible heat flux was -0.1718499999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -6.81", + "(B) 3.11", + "(C) -6.57", + "(D) 5.9", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Cpz_2000-03-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0136", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.8126, longitude 8.6336. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.37645425 W/m^2. Vapor pressure deficit was -0.4824727272727273 kPa. Air pressure was 0.1074615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4942 m/s. Wind direction was -0.4534069444444444 decimal degrees. Relative humidity was 0.2269999999999999 percent. Net radiation was -0.1888529166666666 W/m^2. Incoming photosynthetic photon flux density was -0.43723090234375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4509578285714286 W/m^2. Outgoing longwave radiation was -0.3054257142857143 W/m^2. CO2 concentration was -0.28793725 μmol CO2/mol. Soil heat flux was -0.1687908333333333 W/m^2. Latent heat flux was -0.1665254548333333 W/m^2. Sensible heat flux was -0.1360146 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Isp_2013-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0137", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.9562, longitude 11.2813. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11105625 degrees Celsius. Incoming shortwave radiation was -0.23545975 W/m^2. Incoming longwave radiation was -0.34961425 W/m^2. Vapor pressure deficit was -0.4336181818181818 kPa. Air pressure was 0.0104423076923075 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48725 m/s. Wind direction was -0.3037638888888888 decimal degrees. Relative humidity was 0.1412449999999999 percent. Net radiation was -0.0366423333333333 W/m^2. Incoming photosynthetic photon flux density was -0.14427921875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4358592142857143 W/m^2. Outgoing longwave radiation was -0.2594838095238095 W/m^2. CO2 concentration was -0.322861 μmol CO2/mol. Soil heat flux was -0.1641484666666666 W/m^2. Latent heat flux was -0.1297403 W/m^2. Sensible heat flux was -0.0764951666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.71", + "(B) 1.11", + "(C) 1.42", + "(D) -13.15", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lav_2004-07-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0138", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.740481, longitude 12.750297. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0087499999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3773 W/m^2. Vapor pressure deficit was -0.4895590909090909 kPa. Air pressure was 0.1367307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.493 m/s. Wind direction was 0.6079749999999999 decimal degrees. Relative humidity was 0.2919999999999998 percent. Net radiation was -0.1845433333333333 W/m^2. Outgoing shortwave radiation was -0.451547619047619 W/m^2. Outgoing longwave radiation was -0.3120714285714285 W/m^2. CO2 concentration was -0.272823 μmol CO2/mol. Soil heat flux was -0.1739666666666666 W/m^2. Latent heat flux was -0.1665908543333333 W/m^2. Sensible heat flux was -0.1680386813333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.55", + "(B) 3.61", + "(C) 7.48", + "(D) 0.58", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Lsn_2016-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0139", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.0147, longitude 11.0458. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.011778125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.38903025 W/m^2. Vapor pressure deficit was -0.4881681818181818 kPa. Air pressure was 0.0 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.484495 m/s. Wind direction was 0.7127805555555555 decimal degrees. Relative humidity was 0.2554245 percent. Net radiation was -0.1891923333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4361191734375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437482623296875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4511550047619048 W/m^2. Outgoing longwave radiation was -0.3165516666666667 W/m^2. CO2 concentration was -0.2935467499999999 μmol CO2/mol. Soil heat flux was -0.1678191666666666 W/m^2. Latent heat flux was -0.1666496533333333 W/m^2. Sensible heat flux was -0.1769091 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.77", + "(B) -0.58", + "(C) -8.36", + "(D) -6.75", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-MBo_2019-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0140", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.49091, longitude 7.13943. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08578125 degrees Celsius. Incoming shortwave radiation was -0.13715975 W/m^2. Vapor pressure deficit was -0.4567727272727273 kPa. Air pressure was -0.0839230769230768 kPa. Wind speed was -0.466315 m/s. Wind direction was -0.1671777777777777 decimal degrees. Relative humidity was 0.1972 percent. Incoming photosynthetic photon flux density was -0.00139375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4070632812499999 μmol Photon/m^2/s. CO2 concentration was -0.3006527499999999 μmol CO2/mol. Latent heat flux was -0.1114163333333333 W/m^2. Sensible heat flux was -0.1227211666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.08", + "(B) 0.44", + "(C) -1.12", + "(D) -9.38", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Niv_2019-08-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0141", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.6062, longitude 8.1517. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09515625 degrees Celsius. Incoming shortwave radiation was -0.24095875 W/m^2. Incoming longwave radiation was -0.34574875 W/m^2. Vapor pressure deficit was -0.4416318181818181 kPa. Air pressure was 0.1251192307692308 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4716349999999999 m/s. Wind direction was 0.5621222222222223 decimal degrees. Relative humidity was 0.129 percent. Net radiation was -0.0406933333333333 W/m^2. Incoming photosynthetic photon flux density was -0.10809375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4231938095238095 W/m^2. Outgoing longwave radiation was -0.2591333333333334 W/m^2. CO2 concentration was -0.30777125 μmol CO2/mol. Soil heat flux was -0.1778780499999999 W/m^2. Latent heat flux was -0.1266341666666667 W/m^2. Sensible heat flux was -0.0673126666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.96", + "(B) -3.59", + "(C) -9.04", + "(D) 4.08", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Noe_2004-04-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0142", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.2009, longitude 9.061. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0938125 degrees Celsius. Incoming shortwave radiation was -0.47826025 W/m^2. Vapor pressure deficit was -0.4945454545454545 kPa. Air pressure was 0.1228423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4955299999999999 m/s. Wind direction was -0.5650166666666667 decimal degrees. Relative humidity was 0.464864 percent. Net radiation was -0.1600649333333333 W/m^2. Incoming photosynthetic photon flux density was -0.409902265625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. CO2 concentration was -0.2905582499999999 μmol CO2/mol. Soil heat flux was -0.1658708333333333 W/m^2. Latent heat flux was -0.164274415 W/m^2. Sensible heat flux was -0.16564701 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -6.01", + "(B) 4.72", + "(C) 2.23", + "(D) 5.67", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-PT1_2002-10-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0143", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.5869, longitude 11.4337. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.00603125 degrees Celsius. Incoming shortwave radiation was -0.4353855 W/m^2. Incoming longwave radiation was -0.3439642499999999 W/m^2. Vapor pressure deficit was -0.4963090909090909 kPa. Air pressure was -0.0422461538461537 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.492085 m/s. Wind direction was 0.3395555555555555 decimal degrees. Relative humidity was 0.428635 percent. Net radiation was -0.1486044 W/m^2. Incoming photosynthetic photon flux density was -0.413735 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.41615703125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4346454761904761 W/m^2. Outgoing longwave radiation was -0.3045647619047619 W/m^2. CO2 concentration was -0.30942525 μmol CO2/mol. Soil heat flux was -0.1672380416666666 W/m^2. Latent heat flux was -0.1549812833333333 W/m^2. Sensible heat flux was -0.1691963266666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -29.12", + "(B) -4.04", + "(C) 1.0", + "(D) 2.81", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ren_2010-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0144", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.4081, longitude 11.93. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0684375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33229225 W/m^2. Vapor pressure deficit was -0.5 kPa. Air pressure was 0.1092307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4613 m/s. Wind direction was 0.587125 decimal degrees. Relative humidity was 0.5 percent. Net radiation was -0.170505 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2840583333333333 W/m^2. CO2 concentration was -0.31141725 μmol CO2/mol. Latent heat flux was -0.167909 W/m^2. Sensible heat flux was -0.183602 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.07", + "(B) 1.48", + "(C) -9.6", + "(D) 4.4", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro1_2006-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0145", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.3903, longitude 11.9209. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.071625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4928590909090909 kPa. Air pressure was 0.0965384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4580349999999999 m/s. Wind direction was 0.4796805555555554 decimal degrees. Relative humidity was 0.442 percent. Net radiation was -0.1811283333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.310146 μmol CO2/mol. Soil heat flux was -0.1679506666666666 W/m^2. Latent heat flux was -0.16799788 W/m^2. Sensible heat flux was -0.1804051333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Ro2_2004-02-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0146", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.732, longitude 10.2909. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08965625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3148249999999999 W/m^2. Vapor pressure deficit was -0.4983272727272727 kPa. Air pressure was 0.1280769230769231 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48555 m/s. Wind direction was -0.4211111111111111 decimal degrees. Relative humidity was 0.48875 percent. Net radiation was -0.1726849999999999 W/m^2. Incoming photosynthetic photon flux density was -0.4376265625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519666666666667 W/m^2. Outgoing longwave radiation was -0.2683785714285714 W/m^2. CO2 concentration was -0.2709475 μmol CO2/mol. Soil heat flux was -0.1676666666666666 W/m^2. Latent heat flux was -0.1669066666666666 W/m^2. Sensible heat flux was -0.1733416666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -10.44", + "(B) 6.54", + "(C) 2.33", + "(D) -25.96", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SR2_2019-10-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0147", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.7279, longitude 10.2844. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.145125 degrees Celsius. Incoming shortwave radiation was -0.1673207499999999 W/m^2. Incoming longwave radiation was -0.326353 W/m^2. Vapor pressure deficit was -0.45475 kPa. Air pressure was 0.1213038461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47074 m/s. Wind direction was 0.5427777777777777 decimal degrees. Relative humidity was 0.3250999999999999 percent. Net radiation was 0.0177951666666666 W/m^2. Incoming photosynthetic photon flux density was -0.026296875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.40565625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4302771428571428 W/m^2. Outgoing longwave radiation was -0.2551933333333333 W/m^2. CO2 concentration was -0.30651775 μmol CO2/mol. Soil heat flux was -0.1594401666666666 W/m^2. Latent heat flux was -0.1404196833333333 W/m^2. Sensible heat flux was -0.1056946166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.32", + "(B) 3.37", + "(C) -11.56", + "(D) -2.87", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-SRo_2004-06-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0148", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.8444, longitude 7.5781. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0312375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.372525 W/m^2. Vapor pressure deficit was -0.4768818181818182 kPa. Air pressure was -0.0476999999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48729 m/s. Wind direction was -0.741856111111111 decimal degrees. Relative humidity was 0.2085499999999999 percent. Net radiation was -0.1844666666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43738224375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.305547619047619 W/m^2. CO2 concentration was -0.31048725 μmol CO2/mol. Soil heat flux was -0.1700593466666666 W/m^2. Latent heat flux was -0.1659408799999999 W/m^2. Sensible heat flux was -0.1707968883333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.01", + "(B) 6.97", + "(C) -5.4", + "(D) -5.61", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/IT-Tor_2012-10-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0149", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.3869, longitude 142.3186. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0984375 degrees Celsius. Incoming shortwave radiation was -0.46998225 W/m^2. Incoming longwave radiation was -0.355565 W/m^2. Vapor pressure deficit was -0.4513181818181818 kPa. Air pressure was 0.0734307692307692 kPa. Wind speed was -0.47136 m/s. Wind direction was -0.7916944444444444 decimal degrees. Relative humidity was 0.2022 percent. Incoming photosynthetic photon flux density was -0.39923125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4477107142857143 W/m^2. Outgoing longwave radiation was -0.2703380952380952 W/m^2. CO2 concentration was -0.3242609999999999 μmol CO2/mol. Soil heat flux was -0.1638806666666666 W/m^2. Latent heat flux was -0.1474423333333333 W/m^2. Sensible heat flux was -0.1827431666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-MBF_2003-07-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0150", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.2617, longitude 137.0788. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.037884375 degrees Celsius. Incoming shortwave radiation was -0.4828805 W/m^2. Incoming longwave radiation was -0.32768 W/m^2. Vapor pressure deficit was -0.4938636363636364 kPa. Air pressure was 0.1022576923076922 kPa. Precipitation was recorded at -0.49 mm. Wind speed was -0.468635 m/s. Wind direction was -0.8670555555555555 decimal degrees. Relative humidity was 0.429 percent. Incoming photosynthetic photon flux density was -0.4078125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452255 W/m^2. Outgoing longwave radiation was -0.2897642857142857 W/m^2. CO2 concentration was -0.2717492499999999 μmol CO2/mol. Soil heat flux was -0.1670118333333333 W/m^2. Latent heat flux was -0.1559693 W/m^2. Sensible heat flux was -0.1707453333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.5", + "(B) 0.68", + "(C) -3.99", + "(D) -10.95", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/JP-SMF_2006-02-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0151", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 27.8446, longitude -109.2977. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.2395 degrees Celsius. Incoming shortwave radiation was -0.28655 W/m^2. Incoming longwave radiation was -0.2691 W/m^2. Vapor pressure deficit was -0.0472681818181818 kPa. Air pressure was 0.0792499999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48414 m/s. Wind direction was 0.7955555555555555 decimal degrees. Relative humidity was -0.2386499999999999 percent. Outgoing shortwave radiation was -0.4338333333333333 W/m^2. Outgoing longwave radiation was -0.1808571428571428 W/m^2. CO2 concentration was -0.1905825 μmol CO2/mol. Soil heat flux was -0.1517304166666666 W/m^2. Latent heat flux was -0.170615965 W/m^2. Sensible heat flux was -0.0661091666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.45", + "(B) 0.7", + "(C) -0.79", + "(D) -0.31", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/MX-Tes_2004-07-09_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0152", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 52.2403, longitude 5.0713. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.140375 degrees Celsius. Incoming shortwave radiation was -0.1588875 W/m^2. Incoming longwave radiation was -0.325441 W/m^2. Vapor pressure deficit was -0.3425272727272727 kPa. Air pressure was 0.1253846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47292 m/s. Wind direction was -0.6751944444444444 decimal degrees. Relative humidity was -0.13655 percent. Net radiation was -0.0155006666666666 W/m^2. Outgoing shortwave radiation was -0.3809285714285714 W/m^2. Outgoing longwave radiation was -0.2434204761904762 W/m^2. CO2 concentration was -0.2939475 μmol CO2/mol. Soil heat flux was -0.1645379333333333 W/m^2. Latent heat flux was -0.0968758333333333 W/m^2. Sensible heat flux was -0.1399450333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.46", + "(B) -8.72", + "(C) 4.79", + "(D) 1.61", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Hor_2011-04-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0153", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 52.1666, longitude 5.7436. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.039759375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32786225 W/m^2. Vapor pressure deficit was -0.4985590909090909 kPa. Air pressure was 0.1284615384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49058 m/s. Wind direction was 0.3008333333333333 decimal degrees. Relative humidity was 0.4834999999999999 percent. Net radiation was -0.1668489181666666 W/m^2. Incoming photosynthetic photon flux density was -0.4369784375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4369946875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.28818 W/m^2. CO2 concentration was -0.3025385 μmol CO2/mol. Soil heat flux was -0.1663031666666666 W/m^2. Latent heat flux was -0.1624982999999999 W/m^2. Sensible heat flux was -0.17236915 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.32", + "(B) 1.79", + "(C) 3.22", + "(D) -0.57", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/NL-Loo_2005-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0154", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 9.3181, longitude -79.6346. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4331181818181818 kPa. Air pressure was 0.1153730769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.489865 m/s. Wind direction was 0.2619444444444445 decimal degrees. Relative humidity was 0.2575 percent. Net radiation was -0.20476 W/m^2. Incoming photosynthetic photon flux density was -0.43653125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.324491 μmol CO2/mol. Latent heat flux was -0.1657758 W/m^2. Sensible heat flux was -0.1759482166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.62", + "(B) 0.38", + "(C) -10.2", + "(D) 5.31", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPn_2007-03-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0155", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 9.3138, longitude -79.6314. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1387499999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4773681818181818 kPa. Air pressure was 0.1200230769230768 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.497065 m/s. Wind direction was -0.6227777777777778 decimal degrees. Relative humidity was 0.407 percent. Net radiation was -0.1757133333333333 W/m^2. Incoming photosynthetic photon flux density was -0.43653125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.2980939999999999 μmol CO2/mol. Latent heat flux was -0.1670603816666666 W/m^2. Sensible heat flux was -0.1668545166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.16", + "(B) 7.5", + "(C) 7.88", + "(D) -11.62", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/PA-SPs_2007-03-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0156", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 70.8291, longitude 147.4943. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1116531249999999 degrees Celsius. Incoming shortwave radiation was -0.49329975 W/m^2. Incoming longwave radiation was -0.301691 W/m^2. Vapor pressure deficit was -0.3814409090909091 kPa. Air pressure was 0.1157115384615384 kPa. Precipitation was recorded at -0.49665 mm. Wind speed was -0.455045 m/s. Wind direction was -0.2496769444444443 decimal degrees. Relative humidity was -0.1136104999999999 percent. Net radiation was -0.1670366666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4286389218749999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4504342857142857 W/m^2. Outgoing longwave radiation was -0.2477216666666666 W/m^2. CO2 concentration was -0.3138134999999999 μmol CO2/mol. Soil heat flux was -0.166745 W/m^2. Latent heat flux was -0.1566914 W/m^2. Sensible heat flux was -0.170774 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.34", + "(B) -5.67", + "(C) -1.87", + "(D) 1.75", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Cok_2005-07-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0157", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.4476, longitude 32.9019. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1039593749999999 degrees Celsius. Incoming shortwave radiation was -0.498284 W/m^2. Incoming longwave radiation was -0.34306875 W/m^2. Vapor pressure deficit was -0.4503772727272727 kPa. Air pressure was 0.0981423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47274 m/s. Wind direction was 0.4441222222222222 decimal degrees. Relative humidity was 0.2120765 percent. Net radiation was -0.19307045 W/m^2. Incoming photosynthetic photon flux density was -0.4350191609375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43741572921875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4533819928571428 W/m^2. Outgoing longwave radiation was -0.2664178571428571 W/m^2. CO2 concentration was -0.3101905 μmol CO2/mol. Soil heat flux was -0.1635592166666666 W/m^2. Latent heat flux was -0.1632128183333333 W/m^2. Sensible heat flux was -0.1775385333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.62", + "(B) 3.36", + "(C) 11.27", + "(D) -12.96", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fy2_2015-07-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0158", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.4615, longitude 32.9221. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.081228125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.39795825 W/m^2. Vapor pressure deficit was -0.4965954545454545 kPa. Air pressure was 0.1169961538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4830899999999999 m/s. Wind direction was -0.8386027777777778 decimal degrees. Relative humidity was 0.333167 percent. Net radiation was -0.1862766666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437515416671875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4524591271428571 W/m^2. Outgoing longwave radiation was -0.3284285714285714 W/m^2. CO2 concentration was -0.2969167499999999 μmol CO2/mol. Soil heat flux was -0.1675316666666666 W/m^2. Latent heat flux was -0.1675734499999999 W/m^2. Sensible heat flux was -0.17313715 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.95", + "(B) 0.11", + "(C) -0.13", + "(D) 6.37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Fyo_2016-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0159", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 54.7252, longitude 90.0022. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.1200625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.49605 kPa. Air pressure was 0.093076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.460855 m/s. Wind direction was 0.646163888888889 decimal degrees. Relative humidity was 0.1746000000000001 percent. Net radiation was -0.1715383333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. CO2 concentration was -0.3119115 μmol CO2/mol. Soil heat flux was -0.165527 W/m^2. Latent heat flux was -0.1667216231666666 W/m^2. Sensible heat flux was -0.1682178333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.19", + "(B) 0.59", + "(C) -0.01", + "(D) 0.12", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/RU-Ha1_2003-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0160", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 13.2829, longitude 30.4783. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1423125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.3132227272727272 kPa. Air pressure was 0.0852192307692308 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.482155 m/s. Wind direction was -0.2752777777777778 decimal degrees. Relative humidity was -0.24135 percent. Net radiation was -0.1916 W/m^2. Incoming photosynthetic photon flux density was -0.43749609375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3999375 μmol Photon/m^2/s. CO2 concentration was -0.32850225 μmol CO2/mol. Soil heat flux was -0.1731516666666666 W/m^2. Latent heat flux was -0.16737515 W/m^2. Sensible heat flux was -0.1717799833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.18", + "(B) 2.22", + "(C) -1.19", + "(D) 2.75", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SD-Dem_2005-02-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0161", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 56.09763, longitude 13.41897. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09355 degrees Celsius. Incoming shortwave radiation was -0.20429725 W/m^2. Incoming longwave radiation was -0.3470567499999999 W/m^2. Vapor pressure deficit was -0.4359363636363637 kPa. Air pressure was 0.1262038461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4552049999999999 m/s. Wind direction was 0.5597972222222224 decimal degrees. Relative humidity was -0.238885 percent. Net radiation was -0.0152726666666666 W/m^2. Incoming photosynthetic photon flux density was -0.0790609374999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4284675625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4280928095238095 W/m^2. Outgoing longwave radiation was -0.2656645238095238 W/m^2. CO2 concentration was -0.30555425 μmol CO2/mol. Soil heat flux was -0.165409625 W/m^2. Latent heat flux was -0.1397345833333333 W/m^2. Sensible heat flux was -0.0645483333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 4.21", + "(B) 1.71", + "(C) 6.54", + "(D) -9.62", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Htm_2015-06-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0162", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 60.08649722, longitude 17.47950278. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.090590625 degrees Celsius. Incoming shortwave radiation was -0.461479 W/m^2. Incoming longwave radiation was -0.3124317499999999 W/m^2. Vapor pressure deficit was -0.4705318181818181 kPa. Air pressure was 0.1177692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.443675 m/s. Wind direction was 0.4265638888888888 decimal degrees. Relative humidity was 0.303737 percent. Net radiation was -0.1466120166666666 W/m^2. Incoming photosynthetic photon flux density was -0.39074609375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.436139925 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4494335023809523 W/m^2. Outgoing longwave radiation was -0.2686547619047619 W/m^2. CO2 concentration was -0.29775675 μmol CO2/mol. Soil heat flux was -0.1657067083333333 W/m^2. Latent heat flux was -0.1595045 W/m^2. Sensible heat flux was -0.1576975 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.7", + "(B) 1.83", + "(C) -2.59", + "(D) 0.14", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Nor_2014-10-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0163", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 64.1725, longitude 19.738. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08259375 degrees Celsius. Incoming shortwave radiation was -0.3345277499999999 W/m^2. Vapor pressure deficit was -0.4810090909090909 kPa. Air pressure was 0.1192307692307692 kPa. Precipitation was recorded at -0.4993999999999999 mm. Wind speed was -0.48815 m/s. Wind direction was 0.4509333333333333 decimal degrees. Relative humidity was 0.3625 percent. Net radiation was -0.1075833333333333 W/m^2. Incoming photosynthetic photon flux density was -0.2386153124999999 μmol Photon/m^2/s. CO2 concentration was -0.3058145 μmol CO2/mol. Soil heat flux was -0.165707 W/m^2. Latent heat flux was -0.1290233333333333 W/m^2. Sensible heat flux was -0.1645078333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.79", + "(B) -8.86", + "(C) 1.05", + "(D) 2.94", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Ros_2017-07-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0164", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 68.35594288, longitude 19.04520892. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.016625 degrees Celsius. Incoming shortwave radiation was -0.49894 W/m^2. Incoming longwave radiation was -0.3524825 W/m^2. Vapor pressure deficit was -0.4963272727272727 kPa. Air pressure was 0.0948461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4206499999999999 m/s. Wind direction was 0.4116666666666666 decimal degrees. Relative humidity was 0.4475 percent. Net radiation was -0.1749416666666667 W/m^2. Incoming photosynthetic photon flux density was -0.435875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.436984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4535309523809523 W/m^2. Outgoing longwave radiation was -0.2994214285714285 W/m^2. CO2 concentration was -0.2994525 μmol CO2/mol. Soil heat flux was -0.1684248316666666 W/m^2. Latent heat flux was -0.1668483333333333 W/m^2. Sensible heat flux was -0.1864066666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.83", + "(B) -0.5", + "(C) -1.36", + "(D) 0.2", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Sto_2022-05-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0165", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 64.25611, longitude 19.7745. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0028999999999999 degrees Celsius. Incoming shortwave radiation was -0.3216995 W/m^2. Incoming longwave radiation was -0.373726 W/m^2. Vapor pressure deficit was -0.4631545454545455 kPa. Air pressure was 0.1017961538461539 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46548 m/s. Wind direction was 0.7744138888888888 decimal degrees. Relative humidity was -0.1413195 percent. Net radiation was -0.0829633333333333 W/m^2. Incoming photosynthetic photon flux density was -0.2305334375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.427771796875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4355196666666667 W/m^2. Outgoing longwave radiation was -0.2987473809523809 W/m^2. CO2 concentration was -0.3021359999999999 μmol CO2/mol. Soil heat flux was -0.1670835416666666 W/m^2. Latent heat flux was -0.1554003 W/m^2. Sensible heat flux was -0.1045149999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.48", + "(B) 0.25", + "(C) -0.73", + "(D) 0.52", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SE-Svb_2014-04-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0166", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 15.4028, longitude -15.4322. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.163159375 degrees Celsius. Incoming shortwave radiation was -0.37052225 W/m^2. Vapor pressure deficit was -0.4377090909090909 kPa. Wind speed was -0.46774 m/s. Wind direction was 0.1961055555555556 decimal degrees. Relative humidity was 0.2981854999999999 percent. Net radiation was -0.1247249666666666 W/m^2. Incoming photosynthetic photon flux density was -0.28826015625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.419973 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4050193809523809 W/m^2. Soil heat flux was -0.1625916346666666 W/m^2. Latent heat flux was -0.1253978333333333 W/m^2. Sensible heat flux was -0.1591077166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.7", + "(B) -0.58", + "(C) -5.0", + "(D) -10.11", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/SN-Dhr_2010-08-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0167", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 55.792546, longitude -3.2436918. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.049746875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3560675 W/m^2. Vapor pressure deficit was -0.4902863636363636 kPa. Air pressure was 0.1108461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.465225 m/s. Wind direction was 0.0983333333333332 decimal degrees. Relative humidity was 0.3481499999999999 percent. Net radiation was -0.1872166666666666 W/m^2. Incoming photosynthetic photon flux density was -0.437528125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4515690476190476 W/m^2. Outgoing longwave radiation was -0.2880571428571428 W/m^2. CO2 concentration was -0.28366825 μmol CO2/mol. Soil heat flux was -0.1685651666666666 W/m^2. Latent heat flux was -0.1675347308333333 W/m^2. Sensible heat flux was -0.1761989166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.35", + "(B) 4.57", + "(C) -5.19", + "(D) 2.28", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/UK-AMo_2022-04-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0168", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.8193, longitude -97.8198. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13209375 degrees Celsius. Incoming shortwave radiation was -0.4983845 W/m^2. Incoming longwave radiation was -0.30245 W/m^2. Vapor pressure deficit was -0.4979454545454546 kPa. Air pressure was 0.0967115384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.462275 m/s. Wind direction was -0.1338016666666665 decimal degrees. Relative humidity was 0.4909999999999999 percent. Net radiation was -0.1760071666666667 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522352380952381 W/m^2. Outgoing longwave radiation was -0.251952380952381 W/m^2. CO2 concentration was -0.31100275 μmol CO2/mol. Soil heat flux was -0.1744354166666666 W/m^2. Latent heat flux was -0.16451289 W/m^2. Sensible heat flux was -0.1702067333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.86", + "(B) -11.21", + "(C) 6.7", + "(D) -0.84", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A32_2015-06-17_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0169", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.8085, longitude -97.5489. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06821875 degrees Celsius. Incoming shortwave radiation was -0.4859485 W/m^2. Incoming longwave radiation was -0.364675 W/m^2. Vapor pressure deficit was -0.4307954545454546 kPa. Air pressure was 0.0995384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.473705 m/s. Wind direction was 0.250565 decimal degrees. Relative humidity was -0.07935 percent. Net radiation was -0.1825766666666666 W/m^2. Incoming photosynthetic photon flux density was -0.41640625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43412984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4481271428571428 W/m^2. Outgoing longwave radiation was -0.2916428571428571 W/m^2. CO2 concentration was -0.2959835 μmol CO2/mol. Soil heat flux was -0.165114125 W/m^2. Latent heat flux was -0.1627654166666666 W/m^2. Sensible heat flux was -0.1799261166666667 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.23", + "(B) 4.21", + "(C) -1.22", + "(D) -4.81", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-A74_2016-01-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0170", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.4267, longitude -99.42. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08515625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.341188 W/m^2. Vapor pressure deficit was -0.4796636363636363 kPa. Air pressure was 0.0741076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4941 m/s. Wind direction was -0.0779777777777777 decimal degrees. Relative humidity was 0.357 percent. Net radiation was -0.182641 W/m^2. Incoming photosynthetic photon flux density was -0.4375026562499999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43750109375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4508759523809524 W/m^2. Outgoing longwave radiation was -0.2727090476190476 W/m^2. CO2 concentration was -0.3043125 μmol CO2/mol. Soil heat flux was -0.1756665 W/m^2. Latent heat flux was -0.1689645 W/m^2. Sensible heat flux was -0.1678633333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.31", + "(B) -8.39", + "(C) 0.55", + "(D) 0.67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR1_2009-06-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0171", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.6358, longitude -99.5975. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15571875 degrees Celsius. Incoming shortwave radiation was -0.255755 W/m^2. Incoming longwave radiation was -0.2972102499999999 W/m^2. Vapor pressure deficit was -0.39675 kPa. Air pressure was 0.0661884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.43516 m/s. Wind direction was -0.0771722222222221 decimal degrees. Relative humidity was 0.13975 percent. Net radiation was -0.08686 W/m^2. Incoming photosynthetic photon flux density was -0.1243390625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.373884375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3844338095238095 W/m^2. Outgoing longwave radiation was -0.2364054761904762 W/m^2. CO2 concentration was -0.3086425 μmol CO2/mol. Soil heat flux was -0.14834 W/m^2. Latent heat flux was -0.1012385 W/m^2. Sensible heat flux was -0.1593881666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.1", + "(B) -8.19", + "(C) 0.68", + "(D) -2.93", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-AR2_2009-04-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0172", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.5497, longitude -98.0402. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08975 degrees Celsius. Incoming shortwave radiation was -0.157425 W/m^2. Vapor pressure deficit was -0.4159727272727272 kPa. Air pressure was 0.0884615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.405095 m/s. Wind direction was 0.9214083333333332 decimal degrees. Relative humidity was -0.0646 percent. Net radiation was -0.03995 W/m^2. Incoming photosynthetic photon flux density was -0.0321875 μmol Photon/m^2/s. CO2 concentration was -0.309599 μmol CO2/mol. Soil heat flux was -0.1589913333333333 W/m^2. Latent heat flux was -0.1453455 W/m^2. Sensible heat flux was -0.0658781666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARb_2005-03-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0173", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.5465, longitude -98.04. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06759375 degrees Celsius. Incoming shortwave radiation was -0.0995 W/m^2. Vapor pressure deficit was -0.4308363636363637 kPa. Air pressure was 0.0826923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.460115 m/s. Wind direction was -0.005011111111111 decimal degrees. Relative humidity was -0.0861499999999999 percent. Net radiation was -0.0267833333333333 W/m^2. Incoming photosynthetic photon flux density was 0.0328125 μmol Photon/m^2/s. CO2 concentration was -0.3059362499999999 μmol CO2/mol. Soil heat flux was -0.1529958333333333 W/m^2. Latent heat flux was -0.1425883333333333 W/m^2. Sensible heat flux was -0.0574253333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.85", + "(B) 0.86", + "(C) -0.55", + "(D) 3.68", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARc_2005-03-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0174", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.6058, longitude -97.4888. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1024062499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.329968 W/m^2. Vapor pressure deficit was -0.4918681818181818 kPa. Air pressure was 0.0961538461538461 kPa. Precipitation was recorded at -0.4996666666666667 mm. Wind speed was -0.478985 m/s. Wind direction was -0.6170336111111111 decimal degrees. Relative humidity was 0.452 percent. Net radiation was -0.1708499999999999 W/m^2. Incoming photosynthetic photon flux density was -0.4321828124999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43656046875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4515404761904762 W/m^2. Outgoing longwave radiation was -0.2677083333333333 W/m^2. CO2 concentration was -0.28315425 μmol CO2/mol. Soil heat flux was -0.1705195833333333 W/m^2. Latent heat flux was -0.1634438333333333 W/m^2. Sensible heat flux was -0.1677984933333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.8", + "(B) -19.09", + "(C) -0.08", + "(D) 2.42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ARM_2007-03-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0175", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 70.4696, longitude -157.4089. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0868125 degrees Celsius. Incoming shortwave radiation was -0.420674 W/m^2. Vapor pressure deficit was -0.4696363636363636 kPa. Air pressure was 0.1253846153846153 kPa. Precipitation was recorded at -0.4973333333333333 mm. Wind speed was -0.444095 m/s. Wind direction was -0.0538888888888888 decimal degrees. Relative humidity was 0.2934999999999999 percent. Net radiation was -0.1580166666666666 W/m^2. Incoming photosynthetic photon flux density was -0.34215625 μmol Photon/m^2/s. CO2 concentration was -0.31534425 μmol CO2/mol. Soil heat flux was -0.160785 W/m^2. Latent heat flux was -0.1504858666666666 W/m^2. Sensible heat flux was -0.1741566666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.38", + "(B) 0.11", + "(C) 0.22", + "(D) -1.8", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Atq_2005-08-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0176", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.0992, longitude -121.4993. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13128125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33404825 W/m^2. Vapor pressure deficit was -0.3823 kPa. Air pressure was 0.125676923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48125 m/s. Wind direction was 0.4670398611111112 decimal degrees. Relative humidity was -0.01865 percent. Net radiation was -0.1907499563333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375368515625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4524769585714285 W/m^2. Outgoing longwave radiation was -0.2621984128571428 W/m^2. CO2 concentration was -0.290292 μmol CO2/mol. Soil heat flux was -0.1722736333333333 W/m^2. Latent heat flux was -0.1615104666666666 W/m^2. Sensible heat flux was -0.1821171999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.19", + "(B) -0.44", + "(C) 9.31", + "(D) 6.18", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi1_2016-08-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0177", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1091, longitude -121.5351. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.075125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.359459 W/m^2. Vapor pressure deficit was -0.4859454545454545 kPa. Air pressure was 0.1263115384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.44813 m/s. Wind direction was 0.4513804222222221 decimal degrees. Relative humidity was 0.39 percent. Net radiation was -0.1884078696666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521919880952381 W/m^2. Outgoing longwave radiation was -0.2891233497619047 W/m^2. CO2 concentration was -0.294225 μmol CO2/mol. Soil heat flux was -0.1751858166666666 W/m^2. Latent heat flux was -0.1669261408333333 W/m^2. Sensible heat flux was -0.1767400833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.01", + "(B) 4.92", + "(C) 0.48", + "(D) 0.8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Bi2_2017-04-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0178", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.2167, longitude -86.5406. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1170374999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.328125 W/m^2. Vapor pressure deficit was -0.4484681818181818 kPa. Air pressure was 0.10625 kPa. Wind speed was -0.49667 m/s. Wind direction was 0.4605722222222223 decimal degrees. Relative humidity was 0.2406475 percent. Incoming photosynthetic photon flux density was -0.4375136346875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522416666666666 W/m^2. Outgoing longwave radiation was -0.2687380952380953 W/m^2. CO2 concentration was -0.28445725 μmol CO2/mol. Soil heat flux was -0.166543765 W/m^2. Latent heat flux was -0.1646383366666666 W/m^2. Sensible heat flux was -0.1747116166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.01", + "(B) 20.73", + "(C) 7.52", + "(D) -6.7", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BRG_2017-04-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0179", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 64.6936, longitude -148.33. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0587875 degrees Celsius. Incoming shortwave radiation was -0.41908475 W/m^2. Vapor pressure deficit was -0.4482590909090909 kPa. Air pressure was 0.1099884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.484805 m/s. Wind direction was -0.7193340867777778 decimal degrees. Relative humidity was 0.01786 percent. Net radiation was -0.1513438388883333 W/m^2. Incoming photosynthetic photon flux density was -0.3498777343749999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4340959523809524 W/m^2. CO2 concentration was -0.29506 μmol CO2/mol. Soil heat flux was -0.1686061116666666 W/m^2. Latent heat flux was -0.1615894666666666 W/m^2. Sensible heat flux was -0.165965735 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.42", + "(B) -3.62", + "(C) -0.07", + "(D) -0.16", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-BZo_2018-10-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0180", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7815, longitude -117.0821. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.04554375 degrees Celsius. Incoming shortwave radiation was -0.29451425 W/m^2. Vapor pressure deficit was -0.4763045454545455 kPa. Air pressure was 0.0614115384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45746 m/s. Wind direction was 0.4768958333333333 decimal degrees. Relative humidity was 0.244953 percent. Net radiation was -0.0998342666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1905220312499999 μmol Photon/m^2/s. CO2 concentration was -0.29879775 μmol CO2/mol. Latent heat flux was -0.1218663333333333 W/m^2. Sensible heat flux was -0.14606265 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF1_2017-05-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0181", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.784, longitude -117.0908. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0458187499999999 degrees Celsius. Incoming shortwave radiation was -0.327459 W/m^2. Vapor pressure deficit was -0.4715136363636363 kPa. Air pressure was 0.06395 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45976 m/s. Wind direction was 0.4428125 decimal degrees. Relative humidity was 0.19433825 percent. Net radiation was -0.0985056166666666 W/m^2. Incoming photosynthetic photon flux density was -0.2301188932291666 μmol Photon/m^2/s. CO2 concentration was -0.3012994999999999 μmol CO2/mol. Latent heat flux was -0.1328910999999999 W/m^2. Sensible heat flux was -0.1485111999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.6", + "(B) 2.94", + "(C) 0.6", + "(D) -1.45", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF2_2017-05-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0182", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7551, longitude -117.1261. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.132128125 degrees Celsius. Incoming shortwave radiation was 0.0174135 W/m^2. Vapor pressure deficit was -0.3702 kPa. Air pressure was 0.0663076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4872399999999999 m/s. Wind direction was 0.3995272222222221 decimal degrees. Relative humidity was -0.0688436999999999 percent. Net radiation was -0.0025536833333333 W/m^2. Incoming photosynthetic photon flux density was 0.1843925 μmol Photon/m^2/s. CO2 concentration was -0.3079575 μmol CO2/mol. Latent heat flux was -0.0658931666666666 W/m^2. Sensible heat flux was -0.1445652 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.18", + "(B) -25.82", + "(C) 4.24", + "(D) 1.42", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF3_2017-06-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0183", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7518, longitude -117.1285. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.154390625 degrees Celsius. Incoming shortwave radiation was -0.0595074999999999 W/m^2. Vapor pressure deficit was -0.3370727272727273 kPa. Air pressure was 0.0614461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46619 m/s. Wind direction was 0.4599236111111111 decimal degrees. Relative humidity was -0.0754816499999999 percent. Net radiation was 0.0221559333333333 W/m^2. Incoming photosynthetic photon flux density was 0.09193828125 μmol Photon/m^2/s. CO2 concentration was -0.30306325 μmol CO2/mol. Latent heat flux was -0.029289 W/m^2. Sensible heat flux was -0.1395485333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.76", + "(B) -6.72", + "(C) -22.43", + "(D) 1.01", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CF4_2017-06-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0184", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.09, longitude -109.39. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0944375 degrees Celsius. Incoming shortwave radiation was -0.3676 W/m^2. Vapor pressure deficit was -0.3866181818181818 kPa. Air pressure was 0.0015384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4807 m/s. Wind direction was -0.1555555555555555 decimal degrees. Relative humidity was -0.226 percent. Net radiation was -0.1456116666666666 W/m^2. Outgoing shortwave radiation was -0.4186666666666667 W/m^2. CO2 concentration was -0.3120225 μmol CO2/mol. Soil heat flux was -0.1706266666666666 W/m^2. Latent heat flux was -0.1643396666666666 W/m^2. Sensible heat flux was -0.1601183333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.08", + "(B) -0.1", + "(C) -0.68", + "(D) 0.07", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Cop_2002-04-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0185", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.6285, longitude -83.3471. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07394375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.315949 W/m^2. Vapor pressure deficit was -0.4895045454545454 kPa. Air pressure was 0.1081115384615385 kPa. Precipitation was recorded at -0.49238 mm. Wind speed was -0.457235 m/s. Wind direction was 0.2909861111111111 decimal degrees. Relative humidity was 0.4168690245000001 percent. Net radiation was -0.16679330335 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2778490714285714 W/m^2. CO2 concentration was -0.304129 μmol CO2/mol. Soil heat flux was -0.1541284 W/m^2. Latent heat flux was -0.1642576266666666 W/m^2. Sensible heat flux was -0.1764367333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 10.49", + "(B) -13.91", + "(C) 0.54", + "(D) -3.72", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CRT_2011-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0186", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.1031, longitude -89.5379. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0799875 degrees Celsius. Incoming shortwave radiation was -0.30464075 W/m^2. Incoming longwave radiation was -0.32102725 W/m^2. Vapor pressure deficit was -0.4040227272727273 kPa. Air pressure was 0.104226923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.496285 m/s. Wind direction was -0.1028562222222223 decimal degrees. Relative humidity was -0.22852695 percent. Net radiation was -0.0797752166666666 W/m^2. Outgoing shortwave radiation was -0.4093385714285714 W/m^2. Outgoing longwave radiation was -0.2352741428571428 W/m^2. CO2 concentration was -0.298541 μmol CO2/mol. Latent heat flux was -0.12541454 W/m^2. Sensible heat flux was -0.157263965 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -10.89", + "(B) 1.89", + "(C) 1.9", + "(D) -0.55", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS1_2018-07-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0187", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.1467, longitude -89.5002. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10908125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32280425 W/m^2. Vapor pressure deficit was -0.4864681818181818 kPa. Air pressure was 0.0997961538461538 kPa. Wind speed was -0.488175 m/s. Wind direction was -0.6941952222222222 decimal degrees. Relative humidity was 0.42556675 percent. Net radiation was -0.18155374 W/m^2. Outgoing shortwave radiation was -0.4524793386119047 W/m^2. Outgoing longwave radiation was -0.2630133809523809 W/m^2. CO2 concentration was -0.28741225 μmol CO2/mol. Soil heat flux was -0.1670989133333333 W/m^2. Latent heat flux was -0.1618466166666666 W/m^2. Sensible heat flux was -0.1736286166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.13", + "(B) -11.19", + "(C) 7.26", + "(D) -20.53", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS2_2021-07-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0188", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.1394, longitude -89.5727. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.020584375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3346002499999999 W/m^2. Vapor pressure deficit was -0.4999590909090909 kPa. Air pressure was 0.1027730769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.476755 m/s. Wind direction was -0.8381726666666667 decimal degrees. Relative humidity was 0.4993999999999999 percent. Net radiation was -0.1695107039999999 W/m^2. Outgoing shortwave radiation was -0.4536195238095238 W/m^2. Outgoing longwave radiation was -0.2932223809523809 W/m^2. CO2 concentration was -0.29671125 μmol CO2/mol. Latent heat flux was -0.1648272083333333 W/m^2. Sensible heat flux was -0.1637088416666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.1", + "(B) 0.79", + "(C) 0.26", + "(D) 5.97", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS3_2019-05-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0189", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.1597, longitude -89.5475. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.019965625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3676145 W/m^2. Vapor pressure deficit was -0.4888590909090909 kPa. Air pressure was 0.1027384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.493315 m/s. Wind direction was -0.4708926666666666 decimal degrees. Relative humidity was 0.340565 percent. Net radiation was -0.1893215066666666 W/m^2. Outgoing shortwave radiation was -0.453896759047619 W/m^2. Outgoing longwave radiation was -0.2973653809523809 W/m^2. CO2 concentration was -0.2944859999999999 μmol CO2/mol. Latent heat flux was -0.1671389366666666 W/m^2. Sensible heat flux was -0.1677392016666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.6", + "(B) 6.95", + "(C) 4.98", + "(D) 0.69", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-CS4_2020-05-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0190", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.3448, longitude -89.7117. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.058428125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33497575 W/m^2. Vapor pressure deficit was -0.4712681818181818 kPa. Air pressure was 0.1010423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47124 m/s. Wind direction was 0.880475 decimal degrees. Relative humidity was 0.231217 percent. Net radiation was -0.1750819666666666 W/m^2. Outgoing shortwave radiation was -0.4521915078571428 W/m^2. Outgoing longwave radiation was -0.2840188095238095 W/m^2. CO2 concentration was -0.2910005 μmol CO2/mol. Soil heat flux was -0.1680291316666666 W/m^2. Latent heat flux was -0.1653311233333333 W/m^2. Sensible heat flux was -0.1751110666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.24", + "(B) 0.22", + "(C) 0.08", + "(D) -9.44", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DFC_2018-10-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0191", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1235, longitude -121.549. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1429375 degrees Celsius. Incoming shortwave radiation was -0.0433232499999999 W/m^2. Incoming longwave radiation was -0.33287225 W/m^2. Vapor pressure deficit was -0.4048272727272727 kPa. Air pressure was 0.1264423076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46445 m/s. Wind direction was 0.5069499999999999 decimal degrees. Relative humidity was 0.1248499999999999 percent. Net radiation was 0.0416379999999999 W/m^2. Incoming photosynthetic photon flux density was 0.0909984374999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3645714285714286 W/m^2. Outgoing longwave radiation was -0.2436690476190476 W/m^2. CO2 concentration was -0.3033445 μmol CO2/mol. Soil heat flux was -0.1683578033333333 W/m^2. Latent heat flux was -0.0258673333333333 W/m^2. Sensible heat flux was -0.16075865 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 7.9", + "(B) 4.84", + "(C) -43.92", + "(D) 4.7", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-DS3_2021-08-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0192", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.6156, longitude -122.114. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10175 degrees Celsius. Incoming shortwave radiation was 0.01396 W/m^2. Incoming longwave radiation was -0.3357205 W/m^2. Vapor pressure deficit was -0.4749181818181818 kPa. Air pressure was 0.1275576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.440225 m/s. Wind direction was 0.7176008861111112 decimal degrees. Relative humidity was 0.3509999999999999 percent. Net radiation was 0.1151489438333333 W/m^2. Incoming photosynthetic photon flux density was 0.2344308701562499 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4181389869047619 W/m^2. Outgoing longwave radiation was -0.2432733354761904 W/m^2. CO2 concentration was -0.28758 μmol CO2/mol. Latent heat flux was -0.0509881666666666 W/m^2. Sensible heat flux was -0.1015896666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.53", + "(B) 0.31", + "(C) -0.57", + "(D) -6.62", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-EDN_2018-06-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0193", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 65.3968, longitude -148.9348. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1359031249999999 degrees Celsius. Incoming shortwave radiation was -0.4305785 W/m^2. Vapor pressure deficit was -0.3485636363636363 kPa. Air pressure was 0.098226923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4888 m/s. Wind direction was 0.2222747805555555 decimal degrees. Relative humidity was -0.1395085999999999 percent. Net radiation was -0.1493750542633333 W/m^2. Incoming photosynthetic photon flux density was -0.3444045 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4349172843125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4489746077395238 W/m^2. Soil heat flux was -0.1631938333333333 W/m^2. Latent heat flux was -0.1612186166666666 W/m^2. Sensible heat flux was -0.1614436683333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fcr_2011-05-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0194", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.1426, longitude -111.7273. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0812187499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3531499999999999 W/m^2. Vapor pressure deficit was -0.4768818181818182 kPa. Air pressure was -0.0498076923076922 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48395 m/s. Wind direction was 0.6808333333333334 decimal degrees. Relative humidity was 0.3304999999999999 percent. Net radiation was -0.1920899999999999 W/m^2. Incoming photosynthetic photon flux density was -0.43709375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4512792857142857 W/m^2. Outgoing longwave radiation was -0.2782619047619047 W/m^2. CO2 concentration was -0.30747275 μmol CO2/mol. Soil heat flux was -0.1687038333333333 W/m^2. Latent heat flux was -0.166283836 W/m^2. Sensible heat flux was -0.1717006833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fmf_2005-08-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0195", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.089, longitude -111.762. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1464687499999999 degrees Celsius. Incoming shortwave radiation was -0.0345 W/m^2. Incoming longwave radiation was -0.352525 W/m^2. Vapor pressure deficit was -0.2647363636363636 kPa. Air pressure was -0.051576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.475775 m/s. Wind direction was 0.1933333333333333 decimal degrees. Relative humidity was -0.3959 percent. Net radiation was 0.0511166666666666 W/m^2. Incoming photosynthetic photon flux density was 0.12515625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4120546875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4181690476190476 W/m^2. Outgoing longwave radiation was -0.2139047619047619 W/m^2. CO2 concentration was -0.30774175 μmol CO2/mol. Soil heat flux was -0.1556183333333333 W/m^2. Latent heat flux was -0.1199101666666666 W/m^2. Sensible heat flux was -0.0211389999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.07", + "(B) -4.8", + "(C) 1.49", + "(D) 3.1", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Fuf_2007-05-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0196", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.3665, longitude -106.2399. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.04915625 degrees Celsius. Incoming shortwave radiation was -0.388075 W/m^2. Incoming longwave radiation was -0.36930475 W/m^2. Vapor pressure deficit was -0.4335909090909091 kPa. Air pressure was -0.1145576923076922 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.466585 m/s. Wind direction was 0.3139564166666667 decimal degrees. Relative humidity was -0.18705 percent. Net radiation was -0.1285364756666666 W/m^2. Incoming photosynthetic photon flux density was -0.28946875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4276093749999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4416904761904762 W/m^2. Outgoing longwave radiation was -0.2864761904761905 W/m^2. CO2 concentration was -0.3082827499999999 μmol CO2/mol. Soil heat flux was -0.1674891666666666 W/m^2. Latent heat flux was -0.1600406833333333 W/m^2. Sensible heat flux was -0.1440652333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.41", + "(B) 3.15", + "(C) -0.54", + "(D) 0.95", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-GLE_2008-10-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0197", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.5378, longitude -72.1715. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.009375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4796272727272727 kPa. Air pressure was 0.1170076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.475 m/s. Wind direction was -0.6611111111111111 decimal degrees. Relative humidity was 0.1709999999999999 percent. Net radiation was -0.179 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.306625 μmol CO2/mol. Latent heat flux was -0.1674210333333333 W/m^2. Sensible heat flux was -0.1813 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.8", + "(B) 10.99", + "(C) 1.23", + "(D) -2.6", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ha1_2005-02-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0198", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 33.3455, longitude -79.1957. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.098240625 degrees Celsius. Incoming shortwave radiation was -0.1939402499999999 W/m^2. Incoming longwave radiation was -0.3523469999999999 W/m^2. Vapor pressure deficit was -0.4347727272727273 kPa. Air pressure was 0.1255153846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46015 m/s. Wind direction was 0.6083055555555555 decimal degrees. Relative humidity was 0.09841206 percent. Outgoing shortwave radiation was -0.4259128523015873 W/m^2. Outgoing longwave radiation was -0.2653136063492061 W/m^2. CO2 concentration was -0.3011069999999999 μmol CO2/mol. Latent heat flux was -0.104096 W/m^2. Sensible heat flux was -0.1333605833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -6.77", + "(B) -11.46", + "(C) 0.64", + "(D) 0.54", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB1_2019-01-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0199", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 33.3242, longitude -79.244. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09259375 degrees Celsius. Incoming shortwave radiation was -0.38710975 W/m^2. Incoming longwave radiation was -0.320994 W/m^2. Vapor pressure deficit was -0.4724318181818182 kPa. Air pressure was 0.1333461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46085 m/s. Wind direction was -0.6004997222222221 decimal degrees. Relative humidity was 0.3201513650000001 percent. Net radiation was -0.1101604456666666 W/m^2. Incoming photosynthetic photon flux density was -0.3050086005156249 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.431124301665625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4415842356357142 W/m^2. Outgoing longwave radiation was -0.2659043571428571 W/m^2. CO2 concentration was -0.3076985 μmol CO2/mol. Soil heat flux was -0.1666374188666666 W/m^2. Latent heat flux was -0.1504610666666666 W/m^2. Sensible heat flux was -0.1384247166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -8.61", + "(B) -1.04", + "(C) -15.44", + "(D) 3.26", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB2_2019-01-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0200", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 33.3482, longitude -79.2322. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0082125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.35719725 W/m^2. Vapor pressure deficit was -0.4974227272727273 kPa. Air pressure was 0.1401076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.496615 m/s. Wind direction was 0.2691888888888889 decimal degrees. Relative humidity was 0.4577117166666664 percent. Net radiation was -0.1789171373333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3012214960317459 W/m^2. CO2 concentration was -0.27791525 μmol CO2/mol. Soil heat flux was -0.1770294999999999 W/m^2. Latent heat flux was -0.1675549583333333 W/m^2. Sensible heat flux was -0.1665532809166666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HB3_2019-02-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0201", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6889, longitude -119.4641. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.131790625 degrees Celsius. Incoming shortwave radiation was -0.3757965 W/m^2. Vapor pressure deficit was -0.3408772727272727 kPa. Air pressure was 0.116576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4853499999999999 m/s. Wind direction was -0.1840423073097988 decimal degrees. Relative humidity was -0.2623653064496667 percent. Net radiation was -0.1361779347777778 W/m^2. Incoming photosynthetic photon flux density was -0.2779495208333333 μmol Photon/m^2/s. CO2 concentration was -0.3824309999999999 μmol CO2/mol. Soil heat flux was -0.1707644149999999 W/m^2. Latent heat flux was -0.1582499333333333 W/m^2. Sensible heat flux was -0.15280485 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.82", + "(B) -1.77", + "(C) -0.09", + "(D) -0.45", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn2_2018-09-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0202", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6878, longitude -119.4614. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07920625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32270375 W/m^2. Vapor pressure deficit was -0.4323772727272727 kPa. Air pressure was 0.1126461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.495025 m/s. Wind direction was 0.4280144898179537 decimal degrees. Relative humidity was -0.0072132416666666 percent. Net radiation was -0.1736890158333333 W/m^2. Outgoing shortwave radiation was -0.4518638958630952 W/m^2. Outgoing longwave radiation was -0.2743270297619048 W/m^2. CO2 concentration was -0.2823985 μmol CO2/mol. Soil heat flux was -0.1713694499999999 W/m^2. Latent heat flux was -0.166199078 W/m^2. Sensible heat flux was -0.17022363 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.92", + "(B) -1.21", + "(C) 0.2", + "(D) 0.56", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Hn3_2018-10-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0203", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.2091, longitude -68.747. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1558125 degrees Celsius. Incoming shortwave radiation was -0.125675 W/m^2. Incoming longwave radiation was -0.330675 W/m^2. Vapor pressure deficit was -0.3206090909090909 kPa. Air pressure was 0.1161538461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48631 m/s. Wind direction was 0.4840791666666667 decimal degrees. Relative humidity was -0.1252499999999999 percent. Net radiation was 0.0249 W/m^2. Incoming photosynthetic photon flux density was 0.08421875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4235285714285714 W/m^2. Outgoing longwave radiation was -0.2371428571428571 W/m^2. CO2 concentration was -0.2875834999999999 μmol CO2/mol. Latent heat flux was -0.1054981666666666 W/m^2. Sensible heat flux was -0.082008 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -13.3", + "(B) 5.88", + "(C) 0.06", + "(D) 0.55", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ho2_2017-09-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0204", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.8608, longitude -77.8488. This site belongs to the Cropland/Natural Vegetation Mosaics type: Lands with a mosaic of croplands, forest, shrublands, and grasslands in which no one component comprises more than 60% of the landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1514687499999999 degrees Celsius. Incoming shortwave radiation was -0.150918 W/m^2. Incoming longwave radiation was -0.2688669999999999 W/m^2. Vapor pressure deficit was -0.3277272727272727 kPa. Air pressure was 0.1029884615384614 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.490965 m/s. Wind direction was -0.8373471312499999 decimal degrees. Relative humidity was -0.12603412325 percent. Net radiation was 0.0198905333333333 W/m^2. Outgoing shortwave radiation was -0.3889581428571428 W/m^2. Outgoing longwave radiation was -0.2297283095238095 W/m^2. CO2 concentration was -0.3126045 μmol CO2/mol. Latent heat flux was -0.1085609999999999 W/m^2. Sensible heat flux was -0.1391450166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-HWB_2015-07-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0205", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.8406, longitude -88.241. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0209375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4943181818181818 kPa. Air pressure was 0.1029615384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4622 m/s. Wind direction was 0.8597222222222223 decimal degrees. Relative humidity was 0.3709999999999999 percent. Net radiation was -0.1739166666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. CO2 concentration was -0.303925 μmol CO2/mol. Soil heat flux was -0.1737166666666666 W/m^2. Latent heat flux was -0.1642166666666666 W/m^2. Sensible heat flux was -0.1809333333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -12.04", + "(B) 3.53", + "(C) 0.86", + "(D) -12.25", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-IB2_2004-11-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0206", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 68.6068, longitude -149.2958. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0915625 degrees Celsius. Incoming shortwave radiation was -0.42305 W/m^2. Vapor pressure deficit was -0.4232727272727273 kPa. Air pressure was 0.0396153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4716749999999999 m/s. Wind direction was -1.0 decimal degrees. Relative humidity was -0.0039 percent. Net radiation was -0.1378833333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4417999999999999 W/m^2. CO2 concentration was -0.3107749999999999 μmol CO2/mol. Soil heat flux was -0.1665536666666666 W/m^2. Latent heat flux was -0.1532164733333333 W/m^2. Sensible heat flux was -0.1586961716666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.13", + "(B) 0.11", + "(C) 0.12", + "(D) -0.4", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICh_2008-06-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0207", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 68.6063, longitude -149.3041. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0905 degrees Celsius. Incoming shortwave radiation was -0.3692 W/m^2. Vapor pressure deficit was -0.4294 kPa. Air pressure was 0.0492307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.447325 m/s. Wind direction was -0.6815569444444445 decimal degrees. Relative humidity was 0.0292 percent. Net radiation was -0.1050666666666666 W/m^2. Incoming photosynthetic photon flux density was -0.2594009375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4248729687499999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.433747619047619 W/m^2. CO2 concentration was -0.306375 μmol CO2/mol. Soil heat flux was -0.1580231166666666 W/m^2. Latent heat flux was -0.1480012666666666 W/m^2. Sensible heat flux was -0.1574794666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.42", + "(B) 0.14", + "(C) 0.11", + "(D) 0.35", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ICt_2012-06-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0208", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 68.4865, longitude -155.7503. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.063265625 degrees Celsius. Incoming shortwave radiation was -0.4253274999999999 W/m^2. Incoming longwave radiation was -0.317745 W/m^2. Vapor pressure deficit was -0.4933681818181818 kPa. Air pressure was 0.0787615384615385 kPa. Precipitation was recorded at -0.4983333333333333 mm. Wind speed was -0.484075 m/s. Wind direction was 0.0026461111111111 decimal degrees. Relative humidity was 0.4404049999999999 percent. Net radiation was -0.1275333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.34299375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43159046875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4403383333333333 W/m^2. Outgoing longwave radiation was -0.2756309523809524 W/m^2. CO2 concentration was -0.321735 μmol CO2/mol. Soil heat flux was -0.1599175 W/m^2. Latent heat flux was -0.1472414666666666 W/m^2. Sensible heat flux was -0.1631383761666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.56", + "(B) -1.88", + "(C) -4.72", + "(D) -7.08", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ivo_2004-06-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0209", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 32.582, longitude -106.635. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.14873125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32013975 W/m^2. Vapor pressure deficit was -0.3399909090909091 kPa. Air pressure was 0.0078461538461539 kPa. Precipitation was recorded at -0.5 mm. Wind direction was -0.4684227962962953 decimal degrees. Relative humidity was -0.0968865149999999 percent. Net radiation was -0.1884286349999999 W/m^2. Incoming photosynthetic photon flux density was -0.4374848560130208 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.437125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4515574285714285 W/m^2. Outgoing longwave radiation was -0.2517398333333333 W/m^2. CO2 concentration was -0.31057825 μmol CO2/mol. Soil heat flux was -0.1739774333333333 W/m^2. Latent heat flux was -0.1638944633333333 W/m^2. Sensible heat flux was -0.1721702833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.22", + "(B) 0.27", + "(C) 0.49", + "(D) 0.72", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo1_2012-08-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0210", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 32.5849, longitude -106.6032. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09375 degrees Celsius. Incoming shortwave radiation was -0.3923935 W/m^2. Vapor pressure deficit was -0.3798681818181818 kPa. Air pressure was 0.0069230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45 m/s. Wind direction was -0.8525411111111112 decimal degrees. Relative humidity was -0.27465 percent. Net radiation was -0.1465333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.29431790625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.415152221875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4269833380952381 W/m^2. CO2 concentration was -0.31544475 μmol CO2/mol. Soil heat flux was -0.1713352166666666 W/m^2. Latent heat flux was -0.166507345 W/m^2. Sensible heat flux was -0.13830045 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.91", + "(B) 0.78", + "(C) 0.08", + "(D) -0.33", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Jo2_2014-05-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0211", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.0561, longitude -95.1907. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.085428125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.4011572499999999 W/m^2. Vapor pressure deficit was -0.4977590909090909 kPa. Air pressure was 0.1105884615384614 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.485745 m/s. Wind direction was 0.5100508183333333 decimal degrees. Relative humidity was 0.3840187751499999 percent. Net radiation was -0.180165345 W/m^2. Incoming photosynthetic photon flux density was -0.4374879038454687 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4372293518699999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.451896831547619 W/m^2. Outgoing longwave radiation was -0.3361737741666666 W/m^2. CO2 concentration was -0.30793975 μmol CO2/mol. Soil heat flux was -0.1684464516666666 W/m^2. Latent heat flux was -0.1673588433333333 W/m^2. Sensible heat flux was -0.1698841016666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.9", + "(B) 0.02", + "(C) -1.75", + "(D) 0.0", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KFS_2009-12-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0212", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.7745, longitude -97.5684. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.120121875 degrees Celsius. Incoming shortwave radiation was -0.19375 W/m^2. Incoming longwave radiation was -0.32875175 W/m^2. Vapor pressure deficit was -0.431 kPa. Air pressure was 0.0921115384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47997 m/s. Wind direction was 0.9762644327777776 decimal degrees. Relative humidity was 0.1929227991 percent. Net radiation was -0.0221192449999999 W/m^2. Incoming photosynthetic photon flux density was -0.110785179640625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3974756023809523 W/m^2. Outgoing longwave radiation was -0.2590223333333333 W/m^2. CO2 concentration was -0.29099775 μmol CO2/mol. Soil heat flux was -0.1650752 W/m^2. Latent heat flux was -0.12493035 W/m^2. Sensible heat flux was -0.1492216833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.37", + "(B) -0.87", + "(C) -18.88", + "(D) 4.61", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KLS_2012-04-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0213", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 28.4583, longitude -80.6709. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1724375 degrees Celsius. Incoming shortwave radiation was -0.49993325 W/m^2. Vapor pressure deficit was -0.4551954545454545 kPa. Air pressure was 0.1276923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.465715 m/s. Wind direction was 0.7865222222222223 decimal degrees. Relative humidity was 0.3665 percent. Net radiation was -0.1763606666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4374196875 μmol Photon/m^2/s. CO2 concentration was -0.3139105 μmol CO2/mol. Soil heat flux was -0.166305 W/m^2. Latent heat flux was -0.1667933333333333 W/m^2. Sensible heat flux was -0.1780666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -13.0", + "(B) 1.04", + "(C) 4.01", + "(D) 6.16", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS1_2002-09-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0214", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 28.6086, longitude -80.6715. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09328125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4768409090909091 kPa. Air pressure was 0.1261538461538462 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.482445 m/s. Wind direction was -0.7036111111111112 decimal degrees. Relative humidity was 0.35 percent. Net radiation was -0.189695 W/m^2. Incoming photosynthetic photon flux density was -0.4375321875 μmol Photon/m^2/s. CO2 concentration was -0.30845 μmol CO2/mol. Soil heat flux was -0.17315 W/m^2. Latent heat flux was -0.1676733333333333 W/m^2. Sensible heat flux was -0.1729277833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS2_2003-01-09_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0215", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 28.7084, longitude -80.7427. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11175 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3368 W/m^2. Vapor pressure deficit was -0.4458136363636364 kPa. Air pressure was 0.1309576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4779299999999999 m/s. Wind direction was -0.9245508484722222 decimal degrees. Relative humidity was 0.2091499999999999 percent. Net radiation was -0.1907426666666667 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4509940476190476 W/m^2. Outgoing longwave radiation was -0.2649047619047618 W/m^2. CO2 concentration was -0.298282 μmol CO2/mol. Latent heat flux was -0.1608310333333333 W/m^2. Sensible heat flux was -0.1755142833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.28", + "(B) 3.52", + "(C) 2.83", + "(D) -3.5", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-KS3_2018-04-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0216", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 36.3566, longitude -119.0922. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0616874999999999 degrees Celsius. Incoming shortwave radiation was -0.4992825 W/m^2. Vapor pressure deficit was -0.4761 kPa. Air pressure was 0.1160769230769231 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4884 m/s. Wind direction was -0.5785555555555556 decimal degrees. Relative humidity was 0.2870500000000001 percent. Net radiation was -0.185905 W/m^2. Incoming photosynthetic photon flux density was -0.4366375 μmol Photon/m^2/s. CO2 concentration was -0.29084775 μmol CO2/mol. Soil heat flux was -0.17875 W/m^2. Latent heat flux was -0.165565 W/m^2. Sensible heat flux was -0.1695616666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.47", + "(B) -3.81", + "(C) 1.1", + "(D) -2.98", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Lin_2009-11-09_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0217", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.5659, longitude -110.1344. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.039209375 degrees Celsius. Incoming shortwave radiation was -0.4995765 W/m^2. Vapor pressure deficit was -0.4985409090909091 kPa. Air pressure was 0.0240884615384615 kPa. Precipitation was recorded at -0.4991533333333333 mm. Wind speed was -0.485295 m/s. Wind direction was -0.4492755555555556 decimal degrees. Relative humidity was 0.4831529999999999 percent. Net radiation was -0.1713229 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.31070975 μmol CO2/mol. Soil heat flux was -0.1686976083333333 W/m^2. Latent heat flux was -0.1665459104999999 W/m^2. Sensible heat flux was -0.1593511166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -10.13", + "(B) -1.04", + "(C) 0.75", + "(D) -7.98", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-LS2_2004-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0218", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.5794, longitude -121.5. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.203975 degrees Celsius. Incoming shortwave radiation was -0.0916504999999999 W/m^2. Vapor pressure deficit was -0.1439818181818181 kPa. Air pressure was 0.05 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47403 m/s. Wind direction was -0.5992583333333333 decimal degrees. Relative humidity was -0.294315 percent. Net radiation was -0.0248603333333333 W/m^2. Incoming photosynthetic photon flux density was 0.0533046874999999 μmol Photon/m^2/s. CO2 concentration was -0.31006375 μmol CO2/mol. Soil heat flux was -0.13571 W/m^2. Latent heat flux was -0.1539248333333333 W/m^2. Sensible heat flux was -0.077705 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.21", + "(B) 2.85", + "(C) 0.21", + "(D) -0.32", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me1_2004-07-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0219", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.4526, longitude -121.5589. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.01658125 degrees Celsius. Incoming shortwave radiation was -0.496365 W/m^2. Incoming longwave radiation was -0.365259 W/m^2. Vapor pressure deficit was -0.49815 kPa. Air pressure was 0.0196884615384616 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49618 m/s. Wind direction was -0.4405555555555555 decimal degrees. Relative humidity was 0.4595 percent. Net radiation was -0.173915 W/m^2. Incoming photosynthetic photon flux density was -0.43215625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4509595238095238 W/m^2. Outgoing longwave radiation was -0.3066380952380952 W/m^2. CO2 concentration was -0.3025394999999999 μmol CO2/mol. Soil heat flux was -0.1677477666666666 W/m^2. Latent heat flux was -0.1617984333333333 W/m^2. Sensible heat flux was -0.1691992 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.5", + "(B) -5.75", + "(C) 0.05", + "(D) -12.61", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me2_2005-11-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0220", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.3154, longitude -121.6078. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.041146875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3359237499999999 W/m^2. Vapor pressure deficit was -0.4687636363636364 kPa. Air pressure was 0.0480346153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.468215 m/s. Wind direction was 0.4527777777777778 decimal degrees. Relative humidity was 0.1478099999999999 percent. Net radiation was -0.1687665 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.293117619047619 W/m^2. CO2 concentration was -0.307546 μmol CO2/mol. Latent heat flux was -0.1681261666666666 W/m^2. Sensible heat flux was -0.1784743333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.75", + "(B) -1.37", + "(C) 1.05", + "(D) 0.58", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me3_2009-01-11_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0221", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.4992, longitude -121.6224. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.00644375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.4870454545454545 kPa. Air pressure was 0.0538461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48387 m/s. Wind direction was 0.1399999999999999 decimal degrees. Relative humidity was 0.2515 percent. Net radiation was -0.1853783333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.3119945 μmol CO2/mol. Soil heat flux was -0.1706481666666666 W/m^2. Latent heat flux was -0.167485 W/m^2. Sensible heat flux was -0.1672316666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me4_2000-03-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0222", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.4372, longitude -121.5668. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0132124999999999 degrees Celsius. Incoming shortwave radiation was -0.49999225 W/m^2. Vapor pressure deficit was -0.4850454545454545 kPa. Air pressure was 0.0253923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4906649999999999 m/s. Wind direction was 0.3008333333333333 decimal degrees. Relative humidity was 0.2684999999999999 percent. Net radiation was -0.1868916666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. CO2 concentration was -0.3181 μmol CO2/mol. Soil heat flux was -0.1721703333333333 W/m^2. Latent heat flux was -0.1657533333333333 W/m^2. Sensible heat flux was -0.186635 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.04", + "(B) 0.12", + "(C) -1.38", + "(D) 2.03", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me5_2000-04-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0223", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.3233, longitude -121.6078. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06478125 degrees Celsius. Incoming shortwave radiation was -0.2993 W/m^2. Incoming longwave radiation was -0.3554575 W/m^2. Vapor pressure deficit was -0.4421818181818182 kPa. Air pressure was 0.0435769230769231 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4907 m/s. Wind direction was -0.6054166666666666 decimal degrees. Relative humidity was -0.0049499999999999 percent. Net radiation was -0.0775166666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1955875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4322119047619047 W/m^2. Outgoing longwave radiation was -0.2711047619047618 W/m^2. CO2 concentration was -0.3009 μmol CO2/mol. Soil heat flux was -0.15275 W/m^2. Latent heat flux was -0.1381616666666666 W/m^2. Sensible heat flux was -0.1331016666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.39", + "(B) -4.08", + "(C) 1.67", + "(D) 1.48", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Me6_2015-02-11_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0224", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.2298, longitude -92.1167. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.060721875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3596045 W/m^2. Vapor pressure deficit was -0.4734136363636363 kPa. Air pressure was 0.1084884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48177 m/s. Wind direction was -0.718873611111111 decimal degrees. Relative humidity was 0.2574080499999999 percent. Net radiation was -0.1916141983333333 W/m^2. Incoming photosynthetic photon flux density was -0.43748145868125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43751958858125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4511577109523809 W/m^2. Outgoing longwave radiation was -0.2856725476190476 W/m^2. CO2 concentration was -0.307065 μmol CO2/mol. Soil heat flux was -0.1776227833333333 W/m^2. Latent heat flux was -0.1650188 W/m^2. Sensible heat flux was -0.1761711666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.69", + "(B) 1.6", + "(C) -0.12", + "(D) 2.73", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo1_2015-10-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0225", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.2311, longitude -92.1497. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11996875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3043515 W/m^2. Vapor pressure deficit was -0.4928681818181818 kPa. Air pressure was 0.1013153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49444 m/s. Wind direction was 0.3648147222222222 decimal degrees. Relative humidity was 0.4647518499999999 percent. Net radiation was -0.1765619033333333 W/m^2. Incoming photosynthetic photon flux density was -0.4374984567403125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374866139203125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4515676454761904 W/m^2. Outgoing longwave radiation was -0.2532290714285714 W/m^2. CO2 concentration was -0.29700625 μmol CO2/mol. Soil heat flux was -0.1747424333333333 W/m^2. Latent heat flux was -0.1637919333333333 W/m^2. Sensible heat flux was -0.1663127116666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.48", + "(B) 0.5", + "(C) 8.37", + "(D) 0.25", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mo3_2016-06-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0226", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.7441, longitude -92.2. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.122 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3265 W/m^2. Vapor pressure deficit was -0.4247681818181818 kPa. Air pressure was 0.1046153846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4833 m/s. Wind direction was 0.1694444444444444 decimal degrees. Relative humidity was 0.1354999999999999 percent. Net radiation was -0.1876666666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2583333333333333 W/m^2. CO2 concentration was -0.3160705 μmol CO2/mol. Soil heat flux was -0.1665 W/m^2. Latent heat flux was -0.16582547 W/m^2. Sensible heat flux was -0.1684818833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.31", + "(B) -0.34", + "(C) -6.48", + "(D) 7.6", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-MOz_2004-06-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0227", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 34.4385, longitude -106.2377. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.18074375 degrees Celsius. Incoming shortwave radiation was 0.02033 W/m^2. Incoming longwave radiation was -0.34137575 W/m^2. Vapor pressure deficit was -0.1670954545454545 kPa. Air pressure was -0.0533846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47453 m/s. Wind direction was 0.5663388888888891 decimal degrees. Relative humidity was -0.41809252 percent. Net radiation was 0.0510608383333333 W/m^2. Incoming photosynthetic photon flux density was 0.175744484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3928353095238095 W/m^2. Outgoing longwave radiation was -0.176343219047619 W/m^2. CO2 concentration was -0.31061425 μmol CO2/mol. Latent heat flux was -0.1554828166666666 W/m^2. Sensible heat flux was -0.0020783333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.12", + "(B) 1.89", + "(C) 3.09", + "(D) -1.22", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Mpj_2008-06-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0228", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.0499, longitude -121.765. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08821875 degrees Celsius. Incoming shortwave radiation was -0.28754725 W/m^2. Vapor pressure deficit was -0.43555 kPa. Air pressure was 0.1284615384615385 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.464705 m/s. Wind direction was -0.6681342472222221 decimal degrees. Relative humidity was 0.0599499999999999 percent. Net radiation was -0.0963380283333333 W/m^2. Incoming photosynthetic photon flux density was -0.1653818784375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4209938909375 μmol Photon/m^2/s. CO2 concentration was -0.30624725 μmol CO2/mol. Latent heat flux was -0.135184 W/m^2. Sensible heat flux was -0.1605461666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Myb_2011-03-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0229", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.8118, longitude -76.7119. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0296625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.33679575 W/m^2. Vapor pressure deficit was -0.4983681818181818 kPa. Air pressure was 0.1375692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.496255 m/s. Wind direction was -0.7843938888888888 decimal degrees. Relative humidity was 0.479049346 percent. Net radiation was -0.1702162166666666 W/m^2. Incoming photosynthetic photon flux density was -0.4382048231678125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.45168885 W/m^2. Outgoing longwave radiation was -0.2929366666666666 W/m^2. CO2 concentration was -0.28208375 μmol CO2/mol. Soil heat flux was -0.1702466666666666 W/m^2. Latent heat flux was -0.1691442466666666 W/m^2. Sensible heat flux was -0.1664290873333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC1_2005-01-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0230", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.799, longitude -76.656. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.049615625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.362205 W/m^2. Vapor pressure deficit was -0.4627863636363636 kPa. Air pressure was 0.1298730769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4834449999999999 m/s. Wind direction was 0.179044861111111 decimal degrees. Relative humidity was 0.1171393 percent. Net radiation was -0.1881991316666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519451185714285 W/m^2. Outgoing longwave radiation was -0.2914403095238095 W/m^2. CO2 concentration was -0.2959175 μmol CO2/mol. Soil heat flux was -0.1686011783333333 W/m^2. Latent heat flux was -0.1643000716666666 W/m^2. Sensible heat flux was -0.1741238666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 8.75", + "(B) -6.93", + "(C) 3.18", + "(D) -1.26", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC3_2017-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0231", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.7879, longitude -75.9038. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.12421875 degrees Celsius. Incoming shortwave radiation was -0.18432175 W/m^2. Incoming longwave radiation was -0.328 W/m^2. Vapor pressure deficit was -0.3737181818181818 kPa. Air pressure was 0.117276923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48689 m/s. Wind direction was 0.5013371138888889 decimal degrees. Relative humidity was -0.0985 percent. Net radiation was -0.0299865999999999 W/m^2. Incoming photosynthetic photon flux density was 0.03 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4230952380952381 W/m^2. Outgoing longwave radiation was -0.2499047619047618 W/m^2. CO2 concentration was -0.2987899999999999 μmol CO2/mol. Soil heat flux was -0.1633993333333333 W/m^2. Latent heat flux was -0.1309052666666666 W/m^2. Sensible heat flux was -0.1186121666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.39", + "(B) 3.05", + "(C) 8.45", + "(D) -10.29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NC4_2015-04-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0232", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.1651, longitude -96.4766. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.161 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.29885 W/m^2. Vapor pressure deficit was -0.4927636363636363 kPa. Air pressure was 0.1011538461538461 kPa. Wind speed was -0.485 m/s. Wind direction was -0.2777777777777778 decimal degrees. Relative humidity was 0.4759999999999999 percent. Net radiation was -0.1809333333333333 W/m^2. Outgoing shortwave radiation was -0.4508571428571428 W/m^2. Outgoing longwave radiation was -0.2433809523809524 W/m^2. CO2 concentration was -0.1467375 μmol CO2/mol. Latent heat flux was -0.1675 W/m^2. Sensible heat flux was -0.1675666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.13", + "(B) 3.67", + "(C) 2.21", + "(D) 9.59", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ne1_2001-08-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0233", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 64.8618, longitude -163.7002. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10090625 degrees Celsius. Incoming shortwave radiation was -0.203 W/m^2. Incoming longwave radiation was -0.35325 W/m^2. Vapor pressure deficit was -0.3941363636363637 kPa. Air pressure was 0.1246346153846153 kPa. Wind speed was -0.47399 m/s. Wind direction was -0.8654068152836913 decimal degrees. Relative humidity was -0.1343 percent. Net radiation was -0.05045 W/m^2. Incoming photosynthetic photon flux density was -0.05484375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.406890625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4045 W/m^2. Outgoing longwave radiation was -0.2436666666666666 W/m^2. CO2 concentration was -0.30040075 μmol CO2/mol. Soil heat flux was -0.1666666666666666 W/m^2. Latent heat flux was -0.14281055 W/m^2. Sensible heat flux was -0.1154423333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.19", + "(B) 0.55", + "(C) 2.18", + "(D) -0.34", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NGC_2018-06-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0234", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.0329, longitude -105.5464. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0407499999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3701125 W/m^2. Vapor pressure deficit was -0.4705136363636364 kPa. Air pressure was -0.1061923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48305 m/s. Wind direction was 0.5747500000000002 decimal degrees. Relative humidity was 0.1656 percent. Net radiation was -0.1898116666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4508357142857143 W/m^2. Outgoing longwave radiation was -0.2905214285714286 W/m^2. CO2 concentration was -0.3100929999999999 μmol CO2/mol. Soil heat flux was -0.1678466666666666 W/m^2. Latent heat flux was -0.16618 W/m^2. Sensible heat flux was -0.1705924999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.48", + "(B) 0.26", + "(C) 3.2", + "(D) 0.25", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-NR1_2003-06-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0235", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.5545, longitude -83.8438. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.149721875 degrees Celsius. Incoming shortwave radiation was -0.133004 W/m^2. Incoming longwave radiation was -0.31916775 W/m^2. Vapor pressure deficit was -0.3542045454545454 kPa. Air pressure was 0.1055461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46391 m/s. Wind direction was -0.8450861111111111 decimal degrees. Relative humidity was -0.0386753460522179 percent. Net radiation was 0.0107656666666666 W/m^2. Incoming photosynthetic photon flux density was 0.0323808919999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4042374285714286 W/m^2. Outgoing longwave radiation was -0.2341142857142857 W/m^2. CO2 concentration was -0.317362 μmol CO2/mol. Soil heat flux was -0.1597925 W/m^2. Latent heat flux was -0.1631607366666666 W/m^2. Sensible heat flux was -0.0756271666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -5.9", + "(B) 1.63", + "(C) -1.39", + "(D) 1.35", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Oho_2004-05-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0236", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 27.3836, longitude -81.9509. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.118453125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3246555 W/m^2. Vapor pressure deficit was -0.4489272727272727 kPa. Air pressure was 0.1269538461538462 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.486565 m/s. Wind direction was -0.4746122222222222 decimal degrees. Relative humidity was 0.2444035999999999 percent. Net radiation was -0.1845981583333333 W/m^2. Incoming photosynthetic photon flux density was -0.437477818978125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522131160738095 W/m^2. Outgoing longwave radiation was -0.2615762857142857 W/m^2. CO2 concentration was -0.30147775 μmol CO2/mol. Soil heat flux was -0.1692966916666666 W/m^2. Latent heat flux was -0.1637063883333333 W/m^2. Sensible heat flux was -0.1726009966666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.69", + "(B) 5.69", + "(C) 6.35", + "(D) -1.89", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ONA_2016-04-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0237", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.0201, longitude -83.0183. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.147521875 degrees Celsius. Incoming shortwave radiation was -0.0417565 W/m^2. Incoming longwave radiation was -0.27452375 W/m^2. Vapor pressure deficit was -0.3352454545454545 kPa. Air pressure was 0.1069576923076923 kPa. Wind speed was -0.4916 m/s. Wind direction was -0.6922638888888889 decimal degrees. Relative humidity was -0.121655 percent. Net radiation was 0.0720999999999999 W/m^2. Incoming photosynthetic photon flux density was 0.1111874999999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3801428571428571 W/m^2. Outgoing longwave radiation was -0.2771095238095238 W/m^2. CO2 concentration was -0.313185 μmol CO2/mol. Latent heat flux was -0.0259925 W/m^2. Sensible heat flux was -0.134676 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.84", + "(B) -6.17", + "(C) -13.53", + "(D) 1.64", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-ORv_2011-08-11_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0238", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.3795, longitude -82.5125. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.163346875 degrees Celsius. Incoming shortwave radiation was -0.243 W/m^2. Vapor pressure deficit was -0.3722181818181818 kPa. Air pressure was 0.1174230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.49365 m/s. Wind direction was 0.8483888888888891 decimal degrees. Relative humidity was 0.08545 percent. Net radiation was -0.0312149999999999 W/m^2. Incoming photosynthetic photon flux density was -0.13446875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4407416666666666 W/m^2. CO2 concentration was -0.2979774999999999 μmol CO2/mol. Latent heat flux was -0.1393773333333333 W/m^2. Sensible heat flux was -0.14113 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.63", + "(B) -6.55", + "(C) 1.75", + "(D) -3.79", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-OWC_2016-09-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0239", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.0896, longitude -89.4158. This site belongs to the Water Bodies. type: The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15008125 degrees Celsius. Incoming shortwave radiation was -0.43690825 W/m^2. Incoming longwave radiation was -0.31801675 W/m^2. Vapor pressure deficit was -0.3794272727272727 kPa. Air pressure was 0.0991230769230768 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.442735 m/s. Wind direction was 0.8070661111111112 decimal degrees. Relative humidity was 0.0561408 percent. CO2 concentration was -0.30509125 μmol CO2/mol. Latent heat flux was -0.0763768333333333 W/m^2. Sensible heat flux was -0.16363386 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.07", + "(B) -1.03", + "(C) 0.57", + "(D) 0.24", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Pnp_2016-06-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0240", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 65.1237, longitude -147.4876. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.02450625 degrees Celsius. Incoming shortwave radiation was -0.4116185 W/m^2. Incoming longwave radiation was -0.36972475 W/m^2. Vapor pressure deficit was -0.4634545454545455 kPa. Air pressure was 0.0897461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48227 m/s. Wind direction was -0.84045 decimal degrees. Relative humidity was 0.003905 percent. Net radiation was -0.1473795 W/m^2. Incoming photosynthetic photon flux density was -0.3258934375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.41442765625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4267602380952381 W/m^2. Outgoing longwave radiation was -0.2973102380952381 W/m^2. CO2 concentration was -0.31122425 μmol CO2/mol. Soil heat flux was -0.1693688333333333 W/m^2. Latent heat flux was -0.16489151 W/m^2. Sensible heat flux was -0.1611376233333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.17", + "(B) 0.11", + "(C) 0.8", + "(D) 0.34", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Prr_2010-10-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0241", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 34.4159, longitude -91.6733. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.136675 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3012007499999999 W/m^2. Vapor pressure deficit was -0.4314818181818182 kPa. Air pressure was 0.1230384615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.471175 m/s. Wind direction was -0.4160916666666667 decimal degrees. Relative humidity was 0.2126949999999999 percent. Net radiation was -0.1746284666666666 W/m^2. Incoming photosynthetic photon flux density was -0.437507635421875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43751509375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4518937452380952 W/m^2. Outgoing longwave radiation was -0.252635 W/m^2. CO2 concentration was -0.28997575 μmol CO2/mol. Soil heat flux was -0.1649251333333333 W/m^2. Latent heat flux was -0.1592018 W/m^2. Sensible heat flux was -0.1750807333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.45", + "(B) 7.26", + "(C) -0.5", + "(D) 1.95", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGA_2021-05-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0242", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.5782, longitude -121.8579. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.06146875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.32957425 W/m^2. Vapor pressure deficit was -0.4880727272727272 kPa. Air pressure was 0.1269230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.489185 m/s. Wind direction was 0.0492358333333333 decimal degrees. Relative humidity was 0.3919665 percent. Net radiation was -0.1747124833333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375251718749999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43750966665625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519260469047619 W/m^2. Outgoing longwave radiation was -0.2796102380952381 W/m^2. CO2 concentration was -0.2754645 μmol CO2/mol. Soil heat flux was -0.1617525333333333 W/m^2. Latent heat flux was -0.1643407766666666 W/m^2. Sensible heat flux was -0.1662926521666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.36", + "(B) 2.13", + "(C) 0.91", + "(D) -24.37", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGB_2021-01-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0243", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.6805, longitude -122.0026. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1591031249999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3195235 W/m^2. Vapor pressure deficit was -0.3037318181818181 kPa. Air pressure was 0.1176923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.470425 m/s. Wind direction was -0.2806027777777777 decimal degrees. Relative humidity was -0.1624454999999999 percent. Net radiation was -0.1898000333333333 W/m^2. Incoming photosynthetic photon flux density was -0.43750554471875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375099818593749 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4516505404761904 W/m^2. Outgoing longwave radiation was -0.2500380952380952 W/m^2. CO2 concentration was -0.278394 μmol CO2/mol. Soil heat flux was -0.16616944 W/m^2. Latent heat flux was -0.1601007833333333 W/m^2. Sensible heat flux was -0.1837121833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 6.49", + "(B) 4.3", + "(C) 1.29", + "(D) -0.53", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-RGo_2021-06-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0244", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.1439, longitude -116.7356. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.051209375 degrees Celsius. Incoming shortwave radiation was -0.1033025 W/m^2. Incoming longwave radiation was -0.374851 W/m^2. Vapor pressure deficit was -0.4420136363636363 kPa. Air pressure was -0.008973076923077 kPa. Wind speed was -0.481235 m/s. Wind direction was 0.6649333333333333 decimal degrees. Relative humidity was -0.0860539462549999 percent. Net radiation was 0.0045896 W/m^2. Incoming photosynthetic photon flux density was 0.06375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.397221330952381 W/m^2. Outgoing longwave radiation was -0.2551956452380953 W/m^2. CO2 concentration was -0.3039175 μmol CO2/mol. Soil heat flux was -0.1197221666666666 W/m^2. Latent heat flux was -0.1066194999999999 W/m^2. Sensible heat flux was -0.1026315 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.06", + "(B) 1.21", + "(C) -7.42", + "(D) 2.31", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rls_2015-04-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0245", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.0645, longitude -116.7486. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.032615625 degrees Celsius. Incoming shortwave radiation was -0.14775 W/m^2. Incoming longwave radiation was -0.365125 W/m^2. Vapor pressure deficit was -0.4593818181818181 kPa. Air pressure was -0.0517153846153846 kPa. Wind speed was -0.4619 m/s. Wind direction was 0.8257916666666669 decimal degrees. Relative humidity was -0.0036928023349999 percent. Net radiation was 0.0055049999999999 W/m^2. Incoming photosynthetic photon flux density was 0.0040625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.417697619047619 W/m^2. Outgoing longwave radiation was -0.2690952380952381 W/m^2. CO2 concentration was -0.30397575 μmol CO2/mol. Soil heat flux was -0.1434805833333333 W/m^2. Latent heat flux was -0.1408842166666666 W/m^2. Sensible heat flux was -0.0551459999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.99", + "(B) -5.37", + "(C) 4.98", + "(D) 1.93", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rms_2015-05-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0246", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.7143, longitude -93.0898. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.067728125 degrees Celsius. Incoming shortwave radiation was -0.2317577499999999 W/m^2. Incoming longwave radiation was -0.3655615 W/m^2. Vapor pressure deficit was -0.4536954545454545 kPa. Air pressure was 0.1169115384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.483785 m/s. Wind direction was -0.5830916666666667 decimal degrees. Relative humidity was 0.1082907 percent. Net radiation was -0.0571875166666666 W/m^2. Incoming photosynthetic photon flux density was -0.1070892574999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4053085666666666 W/m^2. Outgoing longwave radiation was -0.2723468333333333 W/m^2. CO2 concentration was -0.30386275 μmol CO2/mol. Soil heat flux was -0.1724639166666666 W/m^2. Latent heat flux was -0.1507404333333333 W/m^2. Sensible heat flux was -0.1139613333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.12", + "(B) 0.03", + "(C) -1.41", + "(D) -0.09", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro1_2015-10-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0247", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.7288, longitude -93.0888. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.163634375 degrees Celsius. Incoming shortwave radiation was -0.2178625 W/m^2. Incoming longwave radiation was -0.3129255 W/m^2. Vapor pressure deficit was -0.3562454545454545 kPa. Air pressure was 0.0953346153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.442535 m/s. Wind direction was -0.0221894444444444 decimal degrees. Relative humidity was 0.0347339 percent. Net radiation was -0.0464075666666666 W/m^2. Incoming photosynthetic photon flux density was -0.0787350307812499 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3902603095238095 W/m^2. Outgoing longwave radiation was -0.2394317857142857 W/m^2. CO2 concentration was -0.30812525 μmol CO2/mol. Soil heat flux was -0.1483866499999999 W/m^2. Latent heat flux was -0.0837138333333333 W/m^2. Sensible heat flux was -0.1753432333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.35", + "(B) 1.99", + "(C) 1.02", + "(D) -10.77", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro2_2015-09-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0248", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.6781, longitude -93.0723. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.16998125 degrees Celsius. Incoming shortwave radiation was -0.1995045 W/m^2. Incoming longwave radiation was -0.312171 W/m^2. Vapor pressure deficit was -0.3377727272727273 kPa. Air pressure was 0.0953346153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46249 m/s. Wind direction was 0.0380793 decimal degrees. Relative humidity was 0.0053825499999999 percent. Net radiation was -0.0270194666666666 W/m^2. Incoming photosynthetic photon flux density was -0.0787350307812499 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4056697904761905 W/m^2. Outgoing longwave radiation was -0.2335170952380952 W/m^2. CO2 concentration was -0.30461875 μmol CO2/mol. Soil heat flux was -0.1604020333333333 W/m^2. Latent heat flux was -0.1058373333333333 W/m^2. Sensible heat flux was -0.1285385 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -6.56", + "(B) -0.04", + "(C) 2.07", + "(D) 3.63", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro4_2015-09-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0249", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.691, longitude -93.0576. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0049125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.38935025 W/m^2. Vapor pressure deficit was -0.4780636363636364 kPa. Air pressure was 0.1013153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4724049999999999 m/s. Wind direction was 0.4932691666666667 decimal degrees. Relative humidity was 0.0819346999999999 percent. Net radiation was -0.1969618566666666 W/m^2. Incoming photosynthetic photon flux density was -0.437257811153125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4513280907142857 W/m^2. Outgoing longwave radiation was -0.3065088809523809 W/m^2. CO2 concentration was -0.2963535 μmol CO2/mol. Soil heat flux was -0.1669994728333333 W/m^2. Latent heat flux was -0.1583388833333333 W/m^2. Sensible heat flux was -0.1719826166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 8.53", + "(B) -0.01", + "(C) 0.18", + "(D) 0.43", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro5_2017-02-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0250", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.6946, longitude -93.0578. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0618781249999999 degrees Celsius. Incoming shortwave radiation was -0.39258075 W/m^2. Incoming longwave radiation was -0.3361854999999999 W/m^2. Vapor pressure deficit was -0.4716909090909091 kPa. Air pressure was 0.0921461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.488765 m/s. Wind direction was -0.50390975 decimal degrees. Relative humidity was 0.2447930999999999 percent. Net radiation was -0.1160133075666666 W/m^2. Incoming photosynthetic photon flux density was -0.292582546875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4436645277166666 W/m^2. Outgoing longwave radiation was -0.2751414285714286 W/m^2. CO2 concentration was -0.2969855 μmol CO2/mol. Soil heat flux was -0.1651518463333333 W/m^2. Latent heat flux was -0.1492609 W/m^2. Sensible heat flux was -0.1592448166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.36", + "(B) -4.11", + "(C) -0.01", + "(D) 0.62", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ro6_2017-02-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0251", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 65.1198, longitude -147.429. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0065625 degrees Celsius. Incoming shortwave radiation was -0.49761725 W/m^2. Incoming longwave radiation was -0.3878954999999999 W/m^2. Vapor pressure deficit was -0.4699772727272727 kPa. Air pressure was 0.0905923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.488135 m/s. Wind direction was -0.1091417499999999 decimal degrees. Relative humidity was -0.08325 percent. Net radiation was -0.1771554075758333 W/m^2. Incoming photosynthetic photon flux density was -0.43539985616875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.435975625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4499672868173809 W/m^2. Outgoing longwave radiation was -0.3295950154523809 W/m^2. CO2 concentration was -0.2940475 μmol CO2/mol. Soil heat flux was -0.1668883461666666 W/m^2. Latent heat flux was -0.166235945 W/m^2. Sensible heat flux was -0.171529 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.46", + "(B) -1.97", + "(C) 0.63", + "(D) 0.9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rpf_2013-04-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0252", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.0653, longitude -116.7591. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1058437499999999 degrees Celsius. Incoming shortwave radiation was -0.108975 W/m^2. Incoming longwave radiation was -0.37475 W/m^2. Vapor pressure deficit was -0.3535681818181818 kPa. Air pressure was -0.0407038461538462 kPa. Wind speed was -0.4628949999999999 m/s. Wind direction was 0.1731329583333332 decimal degrees. Relative humidity was -0.33445 percent. Net radiation was -0.0385499999999999 W/m^2. Outgoing shortwave radiation was -0.3842380952380952 W/m^2. Outgoing longwave radiation was -0.2118571428571428 W/m^2. CO2 concentration was -0.32294825 μmol CO2/mol. Soil heat flux was -0.140235 W/m^2. Latent heat flux was -0.151931 W/m^2. Sensible heat flux was -0.0992424999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.39", + "(B) 2.38", + "(C) -2.63", + "(D) -3.86", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwe_2005-09-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0253", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.1207, longitude -116.7231. This site belongs to the Closed Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.04475625 degrees Celsius. Incoming shortwave radiation was -0.04953625 W/m^2. Incoming longwave radiation was -0.380745 W/m^2. Vapor pressure deficit was -0.4438727272727272 kPa. Air pressure was -0.0261461538461538 kPa. Wind speed was -0.4765149999999999 m/s. Wind direction was 0.832288888888889 decimal degrees. Relative humidity was -0.108936471755 percent. Net radiation was 0.0274921316666666 W/m^2. Incoming photosynthetic photon flux density was 0.1359375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3859947 W/m^2. Outgoing longwave radiation was -0.2535477023809523 W/m^2. CO2 concentration was -0.297798 μmol CO2/mol. Soil heat flux was -0.1564059 W/m^2. Latent heat flux was -0.125303 W/m^2. Sensible heat flux was -0.0723193333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.23", + "(B) -0.88", + "(C) 1.6", + "(D) -0.14", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rwf_2015-04-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0254", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 43.1675, longitude -116.7132. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.044475 degrees Celsius. Incoming shortwave radiation was -0.27586675 W/m^2. Incoming longwave radiation was -0.38436375 W/m^2. Vapor pressure deficit was -0.4471909090909091 kPa. Air pressure was 0.0097076923076923 kPa. Wind speed was -0.47428 m/s. Wind direction was 0.6353222222222222 decimal degrees. Relative humidity was -0.07452652866 percent. Net radiation was -0.091232265 W/m^2. Incoming photosynthetic photon flux density was -0.114375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4191259309523809 W/m^2. Outgoing longwave radiation was -0.2698093809523809 W/m^2. CO2 concentration was -0.30371475 μmol CO2/mol. Soil heat flux was -0.15097765 W/m^2. Latent heat flux was -0.1366616 W/m^2. Sensible heat flux was -0.1333704166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.15", + "(B) 0.57", + "(C) 1.91", + "(D) -3.69", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Rws_2015-04-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0255", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 34.3623, longitude -106.702. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1106999999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3064905 W/m^2. Vapor pressure deficit was -0.4781954545454545 kPa. Air pressure was -0.0055499999999999 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4697449999999999 m/s. Wind direction was -0.1140120555555556 decimal degrees. Relative humidity was 0.38168785 percent. Net radiation was -0.1725637678333333 W/m^2. Incoming photosynthetic photon flux density was -0.4374175883859375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519561991071428 W/m^2. Outgoing longwave radiation was -0.26008645 W/m^2. CO2 concentration was -0.30071325 μmol CO2/mol. Latent heat flux was -0.1648926266666666 W/m^2. Sensible heat flux was -0.17168835 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.15", + "(B) 0.1", + "(C) 0.05", + "(D) 0.21", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Seg_2008-08-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0256", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 34.3349, longitude -106.7442. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.02515 degrees Celsius. Incoming shortwave radiation was -0.2331875 W/m^2. Incoming longwave radiation was -0.371936 W/m^2. Vapor pressure deficit was -0.4551454545454546 kPa. Air pressure was -0.0071269230769231 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.495255 m/s. Wind direction was 0.8458489722222222 decimal degrees. Relative humidity was -0.1039231 percent. Net radiation was -0.0612598183333333 W/m^2. Incoming photosynthetic photon flux density was -0.1299354328124999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4040105192857143 W/m^2. Outgoing longwave radiation was -0.2752597261904762 W/m^2. CO2 concentration was -0.29989975 μmol CO2/mol. Latent heat flux was -0.15995065 W/m^2. Sensible heat flux was -0.1188436666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.74", + "(B) 0.1", + "(C) -0.0", + "(D) -0.0", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ses_2007-11-27_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0257", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.0369, longitude -121.7547. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08303125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.34792925 W/m^2. Vapor pressure deficit was -0.4651409090909091 kPa. Air pressure was 0.1273076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.457215 m/s. Wind direction was 0.4001914472222222 decimal degrees. Relative humidity was 0.2489500000000001 percent. Net radiation was -0.192561329 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452128499047619 W/m^2. Outgoing longwave radiation was -0.2744880961904761 W/m^2. CO2 concentration was -0.295849 μmol CO2/mol. Soil heat flux was -0.1743307999999999 W/m^2. Latent heat flux was -0.1617022666666666 W/m^2. Sensible heat flux was -0.1816590166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.59", + "(B) 0.46", + "(C) -0.15", + "(D) 6.29", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sne_2016-05-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0258", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.0402, longitude -121.7272. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.10734375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.34088475 W/m^2. Vapor pressure deficit was -0.4652363636363636 kPa. Air pressure was 0.1234807692307691 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.450645 m/s. Wind direction was 0.4196476222222222 decimal degrees. Relative humidity was 0.305 percent. Net radiation was -0.192626158 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522222221428572 W/m^2. Outgoing longwave radiation was -0.2655061164285714 W/m^2. CO2 concentration was -0.2909817499999999 μmol CO2/mol. Soil heat flux was -0.1707243166666666 W/m^2. Latent heat flux was -0.166959915 W/m^2. Sensible heat flux was -0.1786666333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -12.21", + "(B) 6.72", + "(C) -0.61", + "(D) -0.14", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Snf_2018-07-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0259", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.9083, longitude -110.8395. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.157 degrees Celsius. Incoming shortwave radiation was -0.09885325 W/m^2. Incoming longwave radiation was -0.3437287499999999 W/m^2. Vapor pressure deficit was -0.2336 kPa. Air pressure was 0.0361307692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.44986 m/s. Wind direction was 0.4431472222222222 decimal degrees. Relative humidity was -0.4182 percent. Net radiation was -0.0201851666666666 W/m^2. Outgoing shortwave radiation was -0.3799973809523809 W/m^2. Outgoing longwave radiation was -0.2031490476190476 W/m^2. CO2 concentration was -0.30886675 μmol CO2/mol. Soil heat flux was -0.13918 W/m^2. Latent heat flux was -0.1607075 W/m^2. Sensible heat flux was -0.0910126666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRC_2008-03-14_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0260", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.7894, longitude -110.8277. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.028965625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.383697 W/m^2. Vapor pressure deficit was -0.4488227272727272 kPa. Air pressure was 0.0194807692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.481345 m/s. Wind direction was -0.2708333333333333 decimal degrees. Relative humidity was -0.1593095 percent. Net radiation was -0.19638115 W/m^2. Incoming photosynthetic photon flux density was -0.4375082031249999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375133125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4513573333333333 W/m^2. Outgoing longwave radiation was -0.3012849047619048 W/m^2. CO2 concentration was -0.30212325 μmol CO2/mol. Soil heat flux was -0.1881990333333333 W/m^2. Latent heat flux was -0.1665489833333333 W/m^2. Sensible heat flux was -0.1722407166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.56", + "(B) -0.19", + "(C) -0.04", + "(D) 0.21", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRG_2009-04-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0261", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.8214, longitude -110.8661. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1205 degrees Celsius. Incoming shortwave radiation was -0.1842999999999999 W/m^2. Incoming longwave radiation was -0.3505 W/m^2. Vapor pressure deficit was -0.3350909090909091 kPa. Air pressure was 0.0318884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.481765 m/s. Wind direction was 0.8466666666666666 decimal degrees. Relative humidity was -0.31093 percent. Net radiation was -0.0354333333333332 W/m^2. Incoming photosynthetic photon flux density was -0.0387624999999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.396453125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4099047619047619 W/m^2. Outgoing longwave radiation was -0.2392857142857143 W/m^2. CO2 concentration was -0.31175075 μmol CO2/mol. Soil heat flux was -0.1204538333333333 W/m^2. Latent heat flux was -0.156795 W/m^2. Sensible heat flux was -0.0934828333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.25", + "(B) 0.18", + "(C) -0.03", + "(D) 0.97", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRM_2004-01-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0262", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.2006, longitude -122.0264. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0828 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.349164 W/m^2. Vapor pressure deficit was -0.4561636363636363 kPa. Air pressure was 0.1343846153846153 kPa. Wind speed was -0.4893849999999999 m/s. Wind direction was 0.3077353777777778 decimal degrees. Relative humidity was 0.18345 percent. Net radiation was -0.1831587333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4370283562499999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4376030515625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4516219761904762 W/m^2. Outgoing longwave radiation was -0.2865634376190475 W/m^2. CO2 concentration was -0.29643325 μmol CO2/mol. Soil heat flux was -0.1646961416666666 W/m^2. Latent heat flux was -0.1672597266666666 W/m^2. Sensible heat flux was -0.1654574866666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.68", + "(B) 4.2", + "(C) 2.06", + "(D) -3.83", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Srr_2016-03-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0263", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.8173, longitude -110.8508. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.12475 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Vapor pressure deficit was -0.3346272727272727 kPa. Air pressure was 0.0276923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.469025 m/s. Wind direction was -0.5042158333333333 decimal degrees. Relative humidity was -0.2795499999999999 percent. Net radiation was -0.18517 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. CO2 concentration was -0.30703725 μmol CO2/mol. Soil heat flux was -0.17445385 W/m^2. Latent heat flux was -0.1666479306 W/m^2. Sensible heat flux was -0.1752912499999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.49", + "(B) 0.08", + "(C) -3.86", + "(D) -2.67", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-SRS_2011-06-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0264", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.3966, longitude -106.8024. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.035059375 degrees Celsius. Incoming shortwave radiation was -0.481695 W/m^2. Vapor pressure deficit was -0.4518636363636363 kPa. Air pressure was -0.0561538461538462 kPa. Wind speed was -0.434855 m/s. Wind direction was 0.7222944444444447 decimal degrees. Relative humidity was -0.0812299999999999 percent. Incoming photosynthetic photon flux density was -0.41549890625 μmol Photon/m^2/s. CO2 concentration was -0.3075645 μmol CO2/mol. Soil heat flux was -0.1725102999999999 W/m^2. Latent heat flux was -0.1565483333333333 W/m^2. Sensible heat flux was -0.1812443333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.55", + "(B) -0.8", + "(C) -0.18", + "(D) 0.37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Sta_2005-11-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0265", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.0882, longitude -75.4372. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0028125 degrees Celsius. Incoming shortwave radiation was -0.464549 W/m^2. Vapor pressure deficit was -0.4841363636363636 kPa. Air pressure was 0.1299461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48258 m/s. Wind direction was 0.5469313019444444 decimal degrees. Relative humidity was 0.205 percent. Net radiation was -0.1498550522766666 W/m^2. Incoming photosynthetic photon flux density was -0.394890625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.40414583959375 μmol Photon/m^2/s. CO2 concentration was -0.3065625 μmol CO2/mol. Latent heat flux was -0.164306106 W/m^2. Sensible heat flux was -0.1647005883333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.23", + "(B) -10.03", + "(C) -16.95", + "(D) 0.39", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-StJ_2015-01-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0266", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.242, longitude -89.3477. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.114384375 degrees Celsius. Incoming shortwave radiation was -0.1893764999999999 W/m^2. Incoming longwave radiation was -0.302507 W/m^2. Vapor pressure deficit was -0.4610863636363636 kPa. Air pressure was 0.0742884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4710049999999999 m/s. Wind direction was 0.9120224999999998 decimal degrees. Relative humidity was 0.29729445 percent. Net radiation was -0.0141601 W/m^2. Incoming photosynthetic photon flux density was -0.064154375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4039040476190476 W/m^2. Outgoing longwave radiation was -0.2528314285714286 W/m^2. CO2 concentration was -0.312845 μmol CO2/mol. Latent heat flux was -0.1289688 W/m^2. Sensible heat flux was -0.1210726666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -22.02", + "(B) 0.29", + "(C) 0.37", + "(D) 1.81", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Syv_2014-06-24_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0267", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.4309, longitude -120.966. This site belongs to the Woody Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 30-60%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0564374999999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3711065 W/m^2. Vapor pressure deficit was -0.44125 kPa. Air pressure was 0.1138461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47652 m/s. Wind direction was -0.3638222222222222 decimal degrees. Relative humidity was -0.0612999999999999 percent. Net radiation was -0.1829256666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.3000647619047619 W/m^2. CO2 concentration was -0.2993685 μmol CO2/mol. Soil heat flux was -0.1736861666666666 W/m^2. Latent heat flux was -0.1665725008333333 W/m^2. Sensible heat flux was -0.1716948333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.28", + "(B) 0.82", + "(C) -1.42", + "(D) 1.66", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Ton_2014-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0268", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1074, longitude -121.6469. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.112 degrees Celsius. Incoming shortwave radiation was -0.1335225 W/m^2. Incoming longwave radiation was -0.3418272499999999 W/m^2. Vapor pressure deficit was -0.4205454545454545 kPa. Air pressure was 0.1321923076923077 kPa. Wind speed was -0.45694 m/s. Wind direction was 0.3783246916666666 decimal degrees. Relative humidity was 0.074655 percent. Net radiation was 0.00534615 W/m^2. Incoming photosynthetic photon flux density was 0.0116093748437499 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.402015625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4044971428571428 W/m^2. Outgoing longwave radiation was -0.2463305966666666 W/m^2. CO2 concentration was -0.3100104999999999 μmol CO2/mol. Latent heat flux was -0.1462080333333333 W/m^2. Sensible heat flux was -0.0526486666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 3.92", + "(B) -0.08", + "(C) -1.57", + "(D) -11.29", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw1_2011-04-11_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0269", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.0969, longitude -121.6365. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1006937499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3367615 W/m^2. Vapor pressure deficit was -0.4670272727272727 kPa. Air pressure was 0.1292307692307692 kPa. Wind speed was -0.411375 m/s. Wind direction was 0.4471111111111112 decimal degrees. Relative humidity was 0.302 percent. Net radiation was -0.1885146666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522378571428571 W/m^2. Outgoing longwave radiation was -0.2674364285714286 W/m^2. CO2 concentration was -0.30765625 μmol CO2/mol. Soil heat flux was -0.170848 W/m^2. Latent heat flux was -0.1681003333333333 W/m^2. Sensible heat flux was -0.1785148333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.16", + "(B) 3.38", + "(C) 0.68", + "(D) -30.8", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw2_2012-05-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0270", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1152, longitude -121.6469. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1125624999999999 degrees Celsius. Incoming shortwave radiation was -0.00940625 W/m^2. Incoming longwave radiation was -0.3470765 W/m^2. Vapor pressure deficit was -0.434 kPa. Air pressure was 0.1277961538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.434405 m/s. Wind direction was 0.434562725 decimal degrees. Relative humidity was 0.1486000000000001 percent. Net radiation was 0.0585578536666666 W/m^2. Incoming photosynthetic photon flux density was 0.1670138889062499 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.421842243125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3562063492857143 W/m^2. Outgoing longwave radiation was -0.2511709285714285 W/m^2. CO2 concentration was -0.2988485 μmol CO2/mol. Soil heat flux was -0.1586141333333333 W/m^2. Latent heat flux was -0.0622501666666666 W/m^2. Sensible heat flux was -0.1092158333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.72", + "(B) 1.02", + "(C) -28.71", + "(D) 6.25", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw3_2017-05-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0271", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1027, longitude -121.6413. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.08925 degrees Celsius. Incoming shortwave radiation was -0.26936275 W/m^2. Incoming longwave radiation was -0.3441835 W/m^2. Vapor pressure deficit was -0.3941136363636363 kPa. Air pressure was 0.1225692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.3959749999999999 m/s. Wind direction was 0.9308087305555558 decimal degrees. Relative humidity was -0.21525 percent. Net radiation was -0.0681067596666666 W/m^2. Incoming photosynthetic photon flux density was -0.193668655 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3727827051562499 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4101715685714286 W/m^2. Outgoing longwave radiation was -0.2673389385714286 W/m^2. CO2 concentration was -0.30555975 μmol CO2/mol. Soil heat flux was -0.1558469999999999 W/m^2. Latent heat flux was -0.1101654999999999 W/m^2. Sensible heat flux was -0.1457341166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.81", + "(B) -6.05", + "(C) -18.85", + "(D) 1.24", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw4_2013-12-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0272", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1072, longitude -121.6426. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.07878125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.34281575 W/m^2. Vapor pressure deficit was -0.4636 kPa. Air pressure was 0.1289461538461538 kPa. Wind speed was -0.4474 m/s. Wind direction was 0.4109596444444444 decimal degrees. Relative humidity was 0.2257499999999999 percent. Net radiation was -0.1877549843333333 W/m^2. Incoming photosynthetic photon flux density was -0.43767523375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519267545238095 W/m^2. Outgoing longwave radiation was -0.2737522035714285 W/m^2. CO2 concentration was -0.301817 μmol CO2/mol. Latent heat flux was -0.15505905 W/m^2. Sensible heat flux was -0.1788988333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -2.37", + "(B) 1.45", + "(C) -11.98", + "(D) -3.17", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Tw5_2018-05-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0273", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.1087, longitude -121.6531. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1860656249999999 degrees Celsius. Incoming shortwave radiation was -0.11998 W/m^2. Vapor pressure deficit was -0.2094545454545454 kPa. Air pressure was 0.1223846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.450845 m/s. Wind direction was 0.3685277777777778 decimal degrees. Relative humidity was -0.262785 percent. Net radiation was -0.0132545 W/m^2. Incoming photosynthetic photon flux density was 0.0880734375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.39982359375 μmol Photon/m^2/s. CO2 concentration was -0.30763575 μmol CO2/mol. Soil heat flux was -0.1492328333333333 W/m^2. Latent heat flux was -0.1092978333333333 W/m^2. Sensible heat flux was -0.0979665 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.07", + "(B) 1.32", + "(C) 4.25", + "(D) 6.21", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Twt_2009-05-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0274", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.5686, longitude -84.6707. This site belongs to the Water Bodies. type: The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1266624999999999 degrees Celsius. Incoming shortwave radiation was -0.12008 W/m^2. Incoming longwave radiation was -0.334805 W/m^2. Vapor pressure deficit was -0.3385909090909091 kPa. Air pressure was 0.1039923076923077 kPa. Wind speed was -0.470165 m/s. Wind direction was -0.7148138888888889 decimal degrees. Relative humidity was -0.24674 percent. Outgoing shortwave radiation was -0.4322542857142857 W/m^2. Outgoing longwave radiation was -0.2564714285714285 W/m^2. CO2 concentration was -0.30554 μmol CO2/mol. Latent heat flux was -0.1317926666666666 W/m^2. Sensible heat flux was -0.1729738333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.66", + "(B) 1.01", + "(C) 0.88", + "(D) 0.19", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UM3_2013-06-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0275", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.5598, longitude -84.7138. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.04409375 degrees Celsius. Incoming shortwave radiation was -0.49992025 W/m^2. Incoming longwave radiation was -0.3367624999999999 W/m^2. Vapor pressure deficit was -0.495340909090909 kPa. Air pressure was 0.09 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.44786 m/s. Wind direction was 0.2235833333333333 decimal degrees. Relative humidity was 0.4492799999999999 percent. Net radiation was -0.1724233333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4369556875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4524485376190476 W/m^2. Outgoing longwave radiation was -0.2885928571428571 W/m^2. CO2 concentration was -0.3041524999999999 μmol CO2/mol. Latent heat flux was -0.16900465 W/m^2. Sensible heat flux was -0.18054125 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.18", + "(B) 0.25", + "(C) 0.07", + "(D) 0.69", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMB_2007-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0276", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.5625, longitude -84.6975. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0703812499999999 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3551375 W/m^2. Vapor pressure deficit was -0.4674863636363636 kPa. Air pressure was 0.1097923076923076 kPa. Wind speed was -0.472415 m/s. Wind direction was 0.8021111111111111 decimal degrees. Relative humidity was 0.23236 percent. Net radiation was -0.195072 W/m^2. Incoming photosynthetic photon flux density was -0.4374946875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4516811904761904 W/m^2. Outgoing longwave radiation was -0.2764642857142857 W/m^2. CO2 concentration was -0.3059199999999999 μmol CO2/mol. Latent heat flux was -0.1674498333333333 W/m^2. Sensible heat flux was -0.1825023333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.37", + "(B) 0.32", + "(C) 0.77", + "(D) 3.75", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-UMd_2010-07-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0277", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.4133, longitude -120.9508. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0528125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.324405 W/m^2. Vapor pressure deficit was -0.4998 kPa. Air pressure was 0.1061538461538461 kPa. Precipitation was recorded at -0.48984 mm. Wind speed was -0.47494 m/s. Wind direction was -0.514888888888889 decimal degrees. Relative humidity was 0.498 percent. Net radiation was -0.1745258333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2840023809523809 W/m^2. CO2 concentration was -0.30554525 μmol CO2/mol. Soil heat flux was -0.16982275 W/m^2. Latent heat flux was -0.16190375 W/m^2. Sensible heat flux was -0.17251715 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.75", + "(B) 0.37", + "(C) 2.5", + "(D) 1.65", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Var_2004-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0278", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.8884, longitude -106.5321. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.073203125 degrees Celsius. Incoming shortwave radiation was -0.35407625 W/m^2. Incoming longwave radiation was -0.3645449999999999 W/m^2. Vapor pressure deficit was -0.4252863636363636 kPa. Air pressure was -0.1057961538461538 kPa. Precipitation was recorded at -0.4908133333333333 mm. Wind speed was -0.45911 m/s. Wind direction was -0.1148866944444444 decimal degrees. Relative humidity was -0.0968842 percent. Net radiation was -0.1086655415 W/m^2. Incoming photosynthetic photon flux density was -0.2757584125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4431062023809524 W/m^2. Outgoing longwave radiation was -0.2765347904761905 W/m^2. CO2 concentration was -0.31010525 μmol CO2/mol. Latent heat flux was -0.1495961999999999 W/m^2. Sensible heat flux was -0.1370089833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.0", + "(B) 1.38", + "(C) -0.07", + "(D) 0.9", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcm_2010-10-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0279", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.8642, longitude -106.5967. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.144809375 degrees Celsius. Incoming shortwave radiation was -0.26367425 W/m^2. Incoming longwave radiation was -0.325947 W/m^2. Vapor pressure deficit was -0.3175318181818182 kPa. Air pressure was -0.0688615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.480485 m/s. Wind direction was 0.1904989999999999 decimal degrees. Relative humidity was -0.2069129999999999 percent. Net radiation was -0.0513488866666666 W/m^2. Incoming photosynthetic photon flux density was -0.151199715625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4351628309523809 W/m^2. Outgoing longwave radiation was -0.2435017833333333 W/m^2. CO2 concentration was -0.31084 μmol CO2/mol. Latent heat flux was -0.0838568333333333 W/m^2. Sensible heat flux was -0.1457970333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 6.74", + "(B) 1.49", + "(C) 1.96", + "(D) -3.42", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Vcp_2010-08-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0280", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.7438, longitude -110.0522. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.14634375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3320315 W/m^2. Vapor pressure deficit was -0.2893136363636364 kPa. Air pressure was 0.0100615384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.486695 m/s. Wind direction was -0.8095194444444445 decimal degrees. Relative humidity was -0.302019 percent. Net radiation was -0.1969 W/m^2. Incoming photosynthetic photon flux density was -0.437769015625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4372121874999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4510747619047618 W/m^2. Outgoing longwave radiation was -0.2551428571428571 W/m^2. CO2 concentration was -0.31027275 μmol CO2/mol. Soil heat flux was -0.1843840833333333 W/m^2. Latent heat flux was -0.16674635 W/m^2. Sensible heat flux was -0.1697382 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.57", + "(B) 0.63", + "(C) 0.16", + "(D) -1.64", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Whs_2009-09-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0281", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6188, longitude -91.0814. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.10386875 degrees Celsius. Incoming shortwave radiation was -0.37532675 W/m^2. Vapor pressure deficit was -0.48715 kPa. Air pressure was 0.1041846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47013 m/s. Wind direction was -0.8008972222222221 decimal degrees. Relative humidity was -0.34942 percent. Net radiation was -0.0714871666666666 W/m^2. Incoming photosynthetic photon flux density was -0.2876525 μmol Photon/m^2/s. CO2 concentration was -0.3168265 μmol CO2/mol. Soil heat flux was -0.1667003333333333 W/m^2. Latent heat flux was -0.155941 W/m^2. Sensible heat flux was -0.120789 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -4.01", + "(B) -2.16", + "(C) 1.01", + "(D) -3.37", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi0_2002-04-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0282", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7305, longitude -91.2329. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.031634375 degrees Celsius. Incoming shortwave radiation was -0.499987 W/m^2. Vapor pressure deficit was -0.4675772727272727 kPa. Air pressure was 0.1049653846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4926299999999999 m/s. Wind direction was -0.0282194444444444 decimal degrees. Relative humidity was 0.0929899999999999 percent. Net radiation was -0.1817208333333333 W/m^2. Incoming photosynthetic photon flux density was -0.43748421875 μmol Photon/m^2/s. CO2 concentration was -0.2895645 μmol CO2/mol. Soil heat flux was -0.1700635 W/m^2. Latent heat flux was -0.1666891666666666 W/m^2. Sensible heat flux was -0.1676826666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 32.18", + "(B) 4.31", + "(C) -12.73", + "(D) 1.84", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi1_2003-05-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0283", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6869, longitude -91.1528. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.147925 degrees Celsius. Incoming shortwave radiation was -0.1311522499999999 W/m^2. Vapor pressure deficit was -0.3260909090909091 kPa. Air pressure was 0.0936461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4870049999999999 m/s. Wind direction was -0.059225 decimal degrees. Relative humidity was -0.15143 percent. Net radiation was 0.0384011666666666 W/m^2. Incoming photosynthetic photon flux density was 0.0058265624999999 μmol Photon/m^2/s. CO2 concentration was -0.3301984999999999 μmol CO2/mol. Soil heat flux was -0.1608541666666666 W/m^2. Latent heat flux was -0.1437125 W/m^2. Sensible heat flux was -0.056625 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -5.28", + "(B) 2.08", + "(C) 1.23", + "(D) -15.3", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi2_2003-09-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0284", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6347, longitude -91.0987. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.03965625 degrees Celsius. Incoming shortwave radiation was -0.25332825 W/m^2. Vapor pressure deficit was -0.4477409090909091 kPa. Air pressure was 0.0978423076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4658899999999999 m/s. Wind direction was -0.4181388888888889 decimal degrees. Relative humidity was -0.0998749999999999 percent. Net radiation was 0.0572553333333333 W/m^2. Incoming photosynthetic photon flux density was -0.1410193749999999 μmol Photon/m^2/s. CO2 concentration was -0.31531775 μmol CO2/mol. Soil heat flux was -0.1610033333333333 W/m^2. Latent heat flux was -0.161905 W/m^2. Sensible heat flux was -0.0316108333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi3_2002-05-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0285", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7393, longitude -91.1663. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0415843749999999 degrees Celsius. Incoming shortwave radiation was -0.4781162499999999 W/m^2. Vapor pressure deficit was -0.4389727272727272 kPa. Air pressure was 0.09225 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47485 m/s. Wind direction was -0.1929083333333333 decimal degrees. Relative humidity was -0.1859899999999999 percent. Net radiation was -0.1016223333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4111971874999999 μmol Photon/m^2/s. CO2 concentration was -0.317859 μmol CO2/mol. Soil heat flux was -0.1655783333333333 W/m^2. Latent heat flux was -0.153305 W/m^2. Sensible heat flux was -0.1450015 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.56", + "(B) -11.18", + "(C) 3.78", + "(D) -3.28", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi4_2002-05-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0286", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6531, longitude -91.0858. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.052059375 degrees Celsius. Incoming shortwave radiation was -0.35155975 W/m^2. Vapor pressure deficit was -0.4626318181818181 kPa. Air pressure was 0.100226923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4752349999999999 m/s. Wind direction was -0.4246222222222222 decimal degrees. Relative humidity was 0.12591 percent. Net radiation was -0.1240906666666666 W/m^2. Incoming photosynthetic photon flux density was -0.25908640625 μmol Photon/m^2/s. CO2 concentration was -0.31895625 μmol CO2/mol. Latent heat flux was -0.1513586666666666 W/m^2. Sensible heat flux was -0.1544935 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.97", + "(B) -13.88", + "(C) 0.14", + "(D) 0.53", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi5_2004-05-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0287", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6249, longitude -91.2982. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.026225 degrees Celsius. Incoming shortwave radiation was -0.4801877499999999 W/m^2. Vapor pressure deficit was -0.4901363636363636 kPa. Air pressure was 0.0923692307692307 kPa. Precipitation was recorded at -0.498 mm. Wind speed was -0.45159 m/s. Wind direction was -0.801413888888889 decimal degrees. Relative humidity was 0.3684999999999999 percent. Net radiation was -0.1493316666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4136871875 μmol Photon/m^2/s. CO2 concentration was -0.306532 μmol CO2/mol. Soil heat flux was -0.1687122533333333 W/m^2. Latent heat flux was -0.1596683333333333 W/m^2. Sensible heat flux was -0.1724631666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -3.66", + "(B) -0.13", + "(C) -0.9", + "(D) -0.15", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi6_2002-05-05_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0288", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.6491, longitude -91.0693. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.098984375 degrees Celsius. Incoming shortwave radiation was -0.42112825 W/m^2. Vapor pressure deficit was -0.4238409090909091 kPa. Air pressure was 0.096 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4775399999999999 m/s. Wind direction was 0.2692555555555556 decimal degrees. Relative humidity was 0.0345199999999999 percent. Net radiation was -0.0893366666666666 W/m^2. Incoming photosynthetic photon flux density was -0.34270203125 μmol Photon/m^2/s. CO2 concentration was -0.3298334999999999 μmol CO2/mol. Latent heat flux was -0.1572905333333333 W/m^2. Sensible heat flux was -0.1515003666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -11.54", + "(B) -6.24", + "(C) 0.12", + "(D) 0.04", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi7_2005-05-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0289", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7223, longitude -91.2524. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.054446875 degrees Celsius. Incoming shortwave radiation was -0.22662325 W/m^2. Vapor pressure deficit was -0.4352363636363636 kPa. Air pressure was 0.0985923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.478725 m/s. Wind direction was -0.7557027777777777 decimal degrees. Relative humidity was -0.132515 percent. Net radiation was -0.0743443333333333 W/m^2. Incoming photosynthetic photon flux density was -0.1089221874999999 μmol Photon/m^2/s. CO2 concentration was -0.31792375 μmol CO2/mol. Soil heat flux was -0.1577741666666666 W/m^2. Latent heat flux was -0.1587743333333333 W/m^2. Sensible heat flux was -0.1057915 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.84", + "(B) 6.75", + "(C) 0.94", + "(D) 3.87", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi8_2002-05-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0290", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7385, longitude -91.0746. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0653375 degrees Celsius. Incoming shortwave radiation was -0.40794525 W/m^2. Vapor pressure deficit was -0.4731181818181818 kPa. Air pressure was 0.0855961538461538 kPa. Precipitation was recorded at -0.4996666666666667 mm. Wind speed was -0.469805 m/s. Wind direction was -0.5829555555555556 decimal degrees. Relative humidity was 0.2673949999999999 percent. Net radiation was -0.0899715 W/m^2. Incoming photosynthetic photon flux density was -0.3268571875 μmol Photon/m^2/s. CO2 concentration was -0.3198585 μmol CO2/mol. Latent heat flux was -0.14339 W/m^2. Sensible heat flux was -0.1370365 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.92", + "(B) -3.88", + "(C) 2.26", + "(D) -11.38", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wi9_2004-06-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0291", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 34.4255, longitude -105.8615. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.198003125 degrees Celsius. Incoming shortwave radiation was -0.0560639999999999 W/m^2. Incoming longwave radiation was -0.3106332499999999 W/m^2. Vapor pressure deficit was -0.1526227272727272 kPa. Air pressure was -0.0341576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.486565 m/s. Wind direction was 0.3814081666666668 decimal degrees. Relative humidity was -0.3180705 percent. Net radiation was 0.0275789749999999 W/m^2. Incoming photosynthetic photon flux density was 0.1164382812499999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3876011166666667 W/m^2. Outgoing longwave radiation was -0.1915090880952381 W/m^2. CO2 concentration was -0.3076314999999999 μmol CO2/mol. Latent heat flux was -0.0956258333333333 W/m^2. Sensible heat flux was -0.1193495 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.06", + "(B) -1.38", + "(C) 3.21", + "(D) -4.82", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wjs_2007-07-18_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0292", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.7365, longitude -109.9419. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.158828125 degrees Celsius. Incoming shortwave radiation was 0.0072149999999999 W/m^2. Incoming longwave radiation was -0.3335885 W/m^2. Vapor pressure deficit was -0.2452545454545454 kPa. Air pressure was 0.002626923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.471665 m/s. Wind direction was 0.6734269444444446 decimal degrees. Relative humidity was -0.3627763144 percent. Net radiation was 0.0364488333333333 W/m^2. Incoming photosynthetic photon flux density was 0.19734375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3704453125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3708457142857143 W/m^2. Outgoing longwave radiation was -0.182530238095238 W/m^2. CO2 concentration was -0.31288175 μmol CO2/mol. Soil heat flux was -0.1343050833333333 W/m^2. Latent heat flux was -0.1351757 W/m^2. Sensible heat flux was -0.0901443333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.03", + "(B) 0.05", + "(C) -3.18", + "(D) 0.69", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-Wkg_2004-05-06_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0293", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 41.4646, longitude -82.9962. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.080884375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.31351775 W/m^2. Vapor pressure deficit was -0.4712454545454546 kPa. Air pressure was 0.1080884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.466715 m/s. Wind direction was 0.197886111111111 decimal degrees. Relative humidity was 0.2881212565 percent. Net radiation was -0.159840798275 W/m^2. Incoming photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523809523809524 W/m^2. Outgoing longwave radiation was -0.2836829285714285 W/m^2. CO2 concentration was -0.3065635 μmol CO2/mol. Latent heat flux was -0.1718729 W/m^2. Sensible heat flux was -0.1800042666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.69", + "(B) 0.52", + "(C) 3.8", + "(D) -2.65", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-WPT_2011-01-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0294", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.7624, longitude -122.3303. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.0554375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.362925 W/m^2. Vapor pressure deficit was -0.4902454545454545 kPa. Air pressure was 0.0952807692307692 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48905 m/s. Wind direction was -0.1520033143818333 decimal degrees. Relative humidity was 0.4054999999999999 percent. Net radiation was -0.1935416666666666 W/m^2. Incoming photosynthetic photon flux density was -0.437465625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4371109375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4527214285714286 W/m^2. Outgoing longwave radiation was -0.2859285714285715 W/m^2. CO2 concentration was -0.2894745 μmol CO2/mol. Soil heat flux was -0.1663155 W/m^2. Latent heat flux was -0.1683647955 W/m^2. Sensible heat flux was -0.1681416849999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -7.78", + "(B) -0.32", + "(C) -4.0", + "(D) 4.41", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAB_2020-10-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0295", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.4106, longitude -99.0588. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1032218749999999 degrees Celsius. Incoming shortwave radiation was -0.21353875 W/m^2. Incoming longwave radiation was -0.361375 W/m^2. Vapor pressure deficit was -0.3787954545454546 kPa. Air pressure was 0.0788346153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.481645 m/s. Wind direction was 0.3564835908429472 decimal degrees. Relative humidity was -0.20905 percent. Net radiation was -0.0567483333333333 W/m^2. Incoming photosynthetic photon flux density was -0.060315625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.397434375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.405647619047619 W/m^2. Outgoing longwave radiation was -0.2461904761904761 W/m^2. CO2 concentration was -0.2936 μmol CO2/mol. Soil heat flux was -0.1575099 W/m^2. Latent heat flux was -0.1448674 W/m^2. Sensible heat flux was -0.1000665 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xAE_2019-01-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0296", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 71.2824, longitude -156.6194. This site belongs to the Permanent Wetlands type: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.022903125 degrees Celsius. Incoming shortwave radiation was -0.4066012499999999 W/m^2. Incoming longwave radiation was -0.33285 W/m^2. Vapor pressure deficit was -0.4918272727272727 kPa. Air pressure was 0.1318884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4775549999999999 m/s. Wind direction was 0.8644024918359636 decimal degrees. Relative humidity was 0.3868000000000001 percent. Net radiation was -0.1161633333333333 W/m^2. Incoming photosynthetic photon flux density was -0.2951390625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4226578125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4380547619047619 W/m^2. Outgoing longwave radiation was -0.2865714285714285 W/m^2. CO2 concentration was -0.295463 μmol CO2/mol. Soil heat flux was -0.15782575 W/m^2. Latent heat flux was -0.1595861666666666 W/m^2. Sensible heat flux was -0.1521738 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.59", + "(B) -0.01", + "(C) 0.0", + "(D) -0.12", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBA_2019-06-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0297", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.0603, longitude -78.0716. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1848749999999999 degrees Celsius. Incoming shortwave radiation was -0.4052362499999999 W/m^2. Incoming longwave radiation was -0.292625 W/m^2. Vapor pressure deficit was -0.3321545454545454 kPa. Air pressure was 0.1102461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4794 m/s. Wind direction was -0.0497978853264694 decimal degrees. Relative humidity was 0.0551 percent. Net radiation was -0.1374333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3253328125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4318125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4383785714285714 W/m^2. Outgoing longwave radiation was -0.2200952380952381 W/m^2. CO2 concentration was -0.2961425 μmol CO2/mol. Soil heat flux was -0.1604313333333333 W/m^2. Latent heat flux was -0.14058925 W/m^2. Sensible heat flux was -0.16886424 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.11", + "(B) 0.64", + "(C) 1.04", + "(D) -4.58", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBL_2019-10-01_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0298", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 65.154, longitude -147.5026. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.03944375 degrees Celsius. Incoming shortwave radiation was -0.2908199999999999 W/m^2. Incoming longwave radiation was -0.40885 W/m^2. Vapor pressure deficit was -0.4761590909090908 kPa. Air pressure was 0.1076576923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.42007 m/s. Wind direction was -0.6821853882688748 decimal degrees. Relative humidity was -0.188 percent. Net radiation was -0.0963216666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1737265625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.3853265625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4105071428571429 W/m^2. Outgoing longwave radiation was -0.3109047619047619 W/m^2. CO2 concentration was -0.29119725 μmol CO2/mol. Soil heat flux was -0.1665608611666666 W/m^2. Latent heat flux was -0.1544475666666666 W/m^2. Sensible heat flux was -0.1033278333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.02", + "(B) 0.78", + "(C) 0.2", + "(D) 1.96", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xBN_2019-04-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0299", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 33.4012, longitude -97.57. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1728625 degrees Celsius. Incoming shortwave radiation was -0.48635375 W/m^2. Incoming longwave radiation was -0.29605 W/m^2. Vapor pressure deficit was -0.3848590909090909 kPa. Air pressure was 0.1028153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.483125 m/s. Wind direction was -0.2806629835877945 decimal degrees. Relative humidity was 0.1591499999999999 percent. Net radiation was -0.177245 W/m^2. Incoming photosynthetic photon flux density was -0.4166734375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4363984374999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4500142857142857 W/m^2. Outgoing longwave radiation was -0.2302142857142857 W/m^2. CO2 concentration was -0.292774 μmol CO2/mol. Soil heat flux was -0.164010445 W/m^2. Latent heat flux was -0.1564658683333333 W/m^2. Sensible heat flux was -0.1664769166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCL_2018-09-13_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0300", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.8155, longitude -104.7456. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.053884375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3738 W/m^2. Vapor pressure deficit was -0.4272 kPa. Air pressure was -0.0136153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4763799999999999 m/s. Wind direction was 0.51175697208705 decimal degrees. Relative humidity was -0.2153 percent. Net radiation was -0.1890483333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375203125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375234375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519833333333333 W/m^2. Outgoing longwave radiation was -0.3023333333333333 W/m^2. CO2 concentration was -0.29494225 μmol CO2/mol. Soil heat flux was -0.1700607833333333 W/m^2. Latent heat flux was -0.165512685 W/m^2. Sensible heat flux was -0.1722536499999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.95", + "(B) 0.21", + "(C) 0.48", + "(D) 1.71", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xCP_2017-02-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0301", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.1617, longitude -99.1066. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13566875 degrees Celsius. Incoming shortwave radiation was -0.458015 W/m^2. Incoming longwave radiation was -0.320875 W/m^2. Vapor pressure deficit was -0.4547363636363636 kPa. Air pressure was 0.0756 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.40009 m/s. Wind direction was -0.15949587415585 decimal degrees. Relative humidity was 0.3089500000000001 percent. Net radiation was -0.1715333333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3920296874999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4339828125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4443619047619047 W/m^2. Outgoing longwave radiation was -0.2427619047619047 W/m^2. CO2 concentration was -0.309614 μmol CO2/mol. Soil heat flux was -0.164440945 W/m^2. Latent heat flux was -0.160173735 W/m^2. Sensible heat flux was -0.1754886333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.31", + "(B) 0.43", + "(C) 0.59", + "(D) -1.36", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDC_2017-08-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0302", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 63.8811, longitude -145.7514. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0356 degrees Celsius. Incoming shortwave radiation was -0.35198 W/m^2. Incoming longwave radiation was -0.39605 W/m^2. Vapor pressure deficit was -0.4805181818181818 kPa. Air pressure was 0.0895230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4762599999999999 m/s. Wind direction was -0.4285839209803333 decimal degrees. Relative humidity was -0.0350999999999999 percent. Net radiation was -0.1049416666666666 W/m^2. Incoming photosynthetic photon flux density was -0.253475 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.415525 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4321166666666667 W/m^2. Outgoing longwave radiation was -0.315547619047619 W/m^2. CO2 concentration was -0.289292 μmol CO2/mol. Soil heat flux was -0.1670806666666666 W/m^2. Latent heat flux was -0.1628635666666666 W/m^2. Sensible heat flux was -0.1341922666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDJ_2019-02-26_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0303", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 32.5417, longitude -87.8039. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.149865625 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.304375 W/m^2. Vapor pressure deficit was -0.4847 kPa. Air pressure was 0.1207538461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47396 m/s. Wind direction was 0.1224709950599361 decimal degrees. Relative humidity was 0.4437 percent. Net radiation was -0.1845416666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4375546875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43743125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521809523809524 W/m^2. Outgoing longwave radiation was -0.2419761904761904 W/m^2. CO2 concentration was -0.2888605 μmol CO2/mol. Soil heat flux was -0.1663823333333333 W/m^2. Latent heat flux was -0.1645352116666666 W/m^2. Sensible heat flux was -0.17798365 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDL_2018-06-21_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0304", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 28.125, longitude -81.4362. This site belongs to the Cropland/Natural Vegetation Mosaics type: Lands with a mosaic of croplands, forest, shrublands, and grasslands in which no one component comprises more than 60% of the landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.086603125 degrees Celsius. Incoming shortwave radiation was -0.2452562499999999 W/m^2. Incoming longwave radiation was -0.339625 W/m^2. Vapor pressure deficit was -0.4180136363636363 kPa. Air pressure was 0.1321653846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47272 m/s. Wind direction was 0.9513258436930192 decimal degrees. Relative humidity was -0.0690999999999999 percent. Net radiation was -0.0529516666666666 W/m^2. Incoming photosynthetic photon flux density was -0.1199203125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4136125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4124142857142857 W/m^2. Outgoing longwave radiation was -0.2561904761904762 W/m^2. CO2 concentration was -0.2901015 μmol CO2/mol. Soil heat flux was -0.1699901116666666 W/m^2. Latent heat flux was -0.1404963166666666 W/m^2. Sensible heat flux was -0.1096343333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xDS_2018-11-29_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0305", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 35.689, longitude -83.5019. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.179196875 degrees Celsius. Incoming shortwave radiation was -0.0678025 W/m^2. Incoming longwave radiation was -0.30045 W/m^2. Vapor pressure deficit was -0.2804181818181818 kPa. Air pressure was 0.079226923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4794299999999999 m/s. Wind direction was -0.0058699456275083 decimal degrees. Relative humidity was -0.1143999999999999 percent. Net radiation was 0.05071 W/m^2. Incoming photosynthetic photon flux density was 0.0630515625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.42016875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.395495238095238 W/m^2. Outgoing longwave radiation was -0.2182857142857142 W/m^2. CO2 concentration was -0.29619975 μmol CO2/mol. Soil heat flux was -0.1625934 W/m^2. Latent heat flux was -0.0811549999999999 W/m^2. Sensible heat flux was -0.1263845999999999 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xGR_2019-05-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0306", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 42.5369, longitude -72.1727. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.049803125 degrees Celsius. Incoming shortwave radiation was -0.49965125 W/m^2. Incoming longwave radiation was -0.324225 W/m^2. Vapor pressure deficit was -0.4902363636363636 kPa. Air pressure was 0.0989538461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46653 m/s. Wind direction was -0.1710590705301306 decimal degrees. Relative humidity was 0.3999000000000001 percent. Net radiation was -0.1685183333333333 W/m^2. Incoming photosynthetic photon flux density was -0.437590625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375890625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4524285714285714 W/m^2. Outgoing longwave radiation was -0.2825238095238095 W/m^2. CO2 concentration was -0.29300575 μmol CO2/mol. Soil heat flux was -0.16800798 W/m^2. Latent heat flux was -0.168039085 W/m^2. Sensible heat flux was -0.1665850666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 5.92", + "(B) 2.94", + "(C) 10.85", + "(D) 1.09", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHA_2017-02-28_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0307", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 63.8757, longitude -149.2133. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.036765625 degrees Celsius. Incoming shortwave radiation was -0.4880675 W/m^2. Incoming longwave radiation was -0.340375 W/m^2. Vapor pressure deficit was -0.4709136363636363 kPa. Air pressure was 0.0558846153846153 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48662 m/s. Wind direction was 0.1797184917735639 decimal degrees. Relative humidity was 0.15525 percent. Net radiation was -0.1643033333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4241703125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4363390625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4500761904761904 W/m^2. Outgoing longwave radiation was -0.2947857142857142 W/m^2. CO2 concentration was -0.30008475 μmol CO2/mol. Soil heat flux was -0.1666492778333333 W/m^2. Latent heat flux was -0.1659945216666666 W/m^2. Sensible heat flux was -0.1788161833333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xHE_2017-09-07_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0308", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.1948, longitude -84.4686. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.140796875 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.29785 W/m^2. Vapor pressure deficit was -0.3750772727272727 kPa. Air pressure was 0.1181423076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4721649999999999 m/s. Wind direction was -0.1848764582112304 decimal degrees. Relative humidity was -0.00155 percent. Net radiation was -0.17393 W/m^2. Incoming photosynthetic photon flux density was -0.43750625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375843749999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4525642857142857 W/m^2. Outgoing longwave radiation was -0.2502380952380952 W/m^2. CO2 concentration was -0.2909265 μmol CO2/mol. Soil heat flux was -0.16602931 W/m^2. Latent heat flux was -0.1666051316666666 W/m^2. Sensible heat flux was -0.1658375433333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 2.0", + "(B) -0.72", + "(C) 1.33", + "(D) -11.13", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJE_2017-11-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0309", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 32.5907, longitude -106.8425. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.157178125 degrees Celsius. Incoming shortwave radiation was -0.499361 W/m^2. Incoming longwave radiation was -0.3198 W/m^2. Vapor pressure deficit was -0.3533727272727273 kPa. Air pressure was 0.0134884615384615 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47287 m/s. Wind direction was -0.0107337814830166 decimal degrees. Relative humidity was -0.0031999999999999 percent. Net radiation was -0.1949033333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4360875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4341359374999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452352380952381 W/m^2. Outgoing longwave radiation was -0.242047619047619 W/m^2. CO2 concentration was -0.297042 μmol CO2/mol. Soil heat flux was -0.1787299166666666 W/m^2. Latent heat flux was -0.1624264 W/m^2. Sensible heat flux was -0.16900736 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.17", + "(B) 1.64", + "(C) 0.05", + "(D) 0.78", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xJR_2019-09-16_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0310", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.1104, longitude -96.6129. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.150325 degrees Celsius. Incoming shortwave radiation was -0.49950125 W/m^2. Incoming longwave radiation was -0.3032749999999999 W/m^2. Vapor pressure deficit was -0.32495 kPa. Air pressure was 0.0995307692307691 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45018 m/s. Wind direction was -0.1114958235470444 decimal degrees. Relative humidity was -0.14275 percent. Net radiation was -0.1818883333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4366609375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4373390625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452497619047619 W/m^2. Outgoing longwave radiation was -0.2440714285714285 W/m^2. CO2 concentration was -0.289955 μmol CO2/mol. Soil heat flux was -0.16671172 W/m^2. Latent heat flux was -0.1664008216666666 W/m^2. Sensible heat flux was -0.1688151533333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKA_2017-09-30_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0311", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.1008, longitude -96.5631. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1516718749999999 degrees Celsius. Incoming shortwave radiation was -0.46646125 W/m^2. Incoming longwave radiation was -0.324925 W/m^2. Vapor pressure deficit was -0.3737 kPa. Air pressure was 0.0922269230769231 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4595349999999999 m/s. Wind direction was -0.1851589181462527 decimal degrees. Relative humidity was 0.0432999999999999 percent. Net radiation was -0.1777366666666666 W/m^2. Incoming photosynthetic photon flux density was -0.3914578125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4329484375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4429928571428571 W/m^2. Outgoing longwave radiation was -0.2448095238095238 W/m^2. CO2 concentration was -0.3057815 μmol CO2/mol. Soil heat flux was -0.1643348899999999 W/m^2. Latent heat flux was -0.1615192283333333 W/m^2. Sensible heat flux was -0.1708013233333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xKZ_2017-08-25_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0312", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.2483, longitude -109.3883. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.041928125 degrees Celsius. Incoming shortwave radiation was -0.49685 W/m^2. Incoming longwave radiation was -0.334475 W/m^2. Vapor pressure deficit was -0.4610409090909091 kPa. Air pressure was -0.0278576923076922 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.43799 m/s. Wind direction was -0.3273067535926889 decimal degrees. Relative humidity was 0.0638499999999999 percent. Net radiation was -0.171915 W/m^2. Incoming photosynthetic photon flux density was -0.4332984375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4369609375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519547619047619 W/m^2. Outgoing longwave radiation was -0.2851904761904761 W/m^2. CO2 concentration was -0.29301125 μmol CO2/mol. Soil heat flux was -0.1578508333333333 W/m^2. Latent heat flux was -0.165496025 W/m^2. Sensible heat flux was -0.1739028166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.0", + "(B) 0.6", + "(C) 0.26", + "(D) -0.53", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xMB_2019-02-02_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0313", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.3783, longitude -80.5248. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.088203125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.3065 W/m^2. Vapor pressure deficit was -0.4952409090909091 kPa. Air pressure was 0.0257692307692307 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4666349999999999 m/s. Wind direction was 0.4749865257783249 decimal degrees. Relative humidity was 0.4675 percent. Net radiation was -0.1674233333333333 W/m^2. Incoming photosynthetic photon flux density was -0.4375234375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4519976190476191 W/m^2. Outgoing longwave radiation was -0.2681428571428571 W/m^2. CO2 concentration was -0.286596 μmol CO2/mol. Soil heat flux was -0.1649096933333333 W/m^2. Latent heat flux was -0.1551764 W/m^2. Sensible heat flux was -0.1725310666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xML_2019-05-03_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0314", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 46.7697, longitude -100.9154. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11439375 degrees Celsius. Incoming shortwave radiation was -0.4995462499999999 W/m^2. Incoming longwave radiation was -0.29545 W/m^2. Vapor pressure deficit was -0.4860863636363636 kPa. Air pressure was 0.0718153846153846 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.445495 m/s. Wind direction was -0.4121200681309861 decimal degrees. Relative humidity was 0.4273 percent. Net radiation was -0.167935 W/m^2. Incoming photosynthetic photon flux density was -0.4378234375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521333333333333 W/m^2. Outgoing longwave radiation was -0.2565714285714285 W/m^2. CO2 concentration was -0.288433 μmol CO2/mol. Soil heat flux was -0.165763 W/m^2. Latent heat flux was -0.1553199333333333 W/m^2. Sensible heat flux was -0.1695530483333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNG_2018-09-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0315", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.1776, longitude -112.4524. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.01731875 degrees Celsius. Incoming shortwave radiation was -0.49878625 W/m^2. Incoming longwave radiation was -0.348175 W/m^2. Vapor pressure deficit was -0.4944454545454546 kPa. Air pressure was -0.0122384615384616 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.488245 m/s. Wind direction was 0.5059844812835722 decimal degrees. Relative humidity was 0.3778999999999999 percent. Net radiation was -0.1666016666666666 W/m^2. Incoming photosynthetic photon flux density was -0.43698125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.436578125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4522809523809523 W/m^2. Outgoing longwave radiation was -0.3076904761904762 W/m^2. CO2 concentration was -0.288201 μmol CO2/mol. Soil heat flux was -0.167574935 W/m^2. Latent heat flux was -0.16833603 W/m^2. Sensible heat flux was -0.19263565 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xNQ_2019-01-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0316", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.2759, longitude -105.5459. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.09113125 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.366625 W/m^2. Vapor pressure deficit was -0.3859090909090909 kPa. Air pressure was -0.0908923076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47849 m/s. Wind direction was -0.4586961864817644 decimal degrees. Relative humidity was -0.25565 percent. Net radiation was -0.202695 W/m^2. Incoming photosynthetic photon flux density was -0.437471875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374546875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4518642857142857 W/m^2. Outgoing longwave radiation was -0.2775714285714286 W/m^2. CO2 concentration was -0.29520675 μmol CO2/mol. Soil heat flux was -0.168827945 W/m^2. Latent heat flux was -0.1638978583333333 W/m^2. Sensible heat flux was -0.1806060166666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xRM_2018-09-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0317", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 29.6893, longitude -81.9934. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1467375 degrees Celsius. Incoming shortwave radiation was -0.499415 W/m^2. Incoming longwave radiation was -0.2912749999999999 W/m^2. Vapor pressure deficit was -0.4754045454545454 kPa. Air pressure was 0.1249538461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.47424 m/s. Wind direction was 0.2689353887317836 decimal degrees. Relative humidity was 0.4065000000000001 percent. Net radiation was -0.175905 W/m^2. Incoming photosynthetic photon flux density was -0.437115625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374640625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4520928571428571 W/m^2. Outgoing longwave radiation was -0.2408095238095238 W/m^2. CO2 concentration was -0.263149 μmol CO2/mol. Soil heat flux was -0.1739704833333333 W/m^2. Latent heat flux was -0.16792303 W/m^2. Sensible heat flux was -0.169512815 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSB_2019-08-19_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0318", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.8929, longitude -78.1395. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.11898125 degrees Celsius. Incoming shortwave radiation was -0.2706275 W/m^2. Incoming longwave radiation was -0.3132 W/m^2. Vapor pressure deficit was -0.4727 kPa. Air pressure was 0.1023423076923077 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.44218 m/s. Wind direction was -0.1614081408291112 decimal degrees. Relative humidity was 0.36375 percent. Net radiation was -0.05363 W/m^2. Incoming photosynthetic photon flux density was -0.1407890625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.427034375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4203190476190476 W/m^2. Outgoing longwave radiation was -0.2502857142857143 W/m^2. CO2 concentration was -0.2970215 μmol CO2/mol. Soil heat flux was -0.1670273333333333 W/m^2. Latent heat flux was -0.1372234666666666 W/m^2. Sensible heat flux was -0.1320096666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 6.23", + "(B) 4.14", + "(C) 2.2", + "(D) -10.78", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSC_2021-09-20_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0319", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 38.8901, longitude -76.56. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.12886875 degrees Celsius. Incoming shortwave radiation was -0.4999125 W/m^2. Incoming longwave radiation was -0.318525 W/m^2. Vapor pressure deficit was -0.4705181818181818 kPa. Air pressure was 0.1254076923076922 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.471975 m/s. Wind direction was 0.6176916855926026 decimal degrees. Relative humidity was 0.3666499999999999 percent. Net radiation was -0.1856116666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4376546875 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4375703124999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.452197619047619 W/m^2. Outgoing longwave radiation was -0.254047619047619 W/m^2. CO2 concentration was -0.28483625 μmol CO2/mol. Soil heat flux was -0.1658554016666666 W/m^2. Latent heat flux was -0.1643413166666666 W/m^2. Sensible heat flux was -0.16876819 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "C", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSE_2017-09-15_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0320", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 37.1088, longitude -119.7323. This site belongs to the Savannas type: Lands with herbaceous and other understory systems, and with forest canopy cover between 10-30%. The forest cover height exceeds 2 meters. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.1868281249999999 degrees Celsius. Incoming shortwave radiation was -0.4422275 W/m^2. Incoming longwave radiation was -0.3123 W/m^2. Vapor pressure deficit was -0.2177909090909091 kPa. Air pressure was 0.0910461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.4452649999999999 m/s. Wind direction was 0.6280882459268222 decimal degrees. Relative humidity was -0.23585 percent. Net radiation was -0.1749 W/m^2. Incoming photosynthetic photon flux density was -0.3747093749999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4316203125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4417880952380952 W/m^2. Outgoing longwave radiation was -0.2174285714285714 W/m^2. CO2 concentration was -0.2995385 μmol CO2/mol. Soil heat flux was -0.1622584166666666 W/m^2. Latent heat flux was -0.1609978833333333 W/m^2. Sensible heat flux was -0.1598890633333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSJ_2019-07-10_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0321", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 40.4619, longitude -103.0293. This site belongs to the Croplands type: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.015575 degrees Celsius. Incoming shortwave radiation was -0.1656862499999999 W/m^2. Incoming longwave radiation was -0.393875 W/m^2. Vapor pressure deficit was -0.4907363636363636 kPa. Air pressure was 0.0002076923076923 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.415065 m/s. Wind direction was 0.991999587454672 decimal degrees. Relative humidity was 0.3000499999999999 percent. Net radiation was -0.0860133333333333 W/m^2. Incoming photosynthetic photon flux density was -0.0240156249999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.1686515625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.2749547619047618 W/m^2. Outgoing longwave radiation was -0.3068333333333333 W/m^2. CO2 concentration was -0.2921042499999999 μmol CO2/mol. Soil heat flux was -0.1663409755 W/m^2. Latent heat flux was -0.1377067833333333 W/m^2. Sensible heat flux was -0.1245526666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -0.21", + "(B) 0.36", + "(C) 2.91", + "(D) 1.12", + "(E) Unable to decide." + ], + "Ground Truth": "B", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSL_2019-02-23_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0322", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 31.9107, longitude -110.8355. This site belongs to the Open Shrublands type: Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10-60%. The shrub foliage can be either evergreen or deciduous. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.15124375 degrees Celsius. Incoming shortwave radiation was -0.5 W/m^2. Incoming longwave radiation was -0.337575 W/m^2. Vapor pressure deficit was -0.2996772727272727 kPa. Air pressure was 0.0352653846153845 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.45402 m/s. Wind direction was 0.2951863114183611 decimal degrees. Relative humidity was -0.2289999999999999 percent. Net radiation was -0.2032716666666666 W/m^2. Incoming photosynthetic photon flux density was -0.4374953124999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.43748125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4523333333333333 W/m^2. Outgoing longwave radiation was -0.2484285714285714 W/m^2. CO2 concentration was -0.29761025 μmol CO2/mol. Soil heat flux was -0.1768181666666667 W/m^2. Latent heat flux was -0.1671102466666666 W/m^2. Sensible heat flux was -0.1792748666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xSR_2017-10-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0323", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.5089, longitude -89.5864. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13606875 degrees Celsius. Incoming shortwave radiation was -0.4178274999999999 W/m^2. Incoming longwave radiation was -0.337425 W/m^2. Vapor pressure deficit was -0.3535681818181818 kPa. Air pressure was 0.0878038461538461 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.46806 m/s. Wind direction was -0.70932940111943 decimal degrees. Relative humidity was -0.1173999999999999 percent. Net radiation was -0.1530766666666666 W/m^2. Incoming photosynthetic photon flux density was -0.3203234375 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4308140625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4374428571428571 W/m^2. Outgoing longwave radiation was -0.2502857142857143 W/m^2. CO2 concentration was -0.29698375 μmol CO2/mol. Soil heat flux was -0.1640209483333333 W/m^2. Latent heat flux was -0.1536957333333333 W/m^2. Sensible heat flux was -0.1632327333333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xST_2018-08-22_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0324", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 32.9505, longitude -87.3933. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.088078125 degrees Celsius. Incoming shortwave radiation was -0.4996212499999999 W/m^2. Incoming longwave radiation was -0.306125 W/m^2. Vapor pressure deficit was -0.49015 kPa. Air pressure was 0.1065923076923076 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.470555 m/s. Wind direction was 0.017474415667161 decimal degrees. Relative humidity was 0.43265 percent. Net radiation was -0.16859 W/m^2. Incoming photosynthetic photon flux density was -0.4375156249999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4374578125 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4521261904761905 W/m^2. Outgoing longwave radiation was -0.2654761904761905 W/m^2. CO2 concentration was -0.295431 μmol CO2/mol. Soil heat flux was -0.1745413333333333 W/m^2. Latent heat flux was -0.165269545 W/m^2. Sensible heat flux was -0.1687683316666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTA_2017-09-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0325", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 45.4937, longitude -89.5857. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.13721875 degrees Celsius. Incoming shortwave radiation was -0.46893 W/m^2. Incoming longwave radiation was -0.334075 W/m^2. Vapor pressure deficit was -0.3786409090909091 kPa. Air pressure was 0.0864461538461538 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.482425 m/s. Wind direction was 0.8857316705245694 decimal degrees. Relative humidity was -0.0059499999999999 percent. Net radiation was -0.17982 W/m^2. Incoming photosynthetic photon flux density was -0.3625328125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4350796875 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4460761904761904 W/m^2. Outgoing longwave radiation was -0.2518809523809524 W/m^2. CO2 concentration was -0.306183 μmol CO2/mol. Soil heat flux was -0.1625637833333333 W/m^2. Latent heat flux was -0.1579035666666666 W/m^2. Sensible heat flux was -0.1700064216666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 0.6", + "(B) 0.05", + "(C) -1.75", + "(D) -0.7", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xTR_2017-08-12_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0326", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 39.0404, longitude -95.1921. This site belongs to the Deciduous Broadleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.142503125 degrees Celsius. Incoming shortwave radiation was -0.4441525 W/m^2. Incoming longwave radiation was -0.311975 W/m^2. Vapor pressure deficit was -0.4288 kPa. Air pressure was 0.1001230769230769 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.48886 m/s. Wind direction was 0.0113909138560111 decimal degrees. Relative humidity was 0.2181499999999999 percent. Net radiation was -0.1521183333333333 W/m^2. Incoming photosynthetic photon flux density was -0.3621640625 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4343453124999999 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4425738095238095 W/m^2. Outgoing longwave radiation was -0.2496666666666666 W/m^2. CO2 concentration was -0.30528675 μmol CO2/mol. Soil heat flux was -0.166541 W/m^2. Latent heat flux was -0.15097785 W/m^2. Sensible heat flux was -0.169488174 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) 1.47", + "(B) 5.35", + "(C) 2.6", + "(D) -1.3", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xUK_2017-07-31_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0327", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 47.1282, longitude -99.2414. This site belongs to the Grasslands type: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.070878125 degrees Celsius. Incoming shortwave radiation was -0.4615025 W/m^2. Incoming longwave radiation was -0.3642749999999999 W/m^2. Vapor pressure deficit was -0.4360272727272727 kPa. Air pressure was 0.0727846153846154 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.458725 m/s. Wind direction was 0.9058112095671692 decimal degrees. Relative humidity was -0.02265 percent. Net radiation was -0.1778183333333333 W/m^2. Incoming photosynthetic photon flux density was -0.390578125 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.4300984375 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.4439071428571429 W/m^2. Outgoing longwave radiation was -0.2813095238095238 W/m^2. CO2 concentration was -0.2915757499999999 μmol CO2/mol. Soil heat flux was -0.157347 W/m^2. Latent heat flux was -0.1651223416666666 W/m^2. Sensible heat flux was -0.1696964383333333 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xWD_2019-04-08_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0328", + "Question Type": "Single Choice", + "Text": "This site is located at latitude 44.9535, longitude -110.5391. This site belongs to the Evergreen Needleleaf Forests type: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was -0.0637062499999999 degrees Celsius. Incoming shortwave radiation was -0.1928837499999999 W/m^2. Incoming longwave radiation was -0.406775 W/m^2. Vapor pressure deficit was -0.4855772727272727 kPa. Air pressure was -0.0506461538461538 kPa. Precipitation was recorded at -0.4999333333333333 mm. Wind speed was -0.488365 m/s. Wind direction was 0.7157741336689055 decimal degrees. Relative humidity was -0.0632999999999999 percent. Net radiation was -0.0787483333333333 W/m^2. Incoming photosynthetic photon flux density was -0.0472453124999999 μmol Photon/m^2/s. Outgoing photosynthetic photon flux density was -0.2478890625 μmol Photon/m^2/s. Outgoing shortwave radiation was -0.3183523809523809 W/m^2. Outgoing longwave radiation was -0.3220238095238095 W/m^2. CO2 concentration was -0.280258 μmol CO2/mol. Soil heat flux was -0.16723852 W/m^2. Latent heat flux was -0.161081 W/m^2. Sensible heat flux was -0.1286241666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) nan", + "(B) nan", + "(C) nan", + "(D) nan", + "(E) Unable to decide." + ], + "Ground Truth": "A", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/US-xYE_2019-03-04_MODIS_band07.png" + ] + }, + { + "Question_id": "Carbon flux estimation/0329", + "Question Type": "Single Choice", + "Text": "This site is located at latitude -33.4648, longitude -66.4598. This site belongs to the Mixed Forests type: Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape. The input images are the 1-7 band images of MODIS satellite, and the pixel value is surface reflection multiplied by 255. The following are the meteorological variables of this station: Air temperature was 0.2053124999999999 degrees Celsius. Incoming shortwave radiation was -0.33560825 W/m^2. Vapor pressure deficit was -0.1993818181818182 kPa. Air pressure was 0.0761115384615384 kPa. Precipitation was recorded at -0.5 mm. Wind speed was -0.475405 m/s. Wind direction was -0.8767630555555556 decimal degrees. Relative humidity was -0.162783 percent. Net radiation was -0.1293252333333333 W/m^2. Incoming photosynthetic photon flux density was -0.2999334375 μmol Photon/m^2/s. CO2 concentration was -0.3109645 μmol CO2/mol. Soil heat flux was -0.1578361333333333 W/m^2. Latent heat flux was -0.1320666666666666 W/m^2. Sensible heat flux was -0.1563666666666666 W/m^2. What is the Net Ecosystem Exchange (NEE) at this site in μmol CO2/m^2/s?", + "L1-task": "Cross-sphere", + "L2-task": "Carbon flux monitoring", + "L3-task": "Reasoning", + "L4-task": "Carbon flux estimation", + "Dataset": "Carbonsense", + "Answer Choices": [ + "(A) -1.29", + "(B) -20.04", + "(C) 1.98", + "(D) -4.06", + "(E) Unable to decide." + ], + "Ground Truth": "D", + "Images": [ + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band01.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band02.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band03.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band04.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band05.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band06.png", + "raw/Cross-sphere/Carbon flux monitoring/image/AR-SLu_2010-01-02_MODIS_band07.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Detecting.json b/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Detecting.json new file mode 100644 index 0000000000000000000000000000000000000000..4eba3a756d25fb6b01700883c033eac1efc89185 --- /dev/null +++ b/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Detecting.json @@ -0,0 +1,13710 @@ +[ + { + "Question_id": "Flood Detecting/0", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-1080005420_2018-05-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/1", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-3_2017-05-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/2", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080027560_2017-02-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/3", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/4", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4837-2080002070_2020-01-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/5", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4487-6080027290_2017-06-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/6", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-4_2018-10-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/7", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4301-6080015940_2015-10-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/8", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4770-7080041050_2019-07-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/9", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-3_2018-03-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/10", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/11", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4793-4080001880_2019-08-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/12", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/13", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-12-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/14", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080027200_2015-08-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/15", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-29_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/16", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/17", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/18", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/19", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-2_2018-03-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/20", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4524-7080052330_2017-10-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/21", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/22", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4901-1080004700_2020-04-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/23", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-4_2017-05-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/24", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4666-4080023830_2018-07-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/25", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4731-6080014360_2019-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/26", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-2_2018-10-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/27", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4783-6080011630_2019-07-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/28", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-07-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/29", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/437-7_2020-05-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/30", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/31", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/32", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-08-01_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/33", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-02-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/34", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4546-4080019520_2017-12-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/35", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/36", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4776-4080039730_2019-06-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/37", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4540-2080010300_2017-11-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/38", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-11-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/39", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4712-4080019680_2019-01-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/40", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-5_2017-05-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/41", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4576-6080014140_2018-02-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/42", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-1_2018-10-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/43", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4652-4080017550_2018-07-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/44", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-2_2018-10-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/45", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4848-1080036440_2019-12-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/46", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4216-4080020980_2014-12-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/47", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4620-7080053160_2018-05-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/48", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4648-1080024770_2018-07-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/49", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-11-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/50", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/51", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-29_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/52", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2016-12-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/53", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/54", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/55", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080011420_2020-01-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/56", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4862-2080017320_2020-01-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/57", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-4_2020-02-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/58", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4388-7080047210_2016-08-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/59", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/60", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4430-2080001360_2016-12-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/61", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4541-4080016210_2017-11-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/62", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/63", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080031900_2017-02-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/64", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4560-7080012660_2018-01-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/65", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4426-1080020040_2017-01-01_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/66", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/67", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4778-2080081250_2019-08-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/68", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/69", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080038230_2018-03-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/70", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-02-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/71", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/72", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/445-1_2020-06-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/73", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/74", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/75", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/76", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4207-1080030220_2014-12-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/77", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4488-4080014350_2017-06-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/78", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/79", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024430_2016-08-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/80", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4643-4080041500_2018-07-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/81", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/82", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/83", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/84", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080084350_2019-01-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/85", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-10-29_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/86", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4316-5080070850_2015-12-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/87", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-1_2017-05-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/88", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080023580_2016-06-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/89", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4809-6080001940_2019-10-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/90", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4758-7080005800_2019-06-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/91", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4859-5080009500_2020-01-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/92", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4631-1080023950_2018-06-18_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/93", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/94", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4821-6080000360_2019-10-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/95", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4655-4080736820_2018-07-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/96", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4695-7080006390_2018-10-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/97", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4716-1080011120_2019-01-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/98", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4650-1080023840_2018-07-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/99", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4276-6080015560_2015-07-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/100", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-1_2018-03-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/101", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4698-2080017430_2018-10-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/102", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4856-6080031480_2019-12-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/103", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/104", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4444-7080013530_2017-02-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/105", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4739-4080013340_2019-04-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/106", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019850_2018-03-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/107", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4788-1080029200_2019-08-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/108", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4834-7080007720_2019-11-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/109", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/110", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4217-5080026850_2014-12-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/111", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/112", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-09-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/113", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/411-1_2019-11-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/114", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4396-4080011540_2016-09-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/115", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-02-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/116", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-5_2018-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/117", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080053640_2017-10-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/118", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/119", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/120", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-02-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/121", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080029610_2019-01-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/122", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080012210_2020-01-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/123", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/124", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/125", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080026610_2015-07-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/126", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/127", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008470_2019-10-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/128", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/129", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/130", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080045890_2017-09-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/131", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/132", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4835-6080012280_2019-11-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/133", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/134", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4635-4080011960_2018-06-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/135", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4300-5080030230_2015-10-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/136", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/137", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4573-1080012680_2018-02-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/138", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4404-4080594470_2016-10-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/139", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-01-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/140", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4508-4080025450_2017-08-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/141", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4406-2080008250_2016-10-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/142", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/143", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024690_2016-07-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/144", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2017-01-01_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/145", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/146", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-18_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/147", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4851-1080007000_2019-12-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/148", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/149", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-3_2018-10-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/150", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/151", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-10-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/152", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-2_2018-03-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/153", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4785-4080027840_2019-08-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/154", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4653-4080015000_2018-07-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/155", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/156", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080028470_2017-02-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/157", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4810-7080004480_2019-10-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/158", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/159", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-18_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/160", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-11-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/161", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/162", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-3_2020-02-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/163", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4472-1080008720_2017-05-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/164", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2018-12-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/165", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/166", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080011660_2019-05-01_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/167", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4555-5080025710_2017-12-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/168", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-1_2018-10-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/169", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4467-7080072180_2017-04-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/170", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4727-7080013800_2019-03-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/171", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4800-4080044180_2019-10-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/172", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008470_2019-10-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/173", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080044350_2017-09-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/174", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/175", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/176", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4697-2080006250_2018-10-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/177", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/178", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2019-01-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/179", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4595-6080037030_2018-04-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/180", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-10-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/181", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-1_2015-02-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/182", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/130-6_2015-09-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/183", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4544-5080010420_2017-11-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/184", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4458-5080069590_2017-03-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/185", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-2_2018-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/186", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/187", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4451-5080071340_2017-03-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/188", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4598-1080009450_2018-04-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/189", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-4_2018-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/190", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008230_2019-11-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/191", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-2_2015-12-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/192", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4285-1080025470_2015-07-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/193", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-01-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/194", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4857-6080033560_2019-12-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/195", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/196", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4381-1080012810_2016-07-31_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/197", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4398-2080010990_2016-09-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/198", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/199", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/200", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080010030_2020-01-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/201", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4775-4080031520_2019-07-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/202", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/203", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/204", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029580_2017-02-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/205", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4504-5080084260_2017-07-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/206", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4649-1080023020_2018-07-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/207", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4446-1080013070_2017-02-25_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/208", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-3_2015-12-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/209", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-6_2018-04-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/210", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4917-1080032500_2020-05-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/211", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019010_2018-03-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/212", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4674-4080003500_2018-09-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/213", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4350-6080016300_2016-04-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/214", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/215", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-5_2018-04-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/216", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4748-7080048410_2019-05-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/217", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4429-4080015550_2016-12-18_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/218", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4520-4080043980_2017-09-18_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/219", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4634-4080029860_2018-06-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/220", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4691-6080001560_2018-10-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/221", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-11_2018-04-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/222", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4559-1080039620_2018-01-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/223", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/224", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022910_2019-10-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/225", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4427-6080018500_2016-12-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/226", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4497-4080043390_2017-07-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/227", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/228", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/174-1_2016-08-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/229", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4309-4080028760_2015-11-12_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/230", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4687-7080045890_2018-10-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/231", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/421-5_2020-01-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/232", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-2_2015-02-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/233", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080083100_2019-01-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/234", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-10-06_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/235", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4530-1080013200_2017-09-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/236", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/237", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4674-4080003500_2018-08-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/238", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-4_2018-10-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/239", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/240", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4664-2080004850_2018-08-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/241", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4479-6080011370_2017-05-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/242", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-1_2015-12-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/243", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/244", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080039740_2020-01-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/245", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4432-4080019410_2017-01-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/246", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4711-7080012950_2018-12-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/247", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4221-2080009900_2015-02-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/248", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4330-5080008500_2016-02-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/249", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/417-1_2019-12-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/250", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-01-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/251", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080070390_2020-02-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/252", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-11-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/253", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4260-1080023300_2015-06-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/254", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4771-7080047060_2019-07-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/255", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-10-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/256", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4498-4080032020_2017-07-17_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/257", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-3_2018-10-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/258", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4429-4080015550_2016-12-30_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/259", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4567-5080018390_2018-02-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/260", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4690-2080066030_2018-10-05_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/261", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-11-03_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/262", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-3_2018-03-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/263", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4500-4080015040_2017-08-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/264", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4676-7080042740_2018-09-26_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/265", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022200_2019-11-15_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/266", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-10-28_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/267", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080036020_2020-01-24_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/268", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080010590_2019-05-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/269", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4886-5080032110_2020-03-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/270", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-13_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/271", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4840-6080034250_2020-01-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/272", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4692-1080031290_2018-10-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/273", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4484-4080025260_2017-06-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/274", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/267-1_2018-02-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/275", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080038850_2020-01-21_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/276", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-10_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/277", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-1_2018-03-27_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/278", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-3_2018-03-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/279", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4252-7080048080_2015-05-07_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/280", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4663-4080029720_2018-08-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/281", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4942-4080040230_2020-06-29_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/282", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4927-4080030920_2020-06-02_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/283", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4283-4080023060_2015-07-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/284", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-09-29_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/285", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4554-2080076100_2017-12-16_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/286", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4931-6080016720_2020-06-22_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/287", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-06-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/288", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4480-7080004990_2017-06-01_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/289", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4832-4080049680_2019-12-04_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/290", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080039250_2018-03-20_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/291", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080009880_2016-07-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/292", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080072120_2017-09-14_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/293", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4338-4080012280_2016-03-19_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/294", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080033560_2019-04-08_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/295", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007260_2020-04-23_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/296", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4502-4080001240_2017-08-09_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/297", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-11_19.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_365_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_365_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_365_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_365_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/298", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-1080005420_2018-05-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/299", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-3_2017-05-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/300", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080027560_2017-02-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/301", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/302", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4837-2080002070_2020-01-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/303", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4487-6080027290_2017-06-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/304", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-4_2018-10-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/305", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4301-6080015940_2015-10-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/306", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4770-7080041050_2019-07-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/307", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-3_2018-03-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/308", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/309", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4793-4080001880_2019-08-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/310", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/311", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-12-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/312", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080027200_2015-08-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/313", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-29_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/314", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/315", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/316", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/317", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-2_2018-03-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/318", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4524-7080052330_2017-10-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/319", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/320", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4901-1080004700_2020-04-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/321", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-4_2017-05-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/322", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4666-4080023830_2018-07-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/323", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4731-6080014360_2019-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/324", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-2_2018-10-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/325", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4783-6080011630_2019-07-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/326", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-07-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/327", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/437-7_2020-05-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/328", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/329", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/330", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-08-01_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-08-01_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/331", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-02-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/332", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4546-4080019520_2017-12-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/333", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/334", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4776-4080039730_2019-06-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/335", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4540-2080010300_2017-11-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/336", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-11-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/337", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4712-4080019680_2019-01-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/338", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-5_2017-05-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/339", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4576-6080014140_2018-02-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/340", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-1_2018-10-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/341", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4652-4080017550_2018-07-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/342", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-2_2018-10-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/343", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4848-1080036440_2019-12-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/344", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4216-4080020980_2014-12-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/345", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4620-7080053160_2018-05-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/346", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4648-1080024770_2018-07-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/347", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-11-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/348", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/349", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-29_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/350", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2016-12-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/351", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/352", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/353", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080011420_2020-01-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/354", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4862-2080017320_2020-01-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/355", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-4_2020-02-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/356", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4388-7080047210_2016-08-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/357", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/358", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4430-2080001360_2016-12-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/359", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4541-4080016210_2017-11-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/360", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/361", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080031900_2017-02-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080031900_2017-02-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/362", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4560-7080012660_2018-01-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/363", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4426-1080020040_2017-01-01_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/364", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/365", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4778-2080081250_2019-08-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/366", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/367", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080038230_2018-03-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/368", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-02-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/369", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/370", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/445-1_2020-06-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/371", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/372", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/373", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/374", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4207-1080030220_2014-12-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/375", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4488-4080014350_2017-06-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/376", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/377", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024430_2016-08-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/378", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4643-4080041500_2018-07-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/379", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/380", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/381", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/382", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080084350_2019-01-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/383", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-10-29_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/384", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4316-5080070850_2015-12-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/385", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-1_2017-05-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/386", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080023580_2016-06-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/387", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4809-6080001940_2019-10-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/388", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4758-7080005800_2019-06-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/389", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4859-5080009500_2020-01-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4859-5080009500_2020-01-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/390", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4631-1080023950_2018-06-18_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/391", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/392", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4821-6080000360_2019-10-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/393", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4655-4080736820_2018-07-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/394", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4695-7080006390_2018-10-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/395", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4716-1080011120_2019-01-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/396", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4650-1080023840_2018-07-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/397", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4276-6080015560_2015-07-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/398", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-1_2018-03-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/399", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4698-2080017430_2018-10-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/400", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4856-6080031480_2019-12-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/401", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/402", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4444-7080013530_2017-02-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/403", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4739-4080013340_2019-04-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/404", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019850_2018-03-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/405", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4788-1080029200_2019-08-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/406", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4834-7080007720_2019-11-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/407", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/408", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4217-5080026850_2014-12-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/409", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/410", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-09-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/411", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/411-1_2019-11-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/411-1_2019-11-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/412", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4396-4080011540_2016-09-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/413", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-02-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/414", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-5_2018-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-5_2018-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/415", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080053640_2017-10-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/416", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/417", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/418", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-02-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/419", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080029610_2019-01-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/420", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080012210_2020-01-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/421", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/422", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/423", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080026610_2015-07-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/424", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/425", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008470_2019-10-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/426", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/427", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/428", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080045890_2017-09-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/429", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/430", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4835-6080012280_2019-11-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/431", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/432", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4635-4080011960_2018-06-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/433", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4300-5080030230_2015-10-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4300-5080030230_2015-10-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/434", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/435", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4573-1080012680_2018-02-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/436", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4404-4080594470_2016-10-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/437", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-01-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/438", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4508-4080025450_2017-08-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/439", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4406-2080008250_2016-10-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/440", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/441", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024690_2016-07-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/442", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2017-01-01_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/443", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/444", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-18_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/445", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4851-1080007000_2019-12-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/446", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/447", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-3_2018-10-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-3_2018-10-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/448", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/449", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-10-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/450", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-2_2018-03-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/451", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4785-4080027840_2019-08-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/452", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4653-4080015000_2018-07-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/453", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/454", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080028470_2017-02-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080028470_2017-02-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/455", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4810-7080004480_2019-10-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/456", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/457", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-18_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/458", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-11-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/459", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/460", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-3_2020-02-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/461", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4472-1080008720_2017-05-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/462", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2018-12-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/463", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/464", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080011660_2019-05-01_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/465", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4555-5080025710_2017-12-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/466", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-1_2018-10-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/467", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4467-7080072180_2017-04-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/468", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4727-7080013800_2019-03-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/469", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4800-4080044180_2019-10-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/470", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008470_2019-10-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008470_2019-10-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/471", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080044350_2017-09-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/472", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/473", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/474", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4697-2080006250_2018-10-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/475", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/476", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2019-01-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/477", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4595-6080037030_2018-04-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/478", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-10-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/479", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-1_2015-02-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/480", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/130-6_2015-09-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/481", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4544-5080010420_2017-11-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/482", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4458-5080069590_2017-03-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/483", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-2_2018-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/484", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/485", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4451-5080071340_2017-03-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/486", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4598-1080009450_2018-04-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4598-1080009450_2018-04-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/487", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-4_2018-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/488", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008230_2019-11-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/489", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-2_2015-12-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/490", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4285-1080025470_2015-07-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/491", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-01-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/492", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4857-6080033560_2019-12-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/493", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/494", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4381-1080012810_2016-07-31_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/495", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4398-2080010990_2016-09-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/496", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/497", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/498", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080010030_2020-01-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/499", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4775-4080031520_2019-07-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/500", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/501", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/502", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029580_2017-02-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/503", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4504-5080084260_2017-07-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/504", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4649-1080023020_2018-07-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/505", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4446-1080013070_2017-02-25_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/506", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-3_2015-12-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/507", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-6_2018-04-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/508", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4917-1080032500_2020-05-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/509", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019010_2018-03-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/510", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4674-4080003500_2018-09-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-09-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/511", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4350-6080016300_2016-04-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/512", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/513", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-5_2018-04-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/514", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4748-7080048410_2019-05-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/515", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4429-4080015550_2016-12-18_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-18_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/516", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4520-4080043980_2017-09-18_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/517", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4634-4080029860_2018-06-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/518", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4691-6080001560_2018-10-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/519", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-11_2018-04-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/520", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4559-1080039620_2018-01-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/521", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/522", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022910_2019-10-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/523", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4427-6080018500_2016-12-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/524", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4497-4080043390_2017-07-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/525", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/526", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/174-1_2016-08-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/527", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4309-4080028760_2015-11-12_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/528", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4687-7080045890_2018-10-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/529", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/421-5_2020-01-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/530", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-2_2015-02-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/531", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080083100_2019-01-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/532", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-10-06_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/533", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4530-1080013200_2017-09-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4530-1080013200_2017-09-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/534", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/535", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4674-4080003500_2018-08-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4674-4080003500_2018-08-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/536", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-4_2018-10-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/537", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/538", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4664-2080004850_2018-08-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/539", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4479-6080011370_2017-05-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/540", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-1_2015-12-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/541", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/542", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080039740_2020-01-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/543", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4432-4080019410_2017-01-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/544", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4711-7080012950_2018-12-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/545", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4221-2080009900_2015-02-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4221-2080009900_2015-02-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/546", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4330-5080008500_2016-02-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/547", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/417-1_2019-12-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/548", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-01-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/549", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080070390_2020-02-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/550", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-11-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/551", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4260-1080023300_2015-06-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/552", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4771-7080047060_2019-07-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/553", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-10-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/554", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4498-4080032020_2017-07-17_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/555", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-3_2018-10-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/556", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4429-4080015550_2016-12-30_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4429-4080015550_2016-12-30_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/557", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4567-5080018390_2018-02-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/558", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4690-2080066030_2018-10-05_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/559", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-11-03_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/560", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-3_2018-03-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/561", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4500-4080015040_2017-08-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/562", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4676-7080042740_2018-09-26_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/563", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022200_2019-11-15_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/564", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-10-28_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/565", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080036020_2020-01-24_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/566", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080010590_2019-05-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/567", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4886-5080032110_2020-03-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/568", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-13_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/569", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4840-6080034250_2020-01-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/570", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4692-1080031290_2018-10-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/571", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4484-4080025260_2017-06-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/572", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/267-1_2018-02-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/573", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080038850_2020-01-21_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/574", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-10_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/575", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-1_2018-03-27_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/576", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-3_2018-03-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-3_2018-03-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/577", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4252-7080048080_2015-05-07_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/578", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4663-4080029720_2018-08-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/579", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4942-4080040230_2020-06-29_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/580", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4927-4080030920_2020-06-02_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/581", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4283-4080023060_2015-07-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/582", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-09-29_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/583", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4554-2080076100_2017-12-16_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/584", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4931-6080016720_2020-06-22_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/585", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-06-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/586", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4480-7080004990_2017-06-01_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/587", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4832-4080049680_2019-12-04_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/588", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080039250_2018-03-20_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/589", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080009880_2016-07-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/590", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080072120_2017-09-14_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/591", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4338-4080012280_2016-03-19_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4338-4080012280_2016-03-19_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/592", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080033560_2019-04-08_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080033560_2019-04-08_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/593", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007260_2020-04-23_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/594", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4502-4080001240_2017-08-09_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Detecting/595", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-11_5.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_351_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_351_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_351_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_351_precip.png" + ], + "Text": "The first image is the GloFAS dis24 data, which represents the forecasted river discharge in cubic meters per second (m^3/s). The second image is the ERA5 temperature data at 2 meters above ground level, measured in Kelvin (K). The third image is the volumetric soil water content in the top layer of the soil, measured in cubic meters per cubic meter (m^3/m^3). The fourth image is the snow depth water equivalent, measured in meters (m). The fifth image is the total precipitation sum, measured in millimeters (mm). Whether flood occurs in the region on the date shown in the images ?", + "Answer Choices": [ + "(A) Flooding occurs", + "(B) Flooding does not occur", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Detecting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Predicting.json b/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Predicting.json new file mode 100644 index 0000000000000000000000000000000000000000..033c8f85094449b45654acee29192877762e6b92 --- /dev/null +++ b/jsons/Cross-sphere/Global_Flood_Forecasting/Reasoning/Flood_Predicting.json @@ -0,0 +1,8035 @@ +[ + { + "Question_id": "Flood Predicting/0000", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-1080005420_2018-05-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-1080005420_2018-05-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-1080005420_2018-05-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4624-1080005420-2018-05-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0001", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-3_2017-05-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-3_2017-05-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-3_2017-05-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/205-3-2017-05-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0002", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080027560_2017-02-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4445-6080027560_2017-02-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4445-6080027560_2017-02-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4445-6080027560-2017-02-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0003", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4523-7080066100-2017-09-17-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0004", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4837-2080002070_2020-01-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4837-2080002070_2020-01-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4837-2080002070_2020-01-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4837-2080002070-2019-12-31-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0005", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4487-6080027290_2017-06-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4487-6080027290_2017-06-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4487-6080027290_2017-06-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4487-6080027290-2017-06-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0006", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-4_2018-10-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-4_2018-10-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-4_2018-10-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/324-4-2018-10-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0007", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4301-6080015940_2015-10-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4301-6080015940_2015-10-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4301-6080015940_2015-10-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4301-6080015940-2015-10-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0008", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4770-7080041050_2019-07-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4770-7080041050_2019-07-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4770-7080041050_2019-07-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4770-7080041050-2019-07-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0009", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-3_2018-03-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-3_2018-03-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-3_2018-03-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/277-3-2018-03-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0010", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4399-5080073410-2016-09-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0011", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4793-4080001880_2019-08-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4793-4080001880_2019-08-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4793-4080001880_2019-08-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4793-4080001880-2019-08-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0012", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4356-4080012790-2016-05-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0013", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-12-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-12-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-12-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4210-2080000350-2014-11-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0014", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080027200_2015-08-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080027200_2015-08-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080027200_2015-08-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4282-4080027200-2015-07-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0015", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-29_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-29_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-29_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4814-1080009040-2019-11-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0016", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4271-1080021690-2015-06-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0017", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-01-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0018", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4911-1080007940-2020-04-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0019", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-2_2018-03-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-2_2018-03-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-2_2018-03-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/277-2-2018-03-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0020", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4524-7080052330_2017-10-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4524-7080052330_2017-10-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4524-7080052330_2017-10-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4524-7080052330-2017-09-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0021", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4873-5080069540-2020-02-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0022", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4901-1080004700_2020-04-25_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4901-1080004700_2020-04-25_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4901-1080004700_2020-04-25_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4901-1080004700-2020-04-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0023", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-4_2017-05-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-4_2017-05-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-4_2017-05-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/205-4-2017-05-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0024", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4666-4080023830_2018-07-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4666-4080023830_2018-07-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4666-4080023830_2018-07-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4666-4080023830-2018-07-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0025", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4731-6080014360_2019-03-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4731-6080014360_2019-03-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4731-6080014360_2019-03-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4731-6080014360-2019-03-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0026", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-2_2018-10-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-2_2018-10-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-2_2018-10-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/321-2-2018-09-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0027", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4783-6080011630_2019-07-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4783-6080011630_2019-07-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4783-6080011630_2019-07-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4783-6080011630-2019-07-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0028", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-07-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080935520_2016-07-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080935520_2016-07-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4370-4080935520-2016-06-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0029", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/437-7_2020-05-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/437-7_2020-05-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/437-7_2020-05-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/437-7-2020-05-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0030", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0031", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-02-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0033", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-02-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-02-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-02-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4726-6080028290-2019-01-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0034", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4546-4080019520_2017-12-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4546-4080019520_2017-12-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4546-4080019520_2017-12-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4546-4080019520-2017-11-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0035", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-25_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-25_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-25_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4608-2080000430-2018-04-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0036", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4776-4080039730_2019-06-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4776-4080039730_2019-06-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4776-4080039730_2019-06-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4776-4080039730-2019-06-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0037", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4540-2080010300_2017-11-14_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4540-2080010300_2017-11-14_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4540-2080010300_2017-11-14_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4540-2080010300-2017-11-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0038", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-11-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-11-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-11-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4410-4080016080-2016-10-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0039", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4712-4080019680_2019-01-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4712-4080019680_2019-01-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4712-4080019680_2019-01-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4712-4080019680-2018-12-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0040", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-5_2017-05-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-5_2017-05-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-5_2017-05-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/205-5-2017-05-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0041", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4576-6080014140_2018-02-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4576-6080014140_2018-02-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4576-6080014140_2018-02-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4576-6080014140-2018-02-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0042", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-1_2018-10-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-1_2018-10-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-1_2018-10-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/321-1-2018-09-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0043", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4652-4080017550_2018-07-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4652-4080017550_2018-07-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4652-4080017550_2018-07-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4652-4080017550-2018-07-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0044", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-2_2018-10-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-2_2018-10-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-2_2018-10-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/324-2-2018-10-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0045", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4848-1080036440_2019-12-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4848-1080036440_2019-12-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4848-1080036440_2019-12-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4848-1080036440-2019-12-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0046", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4216-4080020980_2014-12-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4216-4080020980_2014-12-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4216-4080020980_2014-12-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4216-4080020980-2014-12-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0047", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4620-7080053160_2018-05-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4620-7080053160_2018-05-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4620-7080053160_2018-05-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4620-7080053160-2018-05-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0048", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4648-1080024770_2018-07-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4648-1080024770_2018-07-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4648-1080024770_2018-07-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4648-1080024770-2018-07-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0049", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-11-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-11-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-11-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4531-7080003100-2017-10-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0050", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4624-2080080570-2018-05-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0051", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-29_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-09-29_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-09-29_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4523-7080066100-2017-09-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0052", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2016-12-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2016-12-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2016-12-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4428-5080061660-2016-12-20-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0053", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0054", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080015260_2016-10-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080015260_2016-10-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4410-4080015260-2016-10-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0055", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080011420_2020-01-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080011420_2020-01-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080011420_2020-01-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4863-1080011420-2020-01-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0056", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4862-2080017320_2020-01-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4862-2080017320_2020-01-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4862-2080017320_2020-01-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4862-2080017320-2020-01-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0057", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-4_2020-02-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-4_2020-02-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-4_2020-02-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/427-4-2020-02-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0058", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4388-7080047210_2016-08-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4388-7080047210_2016-08-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4388-7080047210_2016-08-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4388-7080047210-2016-08-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0059", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4356-4080012790-2016-05-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0060", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4430-2080001360_2016-12-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4430-2080001360_2016-12-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4430-2080001360_2016-12-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4430-2080001360-2016-12-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0061", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4541-4080016210_2017-11-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4541-4080016210_2017-11-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4541-4080016210_2017-11-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4541-4080016210-2017-11-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0062", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4322-6080014230-2016-01-20-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0064", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4560-7080012660_2018-01-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4560-7080012660_2018-01-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4560-7080012660_2018-01-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4560-7080012660-2018-01-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0065", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4426-1080020040_2017-01-01_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4426-1080020040_2017-01-01_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4426-1080020040_2017-01-01_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4426-1080020040-2016-12-20-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0066", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4734-2080071890-2019-03-18-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0067", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4778-2080081250_2019-08-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4778-2080081250_2019-08-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4778-2080081250_2019-08-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4778-2080081250-2019-07-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0068", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-02-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0069", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080038230_2018-03-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080038230_2018-03-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080038230_2018-03-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4590-1080038230-2018-03-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0070", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-02-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-02-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-02-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4439-1080012410-2017-01-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0071", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4495-6080085240-2017-08-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0072", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/445-1_2020-06-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/445-1_2020-06-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/445-1_2020-06-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/445-1-2020-06-18-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0073", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-14_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-14_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-14_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4410-4080016080-2016-10-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0074", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4495-6080085240_2017-08-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4495-6080085240_2017-08-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4495-6080085240-2017-08-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0075", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-03-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0076", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4207-1080030220_2014-12-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4207-1080030220_2014-12-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4207-1080030220_2014-12-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4207-1080030220-2014-11-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0077", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4488-4080014350_2017-06-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4488-4080014350_2017-06-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4488-4080014350_2017-06-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4488-4080014350-2017-06-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0078", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4607-6080017100-2018-03-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0079", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024430_2016-08-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024430_2016-08-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024430_2016-08-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4365-4080024430-2016-07-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0080", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4643-4080041500_2018-07-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4643-4080041500_2018-07-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4643-4080041500_2018-07-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4643-4080041500-2018-06-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0081", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4356-4080012790-2016-05-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0082", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4710-2080045130-2018-12-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0083", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-25_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-25_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-25_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4529-4080018070-2017-10-20-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0084", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080084350_2019-01-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080084350_2019-01-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080084350_2019-01-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4717-2080084350-2019-01-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0085", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-10-29_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080003100_2017-10-29_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080003100_2017-10-29_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4531-7080003100-2017-10-17-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0086", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4316-5080070850_2015-12-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4316-5080070850_2015-12-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4316-5080070850_2015-12-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4316-5080070850-2015-12-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0087", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-1_2017-05-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/205-1_2017-05-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/205-1_2017-05-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/205-1-2017-05-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0088", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080023580_2016-06-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080023580_2016-06-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080023580_2016-06-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4365-4080023580-2016-05-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0089", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4809-6080001940_2019-10-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4809-6080001940_2019-10-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4809-6080001940_2019-10-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4809-6080001940-2019-10-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0090", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4758-7080005800_2019-06-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4758-7080005800_2019-06-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4758-7080005800_2019-06-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4758-7080005800-2019-05-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0092", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4631-1080023950_2018-06-18_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4631-1080023950_2018-06-18_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4631-1080023950_2018-06-18_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4631-1080023950-2018-06-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0093", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4579-5080067870-2018-03-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0094", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4821-6080000360_2019-10-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4821-6080000360_2019-10-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4821-6080000360_2019-10-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4821-6080000360-2019-10-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0095", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4655-4080736820_2018-07-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4655-4080736820_2018-07-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4655-4080736820_2018-07-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4655-4080736820-2018-07-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0096", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4695-7080006390_2018-10-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4695-7080006390_2018-10-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4695-7080006390_2018-10-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4695-7080006390-2018-10-17-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0097", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4716-1080011120_2019-01-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4716-1080011120_2019-01-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4716-1080011120_2019-01-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4716-1080011120-2019-01-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0098", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4650-1080023840_2018-07-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4650-1080023840_2018-07-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4650-1080023840_2018-07-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4650-1080023840-2018-07-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0099", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4276-6080015560_2015-07-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4276-6080015560_2015-07-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4276-6080015560_2015-07-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4276-6080015560-2015-07-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0100", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-1_2018-03-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-1_2018-03-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-1_2018-03-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/275-1-2018-03-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0101", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4698-2080017430_2018-10-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4698-2080017430_2018-10-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4698-2080017430_2018-10-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4698-2080017430-2018-10-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0102", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4856-6080031480_2019-12-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4856-6080031480_2019-12-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4856-6080031480_2019-12-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4856-6080031480-2019-12-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0103", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080029310-2017-02-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0104", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4444-7080013530_2017-02-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4444-7080013530_2017-02-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4444-7080013530_2017-02-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4444-7080013530-2017-02-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0105", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4739-4080013340_2019-04-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4739-4080013340_2019-04-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4739-4080013340_2019-04-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4739-4080013340-2019-03-31-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0106", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019850_2018-03-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019850_2018-03-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019850_2018-03-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4586-1080019850-2018-02-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0107", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4788-1080029200_2019-08-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4788-1080029200_2019-08-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4788-1080029200_2019-08-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4788-1080029200-2019-08-18-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0108", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4834-7080007720_2019-11-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4834-7080007720_2019-11-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4834-7080007720_2019-11-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4834-7080007720-2019-11-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0109", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029310_2017-03-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029310_2017-03-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080029310-2017-03-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0110", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4217-5080026850_2014-12-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4217-5080026850_2014-12-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4217-5080026850_2014-12-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4217-5080026850-2014-12-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0112", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-09-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-09-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-09-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4523-7080073100-2017-09-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0114", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4396-4080011540_2016-09-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4396-4080011540_2016-09-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4396-4080011540_2016-09-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4396-4080011540-2016-09-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0115", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-02-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-02-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-02-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4443-4080020620-2017-01-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0117", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080053640_2017-10-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4531-7080053640_2017-10-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4531-7080053640_2017-10-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4531-7080053640-2017-10-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0118", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4564-1080010870-2018-01-20-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0119", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4701-2080047410-2018-11-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0120", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-02-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-02-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-02-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4607-6080017100-2018-02-27-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0121", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080029610_2019-01-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080029610_2019-01-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080029610_2019-01-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4726-6080029610-2019-01-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0122", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080012210_2020-01-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080012210_2020-01-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080012210_2020-01-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4863-1080012210-2020-01-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0123", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4710-2080045130_2018-12-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4710-2080045130_2018-12-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4710-2080045130-2018-12-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0124", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4723-2080045510-2019-02-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0125", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080026610_2015-07-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4282-4080026610_2015-07-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4282-4080026610_2015-07-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4282-4080026610-2015-07-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0126", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4618-7080041400-2018-05-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0128", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4564-1080010870-2018-02-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0129", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-03-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-03-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-03-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0130", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080045890_2017-09-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080045890_2017-09-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080045890_2017-09-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4516-7080045890-2017-09-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0131", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4579-5080067870_2018-03-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4579-5080067870_2018-03-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4579-5080067870-2018-02-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0132", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4835-6080012280_2019-11-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4835-6080012280_2019-11-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4835-6080012280_2019-11-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4835-6080012280-2019-11-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0133", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4608-2080000430_2018-04-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4608-2080000430_2018-04-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4608-2080000430-2018-04-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0134", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4635-4080011960_2018-06-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4635-4080011960_2018-06-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4635-4080011960_2018-06-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4635-4080011960-2018-06-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0136", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-01-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-01-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4564-1080010870-2018-01-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0137", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4573-1080012680_2018-02-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4573-1080012680_2018-02-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4573-1080012680_2018-02-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4573-1080012680-2018-02-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0138", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4404-4080594470_2016-10-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4404-4080594470_2016-10-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4404-4080594470_2016-10-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4404-4080594470-2016-10-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0139", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-01-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4726-6080028290_2019-01-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4726-6080028290_2019-01-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4726-6080028290-2019-01-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0140", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4508-4080025450_2017-08-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4508-4080025450_2017-08-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4508-4080025450_2017-08-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4508-4080025450-2017-07-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0141", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4406-2080008250_2016-10-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4406-2080008250_2016-10-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4406-2080008250_2016-10-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4406-2080008250-2016-10-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0142", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007940_2020-04-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007940_2020-04-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4911-1080007940-2020-04-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0143", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024690_2016-07-14_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4365-4080024690_2016-07-14_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4365-4080024690_2016-07-14_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4365-4080024690-2016-05-27-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0144", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2017-01-01_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4428-5080061660_2017-01-01_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4428-5080061660_2017-01-01_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4428-5080061660-2016-12-27-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0145", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4607-6080017100-2018-03-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0146", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-18_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4734-2080071890_2019-03-18_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4734-2080071890_2019-03-18_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4734-2080071890-2019-03-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0147", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4851-1080007000_2019-12-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4851-1080007000_2019-12-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4851-1080007000_2019-12-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4851-1080007000-2019-11-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0148", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4701-2080047410_2018-11-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4701-2080047410_2018-11-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4701-2080047410-2018-10-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0150", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4322-6080014230_2016-01-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4322-6080014230_2016-01-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4322-6080014230-2016-01-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0151", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-10-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-10-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-10-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4525-7080049270-2017-09-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0152", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-2_2018-03-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/275-2_2018-03-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/275-2_2018-03-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/275-2-2018-03-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0153", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4785-4080027840_2019-08-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4785-4080027840_2019-08-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4785-4080027840_2019-08-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4785-4080027840-2019-07-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0154", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4653-4080015000_2018-07-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4653-4080015000_2018-07-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4653-4080015000_2018-07-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4653-4080015000-2018-07-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0155", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4410-4080016080_2016-10-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4410-4080016080_2016-10-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4410-4080016080-2016-10-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0157", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4810-7080004480_2019-10-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4810-7080004480_2019-10-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4810-7080004480_2019-10-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4810-7080004480-2019-09-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0158", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4529-4080018070_2017-10-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4529-4080018070_2017-10-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4529-4080018070-2017-10-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0159", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-18_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-18_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-18_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0160", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-11-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4210-2080000350_2014-11-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4210-2080000350_2014-11-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4210-2080000350-2014-11-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0161", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4607-6080017100_2018-03-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4607-6080017100_2018-03-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4607-6080017100-2018-02-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0162", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-3_2020-02-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/427-3_2020-02-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/427-3_2020-02-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/427-3-2020-02-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0163", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4472-1080008720_2017-05-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4472-1080008720_2017-05-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4472-1080008720_2017-05-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4472-1080008720-2017-05-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0164", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2018-12-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2018-12-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2018-12-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4713-5080027710-2018-12-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0165", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080069540_2020-02-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080069540_2020-02-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4873-5080069540-2020-02-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0166", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080011660_2019-05-01_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080011660_2019-05-01_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080011660_2019-05-01_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4745-1080011660-2019-04-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0167", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4555-5080025710_2017-12-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4555-5080025710_2017-12-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4555-5080025710_2017-12-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4555-5080025710-2017-12-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0168", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-1_2018-10-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-1_2018-10-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-1_2018-10-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/324-1-2018-10-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0169", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4467-7080072180_2017-04-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4467-7080072180_2017-04-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4467-7080072180_2017-04-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4467-7080072180-2017-04-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0170", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4727-7080013800_2019-03-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4727-7080013800_2019-03-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4727-7080013800_2019-03-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4727-7080013800-2019-02-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0171", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4800-4080044180_2019-10-14_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4800-4080044180_2019-10-14_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4800-4080044180_2019-10-14_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4800-4080044180-2019-10-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0173", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080044350_2017-09-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080044350_2017-09-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080044350_2017-09-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4516-7080044350-2017-08-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0174", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080030790_2017-02-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080030790_2017-02-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080030790-2017-02-09-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0175", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4723-2080045510_2019-02-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4723-2080045510_2019-02-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4723-2080045510-2019-02-07-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0176", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4697-2080006250_2018-10-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4697-2080006250_2018-10-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4697-2080006250_2018-10-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4697-2080006250-2018-10-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0177", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4461-5080086640-2017-04-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0178", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2019-01-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4713-5080027710_2019-01-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4713-5080027710_2019-01-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4713-5080027710-2018-12-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0179", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4595-6080037030_2018-04-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4595-6080037030_2018-04-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4595-6080037030_2018-04-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4595-6080037030-2018-03-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0180", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-10-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-10-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-10-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4816-2080065960-2019-10-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0181", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-1_2015-02-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-1_2015-02-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-1_2015-02-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/118-1-2015-01-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0182", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/130-6_2015-09-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/130-6_2015-09-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/130-6_2015-09-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/130-6-2015-04-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0183", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4544-5080010420_2017-11-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4544-5080010420_2017-11-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4544-5080010420_2017-11-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4544-5080010420-2017-11-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0184", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4458-5080069590_2017-03-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4458-5080069590_2017-03-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4458-5080069590_2017-03-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4458-5080069590-2017-03-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0185", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-2_2018-03-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-2_2018-03-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-2_2018-03-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/273-2-2018-02-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0186", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4814-1080009040_2019-11-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4814-1080009040_2019-11-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4814-1080009040-2019-11-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0187", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4451-5080071340_2017-03-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4451-5080071340_2017-03-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4451-5080071340_2017-03-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4451-5080071340-2017-03-09-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0189", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-4_2018-03-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-4_2018-03-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-4_2018-03-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/273-4-2018-02-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0190", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008230_2019-11-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4818-1080008230_2019-11-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4818-1080008230_2019-11-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4818-1080008230-2019-11-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0191", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-2_2015-12-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-2_2015-12-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-2_2015-12-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/147-2-2015-11-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0192", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4285-1080025470_2015-07-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4285-1080025470_2015-07-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4285-1080025470_2015-07-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4285-1080025470-2015-07-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0193", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-01-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4439-1080012410_2017-01-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4439-1080012410_2017-01-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4439-1080012410-2016-12-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0194", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4857-6080033560_2019-12-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4857-6080033560_2019-12-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4857-6080033560_2019-12-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4857-6080033560-2019-11-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0195", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4402-7080043160-2016-10-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0196", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4381-1080012810_2016-07-31_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4381-1080012810_2016-07-31_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4381-1080012810_2016-07-31_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4381-1080012810-2016-07-24-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0197", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4398-2080010990_2016-09-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4398-2080010990_2016-09-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4398-2080010990_2016-09-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4398-2080010990-2016-09-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0198", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4271-1080021690_2015-06-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4271-1080021690_2015-06-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4271-1080021690-2015-06-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0199", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-05-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-05-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4356-4080012790-2016-05-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0200", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080010030_2020-01-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4863-1080010030_2020-01-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4863-1080010030_2020-01-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4863-1080010030-2020-01-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0201", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4775-4080031520_2019-07-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4775-4080031520_2019-07-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4775-4080031520_2019-07-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4775-4080031520-2019-06-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0202", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4738-6080000240-2019-04-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0203", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4624-2080080570_2018-05-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4624-2080080570_2018-05-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4624-2080080570-2018-05-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0204", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029580_2017-02-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4450-6080029580_2017-02-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4450-6080029580_2017-02-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4450-6080029580-2017-01-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0205", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4504-5080084260_2017-07-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4504-5080084260_2017-07-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4504-5080084260_2017-07-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4504-5080084260-2017-07-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0206", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4649-1080023020_2018-07-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4649-1080023020_2018-07-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4649-1080023020_2018-07-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4649-1080023020-2018-07-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0207", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4446-1080013070_2017-02-25_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4446-1080013070_2017-02-25_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4446-1080013070_2017-02-25_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4446-1080013070-2017-02-18-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0208", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-3_2015-12-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-3_2015-12-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-3_2015-12-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/147-3-2015-11-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0209", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-6_2018-04-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-6_2018-04-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-6_2018-04-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/279-6-2018-04-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0210", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4917-1080032500_2020-05-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4917-1080032500_2020-05-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4917-1080032500_2020-05-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4917-1080032500-2020-05-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0211", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019010_2018-03-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4586-1080019010_2018-03-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4586-1080019010_2018-03-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4586-1080019010-2018-02-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0213", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4350-6080016300_2016-04-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4350-6080016300_2016-04-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4350-6080016300_2016-04-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4350-6080016300-2016-03-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0214", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4738-6080000240_2019-04-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4738-6080000240_2019-04-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4738-6080000240-2019-03-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0215", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-5_2018-04-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-5_2018-04-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-5_2018-04-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/279-5-2018-04-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0216", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4748-7080048410_2019-05-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4748-7080048410_2019-05-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4748-7080048410_2019-05-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4748-7080048410-2019-05-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0218", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4520-4080043980_2017-09-18_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4520-4080043980_2017-09-18_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4520-4080043980_2017-09-18_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4520-4080043980-2017-09-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0219", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4634-4080029860_2018-06-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4634-4080029860_2018-06-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4634-4080029860_2018-06-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4634-4080029860-2018-06-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0220", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4691-6080001560_2018-10-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4691-6080001560_2018-10-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4691-6080001560_2018-10-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4691-6080001560-2018-10-02-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0221", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-11_2018-04-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/279-11_2018-04-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/279-11_2018-04-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/279-11-2018-04-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0222", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4559-1080039620_2018-01-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4559-1080039620_2018-01-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4559-1080039620_2018-01-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4559-1080039620-2017-12-31-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0223", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4402-7080043160_2016-10-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4402-7080043160_2016-10-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4402-7080043160-2016-10-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0224", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022910_2019-10-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022910_2019-10-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022910_2019-10-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4820-1080022910-2019-10-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0225", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4427-6080018500_2016-12-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4427-6080018500_2016-12-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4427-6080018500_2016-12-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4427-6080018500-2016-12-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0226", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4497-4080043390_2017-07-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4497-4080043390_2017-07-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4497-4080043390_2017-07-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4497-4080043390-2017-07-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0227", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4564-1080010870_2018-02-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4564-1080010870_2018-02-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4564-1080010870-2018-02-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0228", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/174-1_2016-08-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/174-1_2016-08-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/174-1_2016-08-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/174-1-2016-07-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0229", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4309-4080028760_2015-11-12_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4309-4080028760_2015-11-12_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4309-4080028760_2015-11-12_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4309-4080028760-2015-10-31-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0230", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4687-7080045890_2018-10-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4687-7080045890_2018-10-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4687-7080045890_2018-10-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4687-7080045890-2018-10-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0231", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/421-5_2020-01-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/421-5_2020-01-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/421-5_2020-01-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/421-5-2020-01-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0232", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-2_2015-02-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/118-2_2015-02-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/118-2_2015-02-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/118-2-2015-01-21-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0233", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080083100_2019-01-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4717-2080083100_2019-01-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4717-2080083100_2019-01-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4717-2080083100-2019-01-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0234", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-10-06_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080066100_2017-10-06_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080066100_2017-10-06_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4523-7080066100-2017-09-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0236", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-18-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0238", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-4_2018-10-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/321-4_2018-10-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/321-4_2018-10-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/321-4-2018-09-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0239", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4461-5080086640_2017-04-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4461-5080086640_2017-04-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4461-5080086640-2017-04-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0240", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4664-2080004850_2018-08-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4664-2080004850_2018-08-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4664-2080004850_2018-08-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4664-2080004850-2018-08-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0241", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4479-6080011370_2017-05-30_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4479-6080011370_2017-05-30_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4479-6080011370_2017-05-30_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4479-6080011370-2017-05-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0242", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-1_2015-12-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/147-1_2015-12-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/147-1_2015-12-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/147-1-2015-12-01-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0243", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0244", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080039740_2020-01-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080039740_2020-01-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080039740_2020-01-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4867-1080039740-2020-01-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0245", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4432-4080019410_2017-01-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4432-4080019410_2017-01-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4432-4080019410_2017-01-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4432-4080019410-2016-12-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0246", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4711-7080012950_2018-12-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4711-7080012950_2018-12-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4711-7080012950_2018-12-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4711-7080012950-2018-11-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0248", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4330-5080008500_2016-02-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4330-5080008500_2016-02-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4330-5080008500_2016-02-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4330-5080008500-2016-01-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0249", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/417-1_2019-12-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/417-1_2019-12-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/417-1_2019-12-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/417-1-2019-12-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0250", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-01-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4443-4080020620_2017-01-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4443-4080020620_2017-01-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4443-4080020620-2017-01-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0251", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080070390_2020-02-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4873-5080070390_2020-02-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4873-5080070390_2020-02-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4873-5080070390-2020-02-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0252", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-11-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080065960_2019-11-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080065960_2019-11-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4816-2080065960-2019-10-31-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0253", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4260-1080023300_2015-06-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4260-1080023300_2015-06-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4260-1080023300_2015-06-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4260-1080023300-2015-05-26-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0254", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4771-7080047060_2019-07-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4771-7080047060_2019-07-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4771-7080047060_2019-07-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4771-7080047060-2019-06-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0255", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-10-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4523-7080073100_2017-10-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4523-7080073100_2017-10-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4523-7080073100-2017-09-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0256", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4498-4080032020_2017-07-17_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4498-4080032020_2017-07-17_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4498-4080032020_2017-07-17_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4498-4080032020-2017-07-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0257", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-3_2018-10-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/324-3_2018-10-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/324-3_2018-10-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/324-3-2018-10-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0259", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4567-5080018390_2018-02-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4567-5080018390_2018-02-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4567-5080018390_2018-02-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4567-5080018390-2018-01-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0260", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4690-2080066030_2018-10-05_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4690-2080066030_2018-10-05_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4690-2080066030_2018-10-05_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4690-2080066030-2018-09-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0261", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-11-03_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-11-03_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-11-03_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4816-2080070610-2019-10-29-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0262", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-3_2018-03-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/273-3_2018-03-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/273-3_2018-03-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/273-3-2018-02-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0263", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4500-4080015040_2017-08-08_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4500-4080015040_2017-08-08_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4500-4080015040_2017-08-08_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4500-4080015040-2017-07-27-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0264", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4676-7080042740_2018-09-26_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4676-7080042740_2018-09-26_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4676-7080042740_2018-09-26_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4676-7080042740-2018-09-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0265", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022200_2019-11-15_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4820-1080022200_2019-11-15_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4820-1080022200_2019-11-15_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4820-1080022200-2019-11-10-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0266", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-10-28_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4816-2080070610_2019-10-28_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4816-2080070610_2019-10-28_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4816-2080070610-2019-10-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0267", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080036020_2020-01-24_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080036020_2020-01-24_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080036020_2020-01-24_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4867-1080036020-2020-01-19-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0268", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080010590_2019-05-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4745-1080010590_2019-05-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4745-1080010590_2019-05-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4745-1080010590-2019-04-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0269", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4886-5080032110_2020-03-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4886-5080032110_2020-03-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4886-5080032110_2020-03-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4886-5080032110-2020-03-03-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0270", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-13_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4616-2080004280_2018-05-13_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4616-2080004280_2018-05-13_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4616-2080004280-2018-05-12-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0271", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4840-6080034250_2020-01-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4840-6080034250_2020-01-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4840-6080034250_2020-01-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4840-6080034250-2019-12-23-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0272", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4692-1080031290_2018-10-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4692-1080031290_2018-10-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4692-1080031290_2018-10-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4692-1080031290-2018-10-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0273", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4484-4080025260_2017-06-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4484-4080025260_2017-06-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4484-4080025260_2017-06-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4484-4080025260-2017-06-06-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0274", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/267-1_2018-02-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/267-1_2018-02-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/267-1_2018-02-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/267-1-2018-01-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0275", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080038850_2020-01-21_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4867-1080038850_2020-01-21_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4867-1080038850_2020-01-21_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4867-1080038850-2020-01-14-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0276", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-10_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4618-7080041400_2018-05-10_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4618-7080041400_2018-05-10_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4618-7080041400-2018-05-05-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0277", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-1_2018-03-27_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/277-1_2018-03-27_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/277-1_2018-03-27_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/277-1-2018-03-15-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0279", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4252-7080048080_2015-05-07_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4252-7080048080_2015-05-07_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4252-7080048080_2015-05-07_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4252-7080048080-2015-04-30-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0280", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4663-4080029720_2018-08-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4663-4080029720_2018-08-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4663-4080029720_2018-08-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4663-4080029720-2018-07-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0281", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4942-4080040230_2020-06-29_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4942-4080040230_2020-06-29_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4942-4080040230_2020-06-29_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4942-4080040230-2020-06-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0282", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4927-4080030920_2020-06-02_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4927-4080030920_2020-06-02_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4927-4080030920_2020-06-02_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4927-4080030920-2020-05-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0283", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4283-4080023060_2015-07-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4283-4080023060_2015-07-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4283-4080023060_2015-07-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4283-4080023060-2015-06-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0284", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-09-29_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4525-7080049270_2017-09-29_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4525-7080049270_2017-09-29_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4525-7080049270-2017-09-17-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0285", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4554-2080076100_2017-12-16_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4554-2080076100_2017-12-16_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4554-2080076100_2017-12-16_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4554-2080076100-2017-12-09-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0286", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4931-6080016720_2020-06-22_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4931-6080016720_2020-06-22_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4931-6080016720_2020-06-22_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4931-6080016720-2020-06-16-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0287", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-06-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4356-4080012790_2016-06-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4356-4080012790_2016-06-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4356-4080012790-2016-05-28-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0288", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4480-7080004990_2017-06-01_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4480-7080004990_2017-06-01_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4480-7080004990_2017-06-01_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4480-7080004990-2017-05-25-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0289", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4832-4080049680_2019-12-04_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4832-4080049680_2019-12-04_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4832-4080049680_2019-12-04_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4832-4080049680-2019-11-22-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0290", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080039250_2018-03-20_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4590-1080039250_2018-03-20_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4590-1080039250_2018-03-20_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4590-1080039250-2018-03-13-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0291", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080009880_2016-07-19_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4370-4080009880_2016-07-19_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4370-4080009880_2016-07-19_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4370-4080009880-2016-06-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0292", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080072120_2017-09-14_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4516-7080072120_2017-09-14_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4516-7080072120_2017-09-14_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4516-7080072120-2017-09-08-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0295", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007260_2020-04-23_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4911-1080007260_2020-04-23_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4911-1080007260_2020-04-23_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4911-1080007260-2020-04-11-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0296", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4502-4080001240_2017-08-09_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4502-4080001240_2017-08-09_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4502-4080001240_2017-08-09_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4502-4080001240-2017-08-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + }, + { + "Question_id": "Flood Predicting/0297", + "Images": [ + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-11_17.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/glofas/4399-5080073410_2016-09-11_18.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_363_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_364_temperature.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_363_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_364_soil_water.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_363_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_364_snow.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_363_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/era5/4399-5080073410_2016-09-11_364_precip.png", + "raw/Cross-sphere/Global_Flood_Forecasting/dataset/s1/4399-5080073410-2016-09-04-s1.png" + ], + "Text": "The first and second images are the GloFAS dis24 data on 2 consecutive dates, which represents the forecasted river discharge in cubic meters per second (m^3/s). The third and fourth images are the ERA5 temperature data at 2 meters above ground level on 2 consecutive dates, measured in Kelvin (K). The fifth and sixth images are the volumetric soil water content in the top layer of the soil on 2 consecutive dates, measured in cubic meters per cubic meter (m^3/m^3). The seventh and eighth images are the snow depth water equivalent on 2 consecutive dates, measured in meters (m). The ninth and tenth images are the total precipitation sum on 2 consecutive dates, measured in millimeters (mm). The eleventh image is the Sentinel-1 data, with vv and vh bands. Whether flood will occur in the region on the next date shown in the images ?", + "Answer Choices": [ + "(A) Flooding will occur", + "(B) Flooding will not occur", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Cross-sphere", + "L2-task": "Global Flood Forecasting", + "L3-task": "Reasoning", + "L4-task": "Flood Predicting", + "Dataset": "Global Flood Forecasting", + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Glacier_analysis/Perception/Glacial_Lake_Recognition.json b/jsons/Cryosphere/Glacier_analysis/Perception/Glacial_Lake_Recognition.json new file mode 100644 index 0000000000000000000000000000000000000000..a6a95b5689ada02c511447670a0a6ac6b960c2d9 --- /dev/null +++ b/jsons/Cryosphere/Glacier_analysis/Perception/Glacial_Lake_Recognition.json @@ -0,0 +1,277 @@ +[ + { + "Question_id": "Glacial Lake Recognition/0", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "A", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/1", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/2", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "C", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/3", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_007.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/4", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "D", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_011.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_009.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/5", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_012.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_013.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/6", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/7", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, which one could most likely be the glacial lake?", + "Ground Truth": "C", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) The first image.", + "(B) The second image.", + "(C) Both.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_006.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/8", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, count total number of glacial lakes.", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 9", + "(D) 0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/9", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given one image, count total number of glacial lakes.", + "Ground Truth": "A", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 9", + "(D) 0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/10", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, count total number of glacial lakes.", + "Ground Truth": "A", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 9", + "(D) 0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_006.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_011.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacial Lake Recognition/11", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images, count total number of glacial lakes.", + "Ground Truth": "B", + "Dataset": "GlacialImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Perception", + "L4-task": "Glacial Lake Recognition", + "Answer Choices": [ + "(A) 2", + "(B) 4", + "(C) 7", + "(D) 0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_013.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Glacier_analysis/Reasoning/Glacier_Melting_Estimation.json b/jsons/Cryosphere/Glacier_analysis/Reasoning/Glacier_Melting_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..dfc4cc587b32de6982c555fbce55e019a275354f --- /dev/null +++ b/jsons/Cryosphere/Glacier_analysis/Reasoning/Glacier_Melting_Estimation.json @@ -0,0 +1,232 @@ +[ + { + "Question_id": "Glacier_Melting_Estimation/0001", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_011.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0002", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_012.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_013.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0003", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "C", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_012.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0004", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "C", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_014.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0005", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_016.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0006", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots that present the melting speed of the same glacier. The first plot is the observed melting rate. The second plot is the melting acceleration rate with color bar. Considering the last two plots, which one aligns best with observed melting rate?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier melting plot.", + "(B) The second glacier melting plot.", + "(C) Neither plot aligns with observed melting rate.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_010.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_019.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0007", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Considering the abient environment, which one would most likely to be in the melting state?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_003.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0008", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Considering the abient environment, which one would most likely to be in the melting state?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_008.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0009", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Considering the abient environment, which one would most likely to be in the melting state?", + "Ground Truth": "C", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Neither glacier is melting.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Glacier_Melting_Estimation/0010", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Considering the abient environment, which one would most likely to be in the melting state?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Glacier Melting Estimation", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Neither glacier is melting.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_006.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_003.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Glacier_analysis/Reasoning/Slide_Recognition.json b/jsons/Cryosphere/Glacier_analysis/Reasoning/Slide_Recognition.json new file mode 100644 index 0000000000000000000000000000000000000000..2f6f9cd68714dfbb3b3182046231cbd3ccde27bd --- /dev/null +++ b/jsons/Cryosphere/Glacier_analysis/Reasoning/Slide_Recognition.json @@ -0,0 +1,178 @@ +[ + { + "Question_id": "Slide_Recognition/0001", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Knowing that the melting glacier is more likely to slide, the glacier in which image has higher chance to slide?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacial_id_007.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0002", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Knowing that the melting glacier is more likely to slide, the glacier in which image has higher chance to slide?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_003.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0003", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Knowing that the melting glacier is more likely to slide, the glacier in which image has higher chance to slide?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0004", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two images of different glaciers. Knowing that the melting glacier is more likely to slide, the glacier in which image has higher chance to slide?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier image.", + "(B) The second glacier image.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_004.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0005", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given three plots of the same glaciers. The first plots is the annual thining of the glacier and the last two plots are the annual thining relative to the fisrt plot. Which one of the last two plots are more likely to slide?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier plot.", + "(B) The second glacier plot.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_020.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_021.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0006", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given three plots of the same glaciers. The first plots is the annual thining of the glacier and the last two plots are the annual thining relative to the fisrt plot. Which one of the last two plots are more likely to slide?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier plot.", + "(B) The second glacier plot.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_020.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_028.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0007", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots. The first plots indicates the location of three glaciers of Greenland. The last three plots present the longitutional melting profile of respective glaciers. Which one has the largest melting rate?", + "Ground Truth": "A", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier plot.", + "(B) The second glacier plot.", + "(C) The third glacier plot.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_030.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_031.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_032.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Slide_Recognition/0008", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given four plots. The first plots indicates the location of three glaciers of Greenland. The last three plots present the traverse melting profile of respective glaciers. Which one has the largest melting rate?", + "Ground Truth": "B", + "Dataset": "GlacierImage", + "L1-task": "Cryosphere", + "L2-task": "Glacier analysis", + "L3-task": "Reasoning", + "L4-task": "Slide Recognition", + "Answer Choices": [ + "(A) The first glacier plot.", + "(B) The second glacier plot.", + "(C) The third glacier plot.", + "(D) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_035.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_033.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/glacier_id_034.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIT.json b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIT.json new file mode 100644 index 0000000000000000000000000000000000000000..7d879d74d56e75faedda940d7a698b6051c866d5 --- /dev/null +++ b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIT.json @@ -0,0 +1,462 @@ +[ + { + "Question_id": "SIC_Estimate_SIT/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.978", + "(B) 1.640", + "(C) 0.965", + "(D) 1.304", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0002", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.024", + "(B) 1.456", + "(C) -1.78", + "(D) 1.965", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0003", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.598", + "(B) 1.244", + "(C) 1.219", + "(D) 1.886", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0004", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.998", + "(B) 1.246", + "(C) 1.734", + "(D) 1.007", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_007.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.144", + "(B) 1.827", + "(C) 1.265", + "(D) 1.534", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_010.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0006", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.595", + "(B) 1.973", + "(C) 1.701", + "(D) 1.359", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_011.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.779", + "(B) 2.016", + "(C) 1.285", + "(D) 0.987", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_013.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0008", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.467", + "(B) 1.102", + "(C) 1.594", + "(D) 1.734", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_015.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 0.946", + "(B) 1.775", + "(C) 1.369", + "(D) 1.052", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_017.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_018.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0010", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.026", + "(B) 1.735", + "(C) 1.648", + "(D) 1.349", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_019.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.978", + "(B) 1.640", + "(C) 0.965", + "(D) 1.281", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_021.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0012", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.024", + "(B) 1.456", + "(C) -1.78", + "(D) 1.965", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_023.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_024.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.562", + "(B) 1.144", + "(C) -0.989", + "(D) 1.890", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_025.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_026.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0014", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.998", + "(B) 1.246", + "(C) 1.683", + "(D) 1.007", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_027.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.124", + "(B) 1.227", + "(C) 1.782", + "(D) 1.534", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_030.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0016", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.495", + "(B) 1.173", + "(C) 1.801", + "(D) 1.643", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_031.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_032.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.679", + "(B) 2.113", + "(C) 1.21", + "(D) 0.883", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_033.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_034.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0018", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.467", + "(B) 1.302", + "(C) 1.594", + "(D) 1.052", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_035.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_036.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 0.946", + "(B) 1.134", + "(C) 1.469", + "(D) 1.02", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_037.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_038.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIT/0020", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice thickness (the second image). Considering the date of SIC map is the following day of the end of SIT trend plot, which choice would most likely to be the averaged SIT of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIT", + "Answer Choices": [ + "(A) 1.126", + "(B) 1.735", + "(C) 0.936", + "(D) 1.328", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_039.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_sit_id_040.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIV.json b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIV.json new file mode 100644 index 0000000000000000000000000000000000000000..44e890236caa4ff62300d98cf360da4485fb9e81 --- /dev/null +++ b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIC_Estimate_SIV.json @@ -0,0 +1,462 @@ +[ + { + "Question_id": "SIC_Estimate_SIV/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 13.214", + "(B) 16.529", + "(C) 12.250", + "(D) 22.41", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0002", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 11.89", + "(B) 23.645", + "(C) 17.746", + "(D) 20.323", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0003", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 18.789", + "(B) 21.796", + "(C) 15.240", + "(D) -2.4", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_005.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0004", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 11.75", + "(B) 14.682", + "(C) 22.58", + "(D) 10.774", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_007.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 22.871", + "(B) 19.235", + "(C) 20.679", + "(D) 14.37", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_010.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0006", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 12.685", + "(B) 18.582", + "(C) 21.430", + "(D) 13.228", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_011.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 12.984", + "(B) 21.74", + "(C) 10.015", + "(D) 13.695", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_013.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0008", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 5.515", + "(B) 9.798", + "(C) 15.649", + "(D) 20.14", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_015.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 13.347", + "(B) 20.364", + "(C) 5.044", + "(D) 17.79", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_017.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_018.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0010", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 23.86", + "(B) 17.779", + "(C) 15.484", + "(D) 11.591", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_019.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 16.447", + "(B) 13.529", + "(C) 11.253", + "(D) 21.11", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_021.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0012", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 12.89", + "(B) 22.615", + "(C) 17.446", + "(D) 20.069", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_023.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_024.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 17.789", + "(B) 22.21", + "(C) 15.240", + "(D) 12.4", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_025.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_026.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0014", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 11.75", + "(B) 22.929", + "(C) 18.58", + "(D) 10.774", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_027.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 20.171", + "(B) 19.035", + "(C) 22.664", + "(D) 13.37", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_030.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0016", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 12.385", + "(B) 17.433", + "(C) 21.131", + "(D) 13.828", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_031.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_032.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 12.284", + "(B) 20.704", + "(C) 10.115", + "(D) 8.603", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_033.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_034.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0018", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 4.069", + "(B) 8.798", + "(C) 13.649", + "(D) 19.34", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_035.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_036.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 3.692", + "(B) 20.634", + "(C) 5.034", + "(D) 17.89", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_037.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_038.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIC_Estimate_SIV/0020", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given one sea ice concentration map (the first image) and one plot for daily trend in sea ice volume (the second image). Considering the date of SIC map is the following day of the end of SIV trend plot, which choice would most likely to be the averaged SIV of the given SIC map?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIC Estimate SIV", + "Answer Choices": [ + "(A) 20.16", + "(B) 3.692", + "(C) 13.184", + "(D) 9.591", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_039.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_siv_id_040.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIT_Trend_Prediction.json b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIT_Trend_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..2fd150581dcdda406e32e90ce491ab69ce2bc651 --- /dev/null +++ b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIT_Trend_Prediction.json @@ -0,0 +1,692 @@ +[ + { + "Question_id": "SIT_Trend_Prediction/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 0.1", + "(B) 3.0", + "(C) 1.8", + "(D) 1.325", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_001.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0002", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.6", + "(B) 1.472", + "(C) 1.8", + "(D) 0.9", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0003", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.617", + "(B) 1.95", + "(C) 1.3", + "(D) 1.126", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_003.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0004", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.682", + "(B) 1.813", + "(C) 1.757", + "(D) 0.757", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.742", + "(B) 2.0", + "(C) 0.59", + "(D) 1.818", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0006", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.823", + "(B) 1.679", + "(C) 1.325", + "(D) 0.98", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.255", + "(B) 3.4", + "(C) 1.755", + "(D) 0.82", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_007.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0008", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.342", + "(B) 1.092", + "(C) 1.77", + "(D) 0.092", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.236", + "(B) 1.431", + "(C) 1.625", + "(D) 1.056", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_009.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0010", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.040", + "(B) 1.136", + "(C) 0.892", + "(D) 1.1", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_010.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.326", + "(B) 1.632", + "(C) 1.585", + "(D) 1.071", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_011.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0012", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.206", + "(B) 1.721", + "(C) 1.187", + "(D) 1.479", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.818", + "(B) 1.574", + "(C) 1.115", + "(D) 0.959", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_013.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0014", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.956", + "(B) 1.061", + "(C) 1.725", + "(D) 1.569", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.912", + "(B) 1.783", + "(C) 1.348", + "(D) 0.983", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0016", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.893", + "(B) 1.295", + "(C) 1.659", + "(D) 1.097", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.223", + "(B) 1.96", + "(C) 1.044", + "(D) 1.567", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_017.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0018", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.391", + "(B) 1.108", + "(C) 0.768", + "(D) 1.454", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_018.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.735", + "(B) 0.968", + "(C) 1.144", + "(D) 1.359", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_019.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0020", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.176", + "(B) 1.203", + "(C) 0.565", + "(D) 0.956", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0021", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.364", + "(B) 2.23", + "(C) 1.943", + "(D) 1.022", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_021.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0022", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.953", + "(B) 1.545", + "(C) 1.176", + "(D) 0.968", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0023", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) -1.5", + "(B) 1.597", + "(C) 1.134", + "(D) 1.896", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_023.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0024", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 0.977", + "(B) 1.014", + "(C) 1.749", + "(D) 1.563", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_024.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0025", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.134", + "(B) 1.443", + "(C) 1.862", + "(D) 2.076", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0026", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.963", + "(B) 1.673", + "(C) 1.043", + "(D) 1.224", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_026.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0027", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.787", + "(B) 1.411", + "(C) 1.024", + "(D) 1.122", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0028", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.447", + "(B) 1.546", + "(C) 1.967", + "(D) 1.136", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0029", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.397", + "(B) 1.113", + "(C) 1.711", + "(D) 0.559", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_029.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIT_Trend_Prediction/0030", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice thickness, the first plot is for the variation of SIT in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIT in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIT Trend Prediction", + "Answer Choices": [ + "(A) 1.038", + "(B) 1.980", + "(C) 1.346", + "(D) 0.774", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sit_id_030.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIV_Trend_Prediction.json b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIV_Trend_Prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..3929e57b03b721a1657c626977b8e56aeb99a7fd --- /dev/null +++ b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/SIV_Trend_Prediction.json @@ -0,0 +1,692 @@ +[ + { + "Question_id": "SIV_Trend_Prediction/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 8.7", + "(B) 13.262", + "(C) 17.72", + "(D) 16.613", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_001.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0002", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) -19.7", + "(B) 19.615", + "(C) 23.365", + "(D) 7.836", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0003", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 17.832", + "(B) 25.643", + "(C) 21.545", + "(D) 19.21", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_003.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0004", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 16.094", + "(B) 19.343", + "(C) 24.960", + "(D) 23.009", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 22.356", + "(B) 24.619", + "(C) 17.119", + "(D) 20.907", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0006", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 19.983", + "(B) 21.736", + "(C) 16.532", + "(D) 18.394", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 8.976", + "(B) 10.56", + "(C) 6.551", + "(D) 11.215", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_007.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0008", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 7.298", + "(B) 6.094", + "(C) 4.877", + "(D) 10.247", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 6.969", + "(B) 5.086", + "(C) 3.028", + "(D) 10.107", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_009.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0010", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 5.877", + "(B) 22.08", + "(C) 9.07", + "(D) 7.468", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_010.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 19.25", + "(B) 16.861", + "(C) 13.216", + "(D) 9.835", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_011.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0012", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 16.325", + "(B) 13.775", + "(C) 19.794", + "(D) 22.673", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 23.650", + "(B) 21.830", + "(C) 9.275", + "(D) 18.268", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_013.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0014", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 23.268", + "(B) 25.347", + "(C) 20.996", + "(D) 17.640", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 16.794", + "(B) 20.193", + "(C) 24.987", + "(D) 22.523", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0016", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 13.246", + "(B) 21.668", + "(C) 18.389", + "(D) 9.978", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) -9.546", + "(B) 8.271", + "(C) 12.29", + "(D) 18.771", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_017.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0018", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 0.875", + "(B) 3.974", + "(C) 9.823", + "(D) 7.776", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_018.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 12.830", + "(B) 3.932", + "(C) 1.027", + "(D) 5.342", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_019.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0020", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 10.49", + "(B) 3.879", + "(C) 7.954", + "(D) 11.52", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_002.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0021", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 16.211", + "(B) 18.962", + "(C) 13.335", + "(D) 9.687", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_021.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0022", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 23.53", + "(B) 22.95", + "(C) 19.972", + "(D) 13.569", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0023", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 20.879", + "(B) 23.454", + "(C) 18.221", + "(D) 17.339", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_023.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0024", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 24.73", + "(B) 19.560", + "(C) -10.6", + "(D) 22.506", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_024.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0025", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 17.068", + "(B) 21.521", + "(C) 15.329", + "(D) 9.726", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0026", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "A", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 16.778", + "(B) 26.123", + "(C) 13.775", + "(D) 10.684", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_026.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0027", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 15.629", + "(B) 11.251", + "(C) 8.772", + "(D) 20.647", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0028", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "B", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 19.264", + "(B) 5.484", + "(C) 2.774", + "(D) 9.568", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0029", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "D", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 9.936", + "(B) 24.579", + "(C) 12.58", + "(D) 4.579", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_029.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIV_Trend_Prediction/0030", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, you are given two plots of daily sea ice volume, the first plot is for the variation of SIV in the previous year and the second plot is for the next year. Given these two plots, which choice would most likely be the averaged SIV in the subsequent 7 days?", + "Ground Truth": "C", + "Dataset": "PIOMAS", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "SIV Trend Prediction", + "Answer Choices": [ + "(A) 18.774", + "(B) 12.560", + "(C) 8.369", + "(D) 3.709", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_pre_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/siv_id_030.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Cryosphere/Sea_ice_forecast/Reasoning/Sea_Ice_Extent_Estimation.json b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/Sea_Ice_Extent_Estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..9f8424977e1fb06c45e5ad4c8cfe6d7d601a95b7 --- /dev/null +++ b/jsons/Cryosphere/Sea_ice_forecast/Reasoning/Sea_Ice_Extent_Estimation.json @@ -0,0 +1,2196 @@ +[ + { + "Question_id": "SIE_Estimation/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 8.93", + "(B) 3.72", + "(C) -1.2", + "(D) 5.43", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_000.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0002", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 3.55", + "(B) 4.72", + "(C) 6.53", + "(D) 1.77", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0003", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 17.34", + "(B) 12.68", + "(C) 3.1", + "(D) -2.0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0004", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 14.2", + "(B) 13.34", + "(C) 16.1", + "(D) 5.23", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_007.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 8.93", + "(B) 3.72", + "(C) -1.2", + "(D) 5.43", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_008.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0006", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.66", + "(B) 9.71", + "(C) 11.03", + "(D) 13.52", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_009.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 3.53", + "(B) 7.81", + "(C) 13.53", + "(D) 11.02", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_010.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0008", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 16.89", + "(B) 8.96", + "(C) 18.79", + "(D) 11.02", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_011.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.33", + "(B) 13.1", + "(C) 14.68", + "(D) -2.4", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_012.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0010", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 15.62", + "(B) 23.9", + "(C) 5.63", + "(D) 18.79", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_013.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 11.2", + "(B) 5.29", + "(C) 7.1", + "(D) 0.9", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_014.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0012", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 9.31", + "(B) 11.75", + "(C) 5.63", + "(D) 14.26", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 12.72", + "(B) 19.26", + "(C) 15.1", + "(D) 16.63", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_016.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0014", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 4.37", + "(B) 12.35", + "(C) 0.69", + "(D) 2.46", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_017.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 13.12", + "(B) 15.50", + "(C) 16.71", + "(D) 10.53", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_018.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0016", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 14.91", + "(B) 12.65", + "(C) 18.75", + "(D) 3.46", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_019.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 12.09", + "(B) 14.46", + "(C) 15.21", + "(D) 17.3", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0018", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 5.77", + "(B) 12.35", + "(C) 16.73", + "(D) 3.62", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_021.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 9.67", + "(B) 7.98", + "(C) 5.1", + "(D) 3.43", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0020", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 5.75", + "(B) 8.95", + "(C) 4.43", + "(D) 12.26", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_023.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0021", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 11.742", + "(B) 15.11", + "(C) 13.28", + "(D) 17.63", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_024.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0022", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 3.17", + "(B) 18.25", + "(C) 10.21", + "(D) 2.6", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0023", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.55", + "(B) 17.21", + "(C) 5.7", + "(D) 2.33", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_026.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0024", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 4.17", + "(B) 12.95", + "(C) 0.19", + "(D) 2.76", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0025", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 14.92", + "(B) 12.16", + "(C) 2.16", + "(D) 10.23", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0026", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 3.39", + "(B) 7.48", + "(C) 2.9", + "(D) 5.36", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_029.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0027", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 15.79", + "(B) 12.94", + "(C) 10.05", + "(D) 8.43", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_030.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0028", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) -4.37", + "(B) 7.85", + "(C) 0.88", + "(D) 4.2", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_031.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0029", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.31", + "(B) 9.16", + "(C) 16.1", + "(D) 1.73", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_032.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0030", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 15.47", + "(B) 11.25", + "(C) 7.69", + "(D) 13.61", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_033.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0031", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 17.7", + "(B) 13.43", + "(C) 5.4", + "(D) 9.36", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_034.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0032", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 12.3", + "(B) 7.6", + "(C) 9.89", + "(D) 15.0", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_035.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0033", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 5.22", + "(B) 9.06", + "(C) 7.3", + "(D) 12.73", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_036.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0034", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 8.32", + "(B) 7.45", + "(C) 12.89", + "(D) 10.7", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_037.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0035", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 14.84", + "(B) 17.1", + "(C) 5.3", + "(D) 11.77", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_038.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0036", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) -17.39", + "(B) 17.39", + "(C) 13.77", + "(D) 9.26", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_039.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0037", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 0.95", + "(B) 19.15", + "(C) 9.15", + "(D) 6.63", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_040.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0038", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 8.34", + "(B) 19.45", + "(C) 16.44", + "(D) 6.84", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_041.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0039", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 12.7", + "(B) 9.56", + "(C) 13.97", + "(D) 15.86", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_042.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0040", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.57", + "(B) 10.75", + "(C) 47.57", + "(D) 5.46", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_043.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0041", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 18.42", + "(B) 17.16", + "(C) 15.51", + "(D) 9.3", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_044.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0042", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 6.37", + "(B) 9.73", + "(C) 7.81", + "(D) 4.26", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_045.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0043", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 7.2", + "(B) 3.35", + "(C) 0.97", + "(D) 1.46", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_046.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0044", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 13.58", + "(B) 23.79", + "(C) 9.62", + "(D) 6.73", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_047.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0045", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 9.77", + "(B) 16.55", + "(C) 11.4", + "(D) 19.76", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_048.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0046", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 4.78", + "(B) 14.81", + "(C) 17.32", + "(D) 16.53", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_049.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0047", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 16.29", + "(B) 12.95", + "(C) 14.97", + "(D) 12.77", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_050.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0048", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 14.85", + "(B) 13.6", + "(C) 15.63", + "(D) 9.6", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_051.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0049", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 1.32", + "(B) 15.32", + "(C) 7.54", + "(D) 5.74", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_052.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "SIE_Estimation/0050", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. Given the sea ice concentration map, estimate the sea ice extent in million square kilometers.", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) 12.92", + "(B) 17.9", + "(C) 10.91", + "(D) 11.63", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_053.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0001", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_001.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_002.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0002", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_054.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_055.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0003", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_056.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_057.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0004", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_058.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_059.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0005", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_060.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_061.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0006", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_062.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_063.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0007", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_064.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_065.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0008", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_066.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_067.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0009", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_068.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_069.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0010", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_070.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_071.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0011", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_072.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_073.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0012", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_074.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_075.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0013", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_076.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_077.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0014", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_078.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_079.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0015", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_080.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_081.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0016", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_082.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_083.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0017", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_084.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_085.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0018", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_086.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_087.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0019", + "Question_type": "Single Choice", + "Text": "As a pan-Arctic researcher, analyze sea ice extent in pan-Arctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_088.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_089.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0020", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_009.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_011.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0021", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_013.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0022", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_017.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_019.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0023", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_021.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_023.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0024", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_025.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0025", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_021.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0026", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_031.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_033.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0027", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_044.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_046.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0028", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent in Antarctic region. You are given two sea ice concentration maps, which one could be the sea ice extent in the melting season?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Unable to decide." + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_050.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_052.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0029", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent. You are given two sea ice concentration maps, one for Antarctic and the other for pan-Arctic region, which one could be the sea ice extent in the melting season?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_028.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_029.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Season_Estimation/0030", + "Question_type": "Single Choice", + "Text": "As a sea ice researcher, analyze sea ice extent. You are given two sea ice concentration maps, one for Antarctic and the other for pan-Arctic region, which one could be the sea ice extent in the melting season?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_039.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_040.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0001", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_004.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0002", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_019.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_089.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0003", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_003.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_005.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0004", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_013.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_007.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0005", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_050.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_027.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0006", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_030.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_035.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0007", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_086.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_066.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0008", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_044.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_028.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0009", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_006.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_017.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0010", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in Antarctic region?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_018.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_083.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0011", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_054.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_066.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0012", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_013.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_015.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0013", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "A", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_078.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_052.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0014", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_046.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_076.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0015", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_072.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_081.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0016", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_011.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_070.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0017", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "C", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_074.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_075.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0018", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_023.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0019", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "B", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_048.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_084.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Regional_Recognition/0020", + "Question_type": "Single Choice", + "Text": "As a geoscientist, you are given two sea ice concentration maps, which one describes the sea ice extent in pan-Arcric region?", + "Ground Truth": "D", + "Dataset": "G02202", + "L1-task": "Cryosphere", + "L2-task": "Sea ice forecast", + "L3-task": "Reasoning", + "L4-task": "Sea Ice Extent Estimation", + "Answer Choices": [ + "(A) The first sea ice concentration map.", + "(B) The second sea ice concentration map.", + "(C) Both sea ice concentration maps.", + "(D) Neither.", + "(E) Unable to decide" + ], + "Images": [ + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_029.png", + "raw/Cryosphere/CryosphereDataset_v1.1/images/sic_id_031.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/P-wave_phase_picking.json b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/P-wave_phase_picking.json new file mode 100644 index 0000000000000000000000000000000000000000..ddf04e850150697fc7ed1e892eaf44b7cfd9df17 --- /dev/null +++ b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/P-wave_phase_picking.json @@ -0,0 +1,6302 @@ +[ + { + "Question_id": "P-wave phase picking/0000", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1600", + "(B) 900", + "(C) 702", + "(D) 1066", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0000.png" + ] + }, + { + "Question_id": "P-wave phase picking/0001", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 573", + "(B) 1147", + "(C) 832", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0001.png" + ] + }, + { + "Question_id": "P-wave phase picking/0002", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 772", + "(B) 900", + "(C) 110", + "(D) 1078", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0002.png" + ] + }, + { + "Question_id": "P-wave phase picking/0003", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -58", + "(B) 959", + "(C) 650", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0003.png" + ] + }, + { + "Question_id": "P-wave phase picking/0004", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 629", + "(B) 946", + "(C) 798", + "(D) 1409", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0004.png" + ] + }, + { + "Question_id": "P-wave phase picking/0005", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 537", + "(B) 401", + "(C) 205", + "(D) 894", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0005.png" + ] + }, + { + "Question_id": "P-wave phase picking/0006", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 490", + "(C) 245", + "(D) 734", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0006.png" + ] + }, + { + "Question_id": "P-wave phase picking/0007", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 569", + "(B) 700", + "(C) 324", + "(D) 856", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0007.png" + ] + }, + { + "Question_id": "P-wave phase picking/0008", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 451", + "(C) 1450", + "(D) 760", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0008.png" + ] + }, + { + "Question_id": "P-wave phase picking/0009", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 380", + "(B) 488", + "(C) 670", + "(D) -507", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0009.png" + ] + }, + { + "Question_id": "P-wave phase picking/0010", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1550", + "(B) 485", + "(C) 747", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0010.png" + ] + }, + { + "Question_id": "P-wave phase picking/0011", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 968", + "(B) 800", + "(C) 655", + "(D) 1750", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0011.png" + ] + }, + { + "Question_id": "P-wave phase picking/0012", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 421", + "(B) 322", + "(C) 746", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0012.png" + ] + }, + { + "Question_id": "P-wave phase picking/0013", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 237", + "(B) 1217", + "(C) 537", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0013.png" + ] + }, + { + "Question_id": "P-wave phase picking/0014", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 656", + "(B) 1502", + "(C) 800", + "(D) 953", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0014.png" + ] + }, + { + "Question_id": "P-wave phase picking/0015", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 267", + "(B) 1122", + "(C) 589", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0015.png" + ] + }, + { + "Question_id": "P-wave phase picking/0016", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 748", + "(B) 484", + "(C) 1135", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0016.png" + ] + }, + { + "Question_id": "P-wave phase picking/0017", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 636", + "(B) 976", + "(C) 103", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0017.png" + ] + }, + { + "Question_id": "P-wave phase picking/0018", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1044", + "(B) 760", + "(C) 1441", + "(D) 901", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0018.png" + ] + }, + { + "Question_id": "P-wave phase picking/0019", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 322", + "(B) 500", + "(C) 1317", + "(D) 613", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0019.png" + ] + }, + { + "Question_id": "P-wave phase picking/0020", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1724", + "(B) 987", + "(C) 800", + "(D) 670", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0020.png" + ] + }, + { + "Question_id": "P-wave phase picking/0021", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1418", + "(B) 900", + "(C) 765", + "(D) 1058", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0021.png" + ] + }, + { + "Question_id": "P-wave phase picking/0022", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 335", + "(B) 1442", + "(C) 500", + "(D) 629", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0022.png" + ] + }, + { + "Question_id": "P-wave phase picking/0023", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 114", + "(C) 471", + "(D) 767", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0023.png" + ] + }, + { + "Question_id": "P-wave phase picking/0024", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1609", + "(B) 813", + "(C) 697", + "(D) 562", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0024.png" + ] + }, + { + "Question_id": "P-wave phase picking/0025", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 899", + "(B) 791", + "(C) 1813", + "(D) 1080", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0025.png" + ] + }, + { + "Question_id": "P-wave phase picking/0026", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 706", + "(C) 1554", + "(D) 1075", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0026.png" + ] + }, + { + "Question_id": "P-wave phase picking/0027", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 801", + "(B) 1000", + "(C) 1122", + "(D) 173", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0027.png" + ] + }, + { + "Question_id": "P-wave phase picking/0028", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 852", + "(B) 375", + "(C) 692", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0028.png" + ] + }, + { + "Question_id": "P-wave phase picking/0029", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 501", + "(B) 296", + "(C) 64", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0029.png" + ] + }, + { + "Question_id": "P-wave phase picking/0030", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 722", + "(B) 416", + "(C) 900", + "(D) 1063", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0030.png" + ] + }, + { + "Question_id": "P-wave phase picking/0031", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 874", + "(C) 560", + "(D) 100", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0031.png" + ] + }, + { + "Question_id": "P-wave phase picking/0032", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 932", + "(B) 1390", + "(C) 800", + "(D) 696", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0032.png" + ] + }, + { + "Question_id": "P-wave phase picking/0033", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 499", + "(B) 623", + "(C) 325", + "(D) 1303", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0033.png" + ] + }, + { + "Question_id": "P-wave phase picking/0034", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 492", + "(B) -212", + "(C) 600", + "(D) 743", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0034.png" + ] + }, + { + "Question_id": "P-wave phase picking/0035", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1029", + "(B) 1234", + "(C) 799", + "(D) 904", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0035.png" + ] + }, + { + "Question_id": "P-wave phase picking/0036", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1277", + "(B) 764", + "(C) 1085", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0036.png" + ] + }, + { + "Question_id": "P-wave phase picking/0037", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1579", + "(B) 600", + "(C) 799", + "(D) 425", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0037.png" + ] + }, + { + "Question_id": "P-wave phase picking/0038", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 718", + "(B) 261", + "(C) 586", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0038.png" + ] + }, + { + "Question_id": "P-wave phase picking/0039", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 493", + "(B) -333", + "(C) 390", + "(D) 615", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0039.png" + ] + }, + { + "Question_id": "P-wave phase picking/0040", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1033", + "(B) 757", + "(C) 366", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0040.png" + ] + }, + { + "Question_id": "P-wave phase picking/0041", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 479", + "(B) 1019", + "(C) 721", + "(D) 903", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0041.png" + ] + }, + { + "Question_id": "P-wave phase picking/0042", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 384", + "(B) 1000", + "(C) 1174", + "(D) 847", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0042.png" + ] + }, + { + "Question_id": "P-wave phase picking/0043", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1093", + "(B) 900", + "(C) 1426", + "(D) 761", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0043.png" + ] + }, + { + "Question_id": "P-wave phase picking/0044", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 613", + "(B) 500", + "(C) 338", + "(D) 105", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0044.png" + ] + }, + { + "Question_id": "P-wave phase picking/0045", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 277", + "(B) 830", + "(C) 700", + "(D) 550", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0045.png" + ] + }, + { + "Question_id": "P-wave phase picking/0046", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 59", + "(B) 900", + "(C) 761", + "(D) 1048", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0046.png" + ] + }, + { + "Question_id": "P-wave phase picking/0047", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 695", + "(B) 532", + "(C) 48", + "(D) 894", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0047.png" + ] + }, + { + "Question_id": "P-wave phase picking/0048", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1035", + "(C) 789", + "(D) 1472", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0048.png" + ] + }, + { + "Question_id": "P-wave phase picking/0049", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 599", + "(B) 863", + "(C) 417", + "(D) 760", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0049.png" + ] + }, + { + "Question_id": "P-wave phase picking/0050", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 966", + "(B) -150", + "(C) 800", + "(D) 606", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0050.png" + ] + }, + { + "Question_id": "P-wave phase picking/0051", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 686", + "(B) 799", + "(C) 324", + "(D) 976", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0051.png" + ] + }, + { + "Question_id": "P-wave phase picking/0052", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 619", + "(B) 430", + "(C) -380", + "(D) 727", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0052.png" + ] + }, + { + "Question_id": "P-wave phase picking/0053", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1390", + "(B) 900", + "(C) 1051", + "(D) 779", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0053.png" + ] + }, + { + "Question_id": "P-wave phase picking/0054", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 719", + "(B) 1010", + "(C) -87", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0054.png" + ] + }, + { + "Question_id": "P-wave phase picking/0055", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 535", + "(B) 800", + "(C) 912", + "(D) 612", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0055.png" + ] + }, + { + "Question_id": "P-wave phase picking/0056", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 613", + "(C) 961", + "(D) 1181", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0056.png" + ] + }, + { + "Question_id": "P-wave phase picking/0057", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1553", + "(C) 1035", + "(D) 705", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0057.png" + ] + }, + { + "Question_id": "P-wave phase picking/0058", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 730", + "(B) 1276", + "(C) 900", + "(D) 1051", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0058.png" + ] + }, + { + "Question_id": "P-wave phase picking/0059", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 222", + "(B) 599", + "(C) 400", + "(D) 1140", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0059.png" + ] + }, + { + "Question_id": "P-wave phase picking/0060", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1210", + "(B) 600", + "(C) 473", + "(D) 785", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0060.png" + ] + }, + { + "Question_id": "P-wave phase picking/0061", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 484", + "(B) 793", + "(C) 882", + "(D) 598", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0061.png" + ] + }, + { + "Question_id": "P-wave phase picking/0062", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 84", + "(B) 1050", + "(C) 784", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0062.png" + ] + }, + { + "Question_id": "P-wave phase picking/0063", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 538", + "(B) 215", + "(C) 406", + "(D) -542", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0063.png" + ] + }, + { + "Question_id": "P-wave phase picking/0064", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 201", + "(B) -315", + "(C) 400", + "(D) 593", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0064.png" + ] + }, + { + "Question_id": "P-wave phase picking/0065", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -105", + "(B) 600", + "(C) 491", + "(D) 769", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0065.png" + ] + }, + { + "Question_id": "P-wave phase picking/0066", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1060", + "(C) 793", + "(D) 501", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0066.png" + ] + }, + { + "Question_id": "P-wave phase picking/0067", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 446", + "(B) 600", + "(C) 726", + "(D) -233", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0067.png" + ] + }, + { + "Question_id": "P-wave phase picking/0068", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 199", + "(B) 398", + "(C) 518", + "(D) -481", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0068.png" + ] + }, + { + "Question_id": "P-wave phase picking/0069", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 721", + "(B) 1093", + "(C) 600", + "(D) 435", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0069.png" + ] + }, + { + "Question_id": "P-wave phase picking/0070", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1128", + "(B) 1342", + "(C) 1000", + "(D) 844", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0070.png" + ] + }, + { + "Question_id": "P-wave phase picking/0071", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1322", + "(B) 799", + "(C) 697", + "(D) 953", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0071.png" + ] + }, + { + "Question_id": "P-wave phase picking/0072", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 765", + "(C) 189", + "(D) 496", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0072.png" + ] + }, + { + "Question_id": "P-wave phase picking/0073", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 248", + "(B) 400", + "(C) 582", + "(D) 164", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0073.png" + ] + }, + { + "Question_id": "P-wave phase picking/0074", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 886", + "(B) -20", + "(C) 583", + "(D) 697", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0074.png" + ] + }, + { + "Question_id": "P-wave phase picking/0075", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 400", + "(B) 214", + "(C) -173", + "(D) 543", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0075.png" + ] + }, + { + "Question_id": "P-wave phase picking/0076", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 902", + "(B) 800", + "(C) 618", + "(D) 264", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0076.png" + ] + }, + { + "Question_id": "P-wave phase picking/0077", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1496", + "(B) 905", + "(C) 768", + "(D) 1065", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0077.png" + ] + }, + { + "Question_id": "P-wave phase picking/0078", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 946", + "(C) 598", + "(D) 616", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0078.png" + ] + }, + { + "Question_id": "P-wave phase picking/0079", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 624", + "(B) 800", + "(C) 935", + "(D) 568", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0079.png" + ] + }, + { + "Question_id": "P-wave phase picking/0080", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 582", + "(B) 173", + "(C) 897", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0080.png" + ] + }, + { + "Question_id": "P-wave phase picking/0081", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 400", + "(B) 296", + "(C) 539", + "(D) 664", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0081.png" + ] + }, + { + "Question_id": "P-wave phase picking/0082", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 340", + "(B) 1122", + "(C) 499", + "(D) 654", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0082.png" + ] + }, + { + "Question_id": "P-wave phase picking/0083", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 740", + "(B) 900", + "(C) 1048", + "(D) 1319", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0083.png" + ] + }, + { + "Question_id": "P-wave phase picking/0084", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 606", + "(B) 901", + "(C) 800", + "(D) 1255", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0084.png" + ] + }, + { + "Question_id": "P-wave phase picking/0085", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -389", + "(B) 495", + "(C) 384", + "(D) 619", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0085.png" + ] + }, + { + "Question_id": "P-wave phase picking/0086", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 683", + "(B) -7", + "(C) 800", + "(D) 990", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0086.png" + ] + }, + { + "Question_id": "P-wave phase picking/0087", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 638", + "(B) 500", + "(C) 327", + "(D) -421", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0087.png" + ] + }, + { + "Question_id": "P-wave phase picking/0088", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1181", + "(B) 800", + "(C) 618", + "(D) 971", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0088.png" + ] + }, + { + "Question_id": "P-wave phase picking/0089", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 255", + "(B) 561", + "(C) 400", + "(D) -292", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0089.png" + ] + }, + { + "Question_id": "P-wave phase picking/0090", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 1157", + "(C) 658", + "(D) 958", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0090.png" + ] + }, + { + "Question_id": "P-wave phase picking/0091", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 186", + "(B) 1053", + "(C) 743", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0091.png" + ] + }, + { + "Question_id": "P-wave phase picking/0092", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) 386", + "(C) 1285", + "(D) 641", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0092.png" + ] + }, + { + "Question_id": "P-wave phase picking/0093", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 573", + "(B) 248", + "(C) 717", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0093.png" + ] + }, + { + "Question_id": "P-wave phase picking/0094", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 246", + "(B) 594", + "(C) 697", + "(D) 822", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0094.png" + ] + }, + { + "Question_id": "P-wave phase picking/0095", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 954", + "(B) 500", + "(C) 650", + "(D) 330", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0095.png" + ] + }, + { + "Question_id": "P-wave phase picking/0096", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1142", + "(B) 417", + "(C) 722", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0096.png" + ] + }, + { + "Question_id": "P-wave phase picking/0097", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) -248", + "(C) 507", + "(D) 890", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0097.png" + ] + }, + { + "Question_id": "P-wave phase picking/0098", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1265", + "(B) 600", + "(C) 701", + "(D) 436", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0098.png" + ] + }, + { + "Question_id": "P-wave phase picking/0099", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 1501", + "(C) 883", + "(D) 508", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0099.png" + ] + }, + { + "Question_id": "P-wave phase picking/0100", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 970", + "(C) 1247", + "(D) 679", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0100.png" + ] + }, + { + "Question_id": "P-wave phase picking/0101", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1164", + "(B) 800", + "(C) 634", + "(D) 951", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0101.png" + ] + }, + { + "Question_id": "P-wave phase picking/0102", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 783", + "(B) 41", + "(C) 900", + "(D) 1067", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0102.png" + ] + }, + { + "Question_id": "P-wave phase picking/0103", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 368", + "(B) 1083", + "(C) 900", + "(D) 747", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0103.png" + ] + }, + { + "Question_id": "P-wave phase picking/0104", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1329", + "(B) 640", + "(C) 334", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0104.png" + ] + }, + { + "Question_id": "P-wave phase picking/0105", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) 672", + "(C) -433", + "(D) 318", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0105.png" + ] + }, + { + "Question_id": "P-wave phase picking/0106", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 735", + "(B) 1073", + "(C) 899", + "(D) 1589", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0106.png" + ] + }, + { + "Question_id": "P-wave phase picking/0107", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1601", + "(B) 981", + "(C) 800", + "(D) 643", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0107.png" + ] + }, + { + "Question_id": "P-wave phase picking/0108", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 773", + "(B) 458", + "(C) 93", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0108.png" + ] + }, + { + "Question_id": "P-wave phase picking/0109", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -284", + "(B) 207", + "(C) 510", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0109.png" + ] + }, + { + "Question_id": "P-wave phase picking/0110", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 954", + "(B) 694", + "(C) 1023", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0110.png" + ] + }, + { + "Question_id": "P-wave phase picking/0111", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 983", + "(B) 799", + "(C) 1712", + "(D) 650", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0111.png" + ] + }, + { + "Question_id": "P-wave phase picking/0112", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 768", + "(B) -339", + "(C) 425", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0112.png" + ] + }, + { + "Question_id": "P-wave phase picking/0113", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1001", + "(B) 900", + "(C) 1389", + "(D) 747", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0113.png" + ] + }, + { + "Question_id": "P-wave phase picking/0114", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 518", + "(B) 909", + "(C) 800", + "(D) 609", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0114.png" + ] + }, + { + "Question_id": "P-wave phase picking/0115", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) -325", + "(C) 679", + "(D) 321", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0115.png" + ] + }, + { + "Question_id": "P-wave phase picking/0116", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 945", + "(B) 629", + "(C) 120", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0116.png" + ] + }, + { + "Question_id": "P-wave phase picking/0117", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 759", + "(C) -75", + "(D) 1001", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0117.png" + ] + }, + { + "Question_id": "P-wave phase picking/0118", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 421", + "(C) 731", + "(D) -224", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0118.png" + ] + }, + { + "Question_id": "P-wave phase picking/0119", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 731", + "(C) -91", + "(D) 1011", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0119.png" + ] + }, + { + "Question_id": "P-wave phase picking/0120", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 10", + "(C) 878", + "(D) 557", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0120.png" + ] + }, + { + "Question_id": "P-wave phase picking/0121", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 505", + "(B) 27", + "(C) 400", + "(D) 272", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0121.png" + ] + }, + { + "Question_id": "P-wave phase picking/0122", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 568", + "(B) 824", + "(C) 700", + "(D) 991", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0122.png" + ] + }, + { + "Question_id": "P-wave phase picking/0123", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1244", + "(B) 722", + "(C) 600", + "(D) 421", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0123.png" + ] + }, + { + "Question_id": "P-wave phase picking/0124", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -103", + "(B) 700", + "(C) 582", + "(D) 849", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0124.png" + ] + }, + { + "Question_id": "P-wave phase picking/0125", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 633", + "(B) 920", + "(C) 800", + "(D) -106", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0125.png" + ] + }, + { + "Question_id": "P-wave phase picking/0126", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) 304", + "(C) 203", + "(D) 674", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0126.png" + ] + }, + { + "Question_id": "P-wave phase picking/0127", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1439", + "(B) 569", + "(C) 700", + "(D) 869", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0127.png" + ] + }, + { + "Question_id": "P-wave phase picking/0128", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1354", + "(B) 598", + "(C) 962", + "(D) 798", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0128.png" + ] + }, + { + "Question_id": "P-wave phase picking/0129", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 727", + "(C) 93", + "(D) 421", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0129.png" + ] + }, + { + "Question_id": "P-wave phase picking/0130", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -33", + "(B) 706", + "(C) 900", + "(D) 1044", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0130.png" + ] + }, + { + "Question_id": "P-wave phase picking/0131", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 120", + "(C) 482", + "(D) 758", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0131.png" + ] + }, + { + "Question_id": "P-wave phase picking/0132", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 453", + "(B) 715", + "(C) 600", + "(D) 1499", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0132.png" + ] + }, + { + "Question_id": "P-wave phase picking/0133", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 571", + "(B) 222", + "(C) 884", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0133.png" + ] + }, + { + "Question_id": "P-wave phase picking/0134", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) -175", + "(C) 347", + "(D) 668", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0134.png" + ] + }, + { + "Question_id": "P-wave phase picking/0135", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1282", + "(B) 333", + "(C) 499", + "(D) 669", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0135.png" + ] + }, + { + "Question_id": "P-wave phase picking/0136", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -177", + "(B) 491", + "(C) 772", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0136.png" + ] + }, + { + "Question_id": "P-wave phase picking/0137", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 952", + "(C) 666", + "(D) 173", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0137.png" + ] + }, + { + "Question_id": "P-wave phase picking/0138", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 733", + "(C) 406", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0138.png" + ] + }, + { + "Question_id": "P-wave phase picking/0139", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 676", + "(B) 369", + "(C) 1325", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0139.png" + ] + }, + { + "Question_id": "P-wave phase picking/0140", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 581", + "(B) 1242", + "(C) 840", + "(D) 698", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0140.png" + ] + }, + { + "Question_id": "P-wave phase picking/0141", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 812", + "(B) 980", + "(C) 1799", + "(D) 684", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0141.png" + ] + }, + { + "Question_id": "P-wave phase picking/0142", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 696", + "(B) 994", + "(C) 800", + "(D) 1309", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0142.png" + ] + }, + { + "Question_id": "P-wave phase picking/0143", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 1520", + "(C) 640", + "(D) 914", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0143.png" + ] + }, + { + "Question_id": "P-wave phase picking/0144", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 333", + "(B) 500", + "(C) 671", + "(D) 819", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0144.png" + ] + }, + { + "Question_id": "P-wave phase picking/0145", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 587", + "(B) 1340", + "(C) 400", + "(D) 282", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0145.png" + ] + }, + { + "Question_id": "P-wave phase picking/0146", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 744", + "(B) 600", + "(C) -181", + "(D) 445", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0146.png" + ] + }, + { + "Question_id": "P-wave phase picking/0147", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 553", + "(B) 700", + "(C) 812", + "(D) 945", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0147.png" + ] + }, + { + "Question_id": "P-wave phase picking/0148", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 492", + "(B) 327", + "(C) 238", + "(D) 608", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0148.png" + ] + }, + { + "Question_id": "P-wave phase picking/0149", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 461", + "(B) 600", + "(C) 926", + "(D) 795", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0149.png" + ] + }, + { + "Question_id": "P-wave phase picking/0150", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 716", + "(B) 914", + "(C) 1098", + "(D) 1644", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0150.png" + ] + }, + { + "Question_id": "P-wave phase picking/0151", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 507", + "(B) 310", + "(C) 667", + "(D) 1439", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0151.png" + ] + }, + { + "Question_id": "P-wave phase picking/0152", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 937", + "(B) 618", + "(C) 1543", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0152.png" + ] + }, + { + "Question_id": "P-wave phase picking/0153", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 347", + "(C) 701", + "(D) 1034", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0153.png" + ] + }, + { + "Question_id": "P-wave phase picking/0154", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -220", + "(B) 257", + "(C) 559", + "(D) 399", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0154.png" + ] + }, + { + "Question_id": "P-wave phase picking/0155", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 597", + "(B) 769", + "(C) 495", + "(D) 1543", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0155.png" + ] + }, + { + "Question_id": "P-wave phase picking/0156", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 429", + "(B) 774", + "(C) 600", + "(D) 1054", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0156.png" + ] + }, + { + "Question_id": "P-wave phase picking/0157", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 435", + "(B) 986", + "(C) 800", + "(D) 647", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0157.png" + ] + }, + { + "Question_id": "P-wave phase picking/0158", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1301", + "(B) 805", + "(C) 970", + "(D) 611", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0158.png" + ] + }, + { + "Question_id": "P-wave phase picking/0159", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 510", + "(B) 700", + "(C) 870", + "(D) 383", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0159.png" + ] + }, + { + "Question_id": "P-wave phase picking/0160", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 727", + "(B) 1205", + "(C) 1081", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0160.png" + ] + }, + { + "Question_id": "P-wave phase picking/0161", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1658", + "(B) 1069", + "(C) 738", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0161.png" + ] + }, + { + "Question_id": "P-wave phase picking/0162", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1061", + "(C) 15", + "(D) 782", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0162.png" + ] + }, + { + "Question_id": "P-wave phase picking/0163", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 1063", + "(C) 405", + "(D) 780", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0163.png" + ] + }, + { + "Question_id": "P-wave phase picking/0164", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 489", + "(C) 631", + "(D) 951", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0164.png" + ] + }, + { + "Question_id": "P-wave phase picking/0165", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 732", + "(C) 981", + "(D) 444", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0165.png" + ] + }, + { + "Question_id": "P-wave phase picking/0166", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 845", + "(B) 544", + "(C) 400", + "(D) 234", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0166.png" + ] + }, + { + "Question_id": "P-wave phase picking/0167", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 419", + "(C) 162", + "(D) 720", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0167.png" + ] + }, + { + "Question_id": "P-wave phase picking/0168", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 825", + "(B) 1083", + "(C) 1398", + "(D) 946", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0168.png" + ] + }, + { + "Question_id": "P-wave phase picking/0169", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) -172", + "(C) 763", + "(D) 418", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0169.png" + ] + }, + { + "Question_id": "P-wave phase picking/0170", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 699", + "(B) 825", + "(C) 594", + "(D) 1680", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0170.png" + ] + }, + { + "Question_id": "P-wave phase picking/0171", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 558", + "(B) 865", + "(C) 173", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0171.png" + ] + }, + { + "Question_id": "P-wave phase picking/0172", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1607", + "(B) 900", + "(C) 758", + "(D) 1005", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0172.png" + ] + }, + { + "Question_id": "P-wave phase picking/0173", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1778", + "(C) 787", + "(D) 1097", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0173.png" + ] + }, + { + "Question_id": "P-wave phase picking/0174", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 480", + "(B) 600", + "(C) 1025", + "(D) 782", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0174.png" + ] + }, + { + "Question_id": "P-wave phase picking/0175", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 843", + "(B) 590", + "(C) 700", + "(D) 1596", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0175.png" + ] + }, + { + "Question_id": "P-wave phase picking/0176", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1436", + "(B) 308", + "(C) 500", + "(D) 679", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0176.png" + ] + }, + { + "Question_id": "P-wave phase picking/0177", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 619", + "(B) 500", + "(C) -469", + "(D) 329", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0177.png" + ] + }, + { + "Question_id": "P-wave phase picking/0178", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 662", + "(B) 500", + "(C) 1417", + "(D) 363", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0178.png" + ] + }, + { + "Question_id": "P-wave phase picking/0179", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 1454", + "(C) 846", + "(D) 598", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0179.png" + ] + }, + { + "Question_id": "P-wave phase picking/0180", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 583", + "(B) 238", + "(C) 699", + "(D) 874", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0180.png" + ] + }, + { + "Question_id": "P-wave phase picking/0181", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 797", + "(B) 687", + "(C) 214", + "(D) 898", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0181.png" + ] + }, + { + "Question_id": "P-wave phase picking/0182", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 221", + "(B) 582", + "(C) 880", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0182.png" + ] + }, + { + "Question_id": "P-wave phase picking/0183", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 498", + "(B) 328", + "(C) 976", + "(D) 659", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0183.png" + ] + }, + { + "Question_id": "P-wave phase picking/0184", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 487", + "(C) 731", + "(D) 354", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0184.png" + ] + }, + { + "Question_id": "P-wave phase picking/0185", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1064", + "(B) 900", + "(C) 1508", + "(D) 748", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0185.png" + ] + }, + { + "Question_id": "P-wave phase picking/0186", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 238", + "(B) 560", + "(C) 54", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0186.png" + ] + }, + { + "Question_id": "P-wave phase picking/0187", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1159", + "(B) 501", + "(C) 1000", + "(D) 819", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0187.png" + ] + }, + { + "Question_id": "P-wave phase picking/0188", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 515", + "(B) -89", + "(C) 700", + "(D) 820", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0188.png" + ] + }, + { + "Question_id": "P-wave phase picking/0189", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 606", + "(B) 498", + "(C) 960", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0189.png" + ] + }, + { + "Question_id": "P-wave phase picking/0190", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 589", + "(B) 804", + "(C) 700", + "(D) 452", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0190.png" + ] + }, + { + "Question_id": "P-wave phase picking/0191", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 807", + "(B) 500", + "(C) 303", + "(D) 673", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0191.png" + ] + }, + { + "Question_id": "P-wave phase picking/0192", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 736", + "(B) 1085", + "(C) 583", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0192.png" + ] + }, + { + "Question_id": "P-wave phase picking/0193", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 516", + "(B) 233", + "(C) 1394", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0193.png" + ] + }, + { + "Question_id": "P-wave phase picking/0194", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 188", + "(B) 930", + "(C) 800", + "(D) 608", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0194.png" + ] + }, + { + "Question_id": "P-wave phase picking/0195", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 460", + "(B) 625", + "(C) 751", + "(D) 1622", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0195.png" + ] + }, + { + "Question_id": "P-wave phase picking/0196", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 939", + "(B) 722", + "(C) 600", + "(D) 439", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0196.png" + ] + }, + { + "Question_id": "P-wave phase picking/0197", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 703", + "(B) -252", + "(C) 329", + "(D) 513", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0197.png" + ] + }, + { + "Question_id": "P-wave phase picking/0198", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 26", + "(B) 1181", + "(C) 837", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0198.png" + ] + }, + { + "Question_id": "P-wave phase picking/0199", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 701", + "(B) 500", + "(C) 326", + "(D) 666", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0199.png" + ] + }, + { + "Question_id": "P-wave phase picking/0200", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 391", + "(B) -315", + "(C) 601", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0200.png" + ] + }, + { + "Question_id": "P-wave phase picking/0201", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) 1350", + "(C) 391", + "(D) 620", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0201.png" + ] + }, + { + "Question_id": "P-wave phase picking/0202", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 752", + "(B) 1055", + "(C) 900", + "(D) 568", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0202.png" + ] + }, + { + "Question_id": "P-wave phase picking/0203", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 506", + "(B) 281", + "(C) -337", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0203.png" + ] + }, + { + "Question_id": "P-wave phase picking/0204", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 271", + "(B) 556", + "(C) 105", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0204.png" + ] + }, + { + "Question_id": "P-wave phase picking/0205", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 765", + "(C) 804", + "(D) 449", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0205.png" + ] + }, + { + "Question_id": "P-wave phase picking/0206", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 762", + "(B) 883", + "(C) 553", + "(D) 1007", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0206.png" + ] + }, + { + "Question_id": "P-wave phase picking/0207", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 978", + "(B) 556", + "(C) 831", + "(D) 724", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0207.png" + ] + }, + { + "Question_id": "P-wave phase picking/0208", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1059", + "(B) 900", + "(C) 779", + "(D) 212", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0208.png" + ] + }, + { + "Question_id": "P-wave phase picking/0209", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 655", + "(B) 399", + "(C) -76", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0209.png" + ] + }, + { + "Question_id": "P-wave phase picking/0210", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 809", + "(B) 511", + "(C) 700", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0210.png" + ] + }, + { + "Question_id": "P-wave phase picking/0211", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) 902", + "(C) 457", + "(D) 725", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0211.png" + ] + }, + { + "Question_id": "P-wave phase picking/0212", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 752", + "(C) 1022", + "(D) 520", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0212.png" + ] + }, + { + "Question_id": "P-wave phase picking/0213", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 518", + "(B) 400", + "(C) 219", + "(D) 608", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0213.png" + ] + }, + { + "Question_id": "P-wave phase picking/0214", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 571", + "(B) 460", + "(C) 200", + "(D) 310", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0214.png" + ] + }, + { + "Question_id": "P-wave phase picking/0215", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -44", + "(B) 938", + "(C) 666", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0215.png" + ] + }, + { + "Question_id": "P-wave phase picking/0216", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 655", + "(B) 959", + "(C) 800", + "(D) 472", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0216.png" + ] + }, + { + "Question_id": "P-wave phase picking/0217", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 746", + "(B) 500", + "(C) 652", + "(D) 304", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0217.png" + ] + }, + { + "Question_id": "P-wave phase picking/0218", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 672", + "(B) -203", + "(C) 500", + "(D) 333", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0218.png" + ] + }, + { + "Question_id": "P-wave phase picking/0219", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 315", + "(B) 500", + "(C) 1319", + "(D) 615", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0219.png" + ] + }, + { + "Question_id": "P-wave phase picking/0220", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 569", + "(B) 1026", + "(C) 231", + "(D) 407", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0220.png" + ] + }, + { + "Question_id": "P-wave phase picking/0221", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 703", + "(B) 600", + "(C) 498", + "(D) 1080", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0221.png" + ] + }, + { + "Question_id": "P-wave phase picking/0222", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -144", + "(B) 655", + "(C) 500", + "(D) 348", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0222.png" + ] + }, + { + "Question_id": "P-wave phase picking/0223", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 383", + "(B) 656", + "(C) -19", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0223.png" + ] + }, + { + "Question_id": "P-wave phase picking/0224", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 977", + "(B) 611", + "(C) 337", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0224.png" + ] + }, + { + "Question_id": "P-wave phase picking/0225", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 781", + "(B) 600", + "(C) 1494", + "(D) 495", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0225.png" + ] + }, + { + "Question_id": "P-wave phase picking/0226", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1086", + "(B) 884", + "(C) 540", + "(D) 710", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0226.png" + ] + }, + { + "Question_id": "P-wave phase picking/0227", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1159", + "(B) 496", + "(C) 354", + "(D) 647", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0227.png" + ] + }, + { + "Question_id": "P-wave phase picking/0228", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 399", + "(B) 1084", + "(C) 589", + "(D) 277", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0228.png" + ] + }, + { + "Question_id": "P-wave phase picking/0229", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 640", + "(B) 216", + "(C) 356", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0229.png" + ] + }, + { + "Question_id": "P-wave phase picking/0230", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -200", + "(B) 253", + "(C) 400", + "(D) 548", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0230.png" + ] + }, + { + "Question_id": "P-wave phase picking/0231", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 856", + "(B) 1027", + "(C) 581", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0231.png" + ] + }, + { + "Question_id": "P-wave phase picking/0232", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 419", + "(B) 286", + "(C) 712", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0232.png" + ] + }, + { + "Question_id": "P-wave phase picking/0233", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) 400", + "(C) -576", + "(D) 222", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0233.png" + ] + }, + { + "Question_id": "P-wave phase picking/0234", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1319", + "(B) 763", + "(C) 1034", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0234.png" + ] + }, + { + "Question_id": "P-wave phase picking/0235", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1494", + "(B) 700", + "(C) 856", + "(D) 572", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0235.png" + ] + }, + { + "Question_id": "P-wave phase picking/0236", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1000", + "(B) 266", + "(C) 1160", + "(D) 877", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0236.png" + ] + }, + { + "Question_id": "P-wave phase picking/0237", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 272", + "(B) 525", + "(C) 400", + "(D) 644", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0237.png" + ] + }, + { + "Question_id": "P-wave phase picking/0238", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 413", + "(B) 708", + "(C) 230", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0238.png" + ] + }, + { + "Question_id": "P-wave phase picking/0239", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 790", + "(B) 1655", + "(C) 898", + "(D) 671", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0239.png" + ] + }, + { + "Question_id": "P-wave phase picking/0240", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 707", + "(B) 1745", + "(C) 900", + "(D) 1020", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0240.png" + ] + }, + { + "Question_id": "P-wave phase picking/0241", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1565", + "(B) 900", + "(C) 1045", + "(D) 797", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0241.png" + ] + }, + { + "Question_id": "P-wave phase picking/0242", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 230", + "(B) 400", + "(C) 544", + "(D) -599", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0242.png" + ] + }, + { + "Question_id": "P-wave phase picking/0243", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 500", + "(B) -482", + "(C) 323", + "(D) 605", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0243.png" + ] + }, + { + "Question_id": "P-wave phase picking/0244", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 600", + "(B) -194", + "(C) 422", + "(D) 714", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0244.png" + ] + }, + { + "Question_id": "P-wave phase picking/0245", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 814", + "(B) 924", + "(C) 1370", + "(D) 676", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0245.png" + ] + }, + { + "Question_id": "P-wave phase picking/0246", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1041", + "(B) 800", + "(C) 960", + "(D) 697", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0246.png" + ] + }, + { + "Question_id": "P-wave phase picking/0247", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1054", + "(B) 747", + "(C) 263", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0247.png" + ] + }, + { + "Question_id": "P-wave phase picking/0248", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 687", + "(B) 886", + "(C) 541", + "(D) 398", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0248.png" + ] + }, + { + "Question_id": "P-wave phase picking/0249", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 448", + "(B) 800", + "(C) 618", + "(D) 949", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0249.png" + ] + }, + { + "Question_id": "P-wave phase picking/0250", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 400", + "(B) 244", + "(C) -40", + "(D) 583", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0250.png" + ] + }, + { + "Question_id": "P-wave phase picking/0251", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 498", + "(B) 636", + "(C) 341", + "(D) 875", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0251.png" + ] + }, + { + "Question_id": "P-wave phase picking/0252", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 619", + "(B) 303", + "(C) 500", + "(D) 179", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0252.png" + ] + }, + { + "Question_id": "P-wave phase picking/0253", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 507", + "(B) 102", + "(C) 851", + "(D) 699", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0253.png" + ] + }, + { + "Question_id": "P-wave phase picking/0254", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 738", + "(B) 600", + "(C) 229", + "(D) 457", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0254.png" + ] + }, + { + "Question_id": "P-wave phase picking/0255", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 743", + "(C) 1438", + "(D) 1050", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0255.png" + ] + }, + { + "Question_id": "P-wave phase picking/0256", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 400", + "(B) 1360", + "(C) 296", + "(D) 570", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0256.png" + ] + }, + { + "Question_id": "P-wave phase picking/0257", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 775", + "(B) 444", + "(C) 1216", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0257.png" + ] + }, + { + "Question_id": "P-wave phase picking/0258", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 863", + "(B) -291", + "(C) 700", + "(D) 552", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0258.png" + ] + }, + { + "Question_id": "P-wave phase picking/0259", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 395", + "(B) 500", + "(C) -62", + "(D) 612", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0259.png" + ] + }, + { + "Question_id": "P-wave phase picking/0260", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1392", + "(B) 656", + "(C) 935", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0260.png" + ] + }, + { + "Question_id": "P-wave phase picking/0261", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1086", + "(B) 1125", + "(C) 900", + "(D) 747", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0261.png" + ] + }, + { + "Question_id": "P-wave phase picking/0262", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 737", + "(B) 1079", + "(C) 900", + "(D) 1629", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0262.png" + ] + }, + { + "Question_id": "P-wave phase picking/0263", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 470", + "(B) 602", + "(C) -228", + "(D) 755", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0263.png" + ] + }, + { + "Question_id": "P-wave phase picking/0264", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -240", + "(B) 574", + "(C) 889", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0264.png" + ] + }, + { + "Question_id": "P-wave phase picking/0265", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 596", + "(C) 882", + "(D) 1695", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0265.png" + ] + }, + { + "Question_id": "P-wave phase picking/0266", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 803", + "(B) 930", + "(C) 615", + "(D) 1152", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0266.png" + ] + }, + { + "Question_id": "P-wave phase picking/0267", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 899", + "(B) 212", + "(C) 756", + "(D) 1040", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0267.png" + ] + }, + { + "Question_id": "P-wave phase picking/0268", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 799", + "(B) 1049", + "(C) 989", + "(D) 628", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0268.png" + ] + }, + { + "Question_id": "P-wave phase picking/0269", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 859", + "(C) -42", + "(D) 529", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0269.png" + ] + }, + { + "Question_id": "P-wave phase picking/0270", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 536", + "(C) 803", + "(D) 239", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0270.png" + ] + }, + { + "Question_id": "P-wave phase picking/0271", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 399", + "(C) 290", + "(D) 547", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0271.png" + ] + }, + { + "Question_id": "P-wave phase picking/0272", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1046", + "(B) 650", + "(C) 899", + "(D) 786", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0272.png" + ] + }, + { + "Question_id": "P-wave phase picking/0273", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 271", + "(B) 530", + "(C) 918", + "(D) 397", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0273.png" + ] + }, + { + "Question_id": "P-wave phase picking/0274", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 349", + "(B) 607", + "(C) 61", + "(D) 500", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0274.png" + ] + }, + { + "Question_id": "P-wave phase picking/0275", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1140", + "(B) 379", + "(C) 498", + "(D) 631", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0275.png" + ] + }, + { + "Question_id": "P-wave phase picking/0276", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 504", + "(B) 697", + "(C) 175", + "(D) 894", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0276.png" + ] + }, + { + "Question_id": "P-wave phase picking/0277", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 215", + "(B) 740", + "(C) 561", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0277.png" + ] + }, + { + "Question_id": "P-wave phase picking/0278", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 431", + "(B) 600", + "(C) -260", + "(D) 717", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0278.png" + ] + }, + { + "Question_id": "P-wave phase picking/0279", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -11", + "(B) 262", + "(C) 522", + "(D) 400", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0279.png" + ] + }, + { + "Question_id": "P-wave phase picking/0280", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 750", + "(B) 437", + "(C) -236", + "(D) 600", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0280.png" + ] + }, + { + "Question_id": "P-wave phase picking/0281", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1761", + "(B) 760", + "(C) 1093", + "(D) 904", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0281.png" + ] + }, + { + "Question_id": "P-wave phase picking/0282", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 900", + "(B) 1053", + "(C) 709", + "(D) -41", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0282.png" + ] + }, + { + "Question_id": "P-wave phase picking/0283", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 782", + "(B) 409", + "(C) 597", + "(D) 29", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0283.png" + ] + }, + { + "Question_id": "P-wave phase picking/0284", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -157", + "(B) 435", + "(C) 600", + "(D) 798", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0284.png" + ] + }, + { + "Question_id": "P-wave phase picking/0285", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 646", + "(B) 500", + "(C) 1383", + "(D) 308", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0285.png" + ] + }, + { + "Question_id": "P-wave phase picking/0286", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 200", + "(B) 1139", + "(C) 854", + "(D) 1000", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0286.png" + ] + }, + { + "Question_id": "P-wave phase picking/0287", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 316", + "(B) 744", + "(C) 499", + "(D) 685", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0287.png" + ] + }, + { + "Question_id": "P-wave phase picking/0288", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1190", + "(B) 615", + "(C) 500", + "(D) 332", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0288.png" + ] + }, + { + "Question_id": "P-wave phase picking/0289", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 118", + "(B) 376", + "(C) 499", + "(D) 665", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0289.png" + ] + }, + { + "Question_id": "P-wave phase picking/0290", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 401", + "(B) 797", + "(C) 600", + "(D) 1064", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0290.png" + ] + }, + { + "Question_id": "P-wave phase picking/0291", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 880", + "(C) 521", + "(D) 921", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0291.png" + ] + }, + { + "Question_id": "P-wave phase picking/0292", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 745", + "(B) 900", + "(C) 1026", + "(D) 1744", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0292.png" + ] + }, + { + "Question_id": "P-wave phase picking/0293", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1", + "(B) 221", + "(C) 400", + "(D) 578", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0293.png" + ] + }, + { + "Question_id": "P-wave phase picking/0294", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 32", + "(C) 635", + "(D) 911", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0294.png" + ] + }, + { + "Question_id": "P-wave phase picking/0295", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1276", + "(B) 725", + "(C) 1061", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0295.png" + ] + }, + { + "Question_id": "P-wave phase picking/0296", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 800", + "(B) 937", + "(C) 642", + "(D) 1213", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0296.png" + ] + }, + { + "Question_id": "P-wave phase picking/0297", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 599", + "(B) 1080", + "(C) 751", + "(D) 399", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0297.png" + ] + }, + { + "Question_id": "P-wave phase picking/0298", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 507", + "(B) 875", + "(C) 700", + "(D) 252", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0298.png" + ] + }, + { + "Question_id": "P-wave phase picking/0299", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of P-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize vertical-component analysis validated by transverse energy analysis, with supplementary horizontal-component polarization verification. Output a integer [x] relative to sample index 0, rounded to nearest phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "P-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 680", + "(B) 359", + "(C) 500", + "(D) -437", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/P-wave/STEAD_Waveform_0299.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/S-wave_phase_picking.json b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/S-wave_phase_picking.json new file mode 100644 index 0000000000000000000000000000000000000000..3c02fff7ab83c2e0dcb81b63636f778262b1afb8 --- /dev/null +++ b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/S-wave_phase_picking.json @@ -0,0 +1,6302 @@ +[ + { + "Question_id": "S-wave phase picking/0000", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 469", + "(B) 624", + "(C) 27", + "(D) 800", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0000.png" + ] + }, + { + "Question_id": "S-wave phase picking/0001", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 620", + "(B) 769", + "(C) 1207", + "(D) 922", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0001.png" + ] + }, + { + "Question_id": "S-wave phase picking/0002", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 884", + "(B) 1041", + "(C) 1689", + "(D) 749", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0002.png" + ] + }, + { + "Question_id": "S-wave phase picking/0003", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5024", + "(B) 5524", + "(C) 4752", + "(D) 4921", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0003.png" + ] + }, + { + "Question_id": "S-wave phase picking/0004", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1515", + "(B) 1356", + "(C) 1174", + "(D) 1568", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0004.png" + ] + }, + { + "Question_id": "S-wave phase picking/0005", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1168", + "(B) 895", + "(C) 1024", + "(D) 618", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0005.png" + ] + }, + { + "Question_id": "S-wave phase picking/0006", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1530", + "(B) 1897", + "(C) 1021", + "(D) 1724", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0006.png" + ] + }, + { + "Question_id": "S-wave phase picking/0007", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1272", + "(B) 1145", + "(C) 1466", + "(D) 1683", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0007.png" + ] + }, + { + "Question_id": "S-wave phase picking/0008", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1798", + "(B) 1095", + "(C) 947", + "(D) 802", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0008.png" + ] + }, + { + "Question_id": "S-wave phase picking/0009", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 739", + "(B) 1201", + "(C) 570", + "(D) 899", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0009.png" + ] + }, + { + "Question_id": "S-wave phase picking/0010", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1587", + "(B) 1724", + "(C) 1413", + "(D) 1057", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0010.png" + ] + }, + { + "Question_id": "S-wave phase picking/0011", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 924", + "(B) 1237", + "(C) 298", + "(D) 1053", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0011.png" + ] + }, + { + "Question_id": "S-wave phase picking/0012", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2052", + "(B) 2158", + "(C) 1138", + "(D) 1942", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0012.png" + ] + }, + { + "Question_id": "S-wave phase picking/0013", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1138", + "(B) 1387", + "(C) 942", + "(D) 841", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0013.png" + ] + }, + { + "Question_id": "S-wave phase picking/0014", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2151", + "(B) 2261", + "(C) 1988", + "(D) 1680", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0014.png" + ] + }, + { + "Question_id": "S-wave phase picking/0015", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1177", + "(B) 797", + "(C) 1652", + "(D) 984", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0015.png" + ] + }, + { + "Question_id": "S-wave phase picking/0016", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1148", + "(B) 1416", + "(C) 1309", + "(D) 1016", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0016.png" + ] + }, + { + "Question_id": "S-wave phase picking/0017", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2347", + "(B) 2611", + "(C) 2508", + "(D) 1822", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0017.png" + ] + }, + { + "Question_id": "S-wave phase picking/0018", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1421", + "(B) 1292", + "(C) 1143", + "(D) 357", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0018.png" + ] + }, + { + "Question_id": "S-wave phase picking/0019", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 763", + "(B) 942", + "(C) 1288", + "(D) 1109", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0019.png" + ] + }, + { + "Question_id": "S-wave phase picking/0020", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 705", + "(B) 527", + "(C) -134", + "(D) 411", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0020.png" + ] + }, + { + "Question_id": "S-wave phase picking/0021", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1057", + "(B) 1364", + "(C) 2121", + "(D) 1190", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0021.png" + ] + }, + { + "Question_id": "S-wave phase picking/0022", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1767", + "(B) 2081", + "(C) 1941", + "(D) 2200", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0022.png" + ] + }, + { + "Question_id": "S-wave phase picking/0023", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 848", + "(B) 993", + "(C) 722", + "(D) 1369", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0023.png" + ] + }, + { + "Question_id": "S-wave phase picking/0024", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1424", + "(B) 1702", + "(C) 1600", + "(D) 2365", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0024.png" + ] + }, + { + "Question_id": "S-wave phase picking/0025", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 761", + "(B) 1156", + "(C) 1027", + "(D) 1272", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0025.png" + ] + }, + { + "Question_id": "S-wave phase picking/0026", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1188", + "(B) 1511", + "(C) 440", + "(D) 1312", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0026.png" + ] + }, + { + "Question_id": "S-wave phase picking/0027", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 671", + "(B) 499", + "(C) 1442", + "(D) 863", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0027.png" + ] + }, + { + "Question_id": "S-wave phase picking/0028", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 909", + "(B) 1266", + "(C) 503", + "(D) 1096", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0028.png" + ] + }, + { + "Question_id": "S-wave phase picking/0029", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 563", + "(B) 993", + "(C) 418", + "(D) 762", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0029.png" + ] + }, + { + "Question_id": "S-wave phase picking/0030", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 759", + "(B) 231", + "(C) 936", + "(D) 1079", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0030.png" + ] + }, + { + "Question_id": "S-wave phase picking/0031", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1846", + "(B) 1733", + "(C) 1577", + "(D) 2605", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0031.png" + ] + }, + { + "Question_id": "S-wave phase picking/0032", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1214", + "(B) 1033", + "(C) 883", + "(D) 1753", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0032.png" + ] + }, + { + "Question_id": "S-wave phase picking/0033", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2128", + "(B) 1330", + "(C) 1948", + "(D) 1810", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0033.png" + ] + }, + { + "Question_id": "S-wave phase picking/0034", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2154", + "(B) 1659", + "(C) 1786", + "(D) 1496", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0034.png" + ] + }, + { + "Question_id": "S-wave phase picking/0035", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1766", + "(B) 1624", + "(C) 2542", + "(D) 1513", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0035.png" + ] + }, + { + "Question_id": "S-wave phase picking/0036", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 828", + "(B) -297", + "(C) 700", + "(D) 586", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0036.png" + ] + }, + { + "Question_id": "S-wave phase picking/0037", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1253", + "(B) 966", + "(C) 2034", + "(D) 1152", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0037.png" + ] + }, + { + "Question_id": "S-wave phase picking/0038", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1290", + "(B) 1112", + "(C) 1392", + "(D) 1020", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0038.png" + ] + }, + { + "Question_id": "S-wave phase picking/0039", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1047", + "(B) 1600", + "(C) 854", + "(D) 745", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0039.png" + ] + }, + { + "Question_id": "S-wave phase picking/0040", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1107", + "(B) 806", + "(C) 537", + "(D) 919", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0040.png" + ] + }, + { + "Question_id": "S-wave phase picking/0041", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1115", + "(B) 725", + "(C) 513", + "(D) 925", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0041.png" + ] + }, + { + "Question_id": "S-wave phase picking/0042", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 237", + "(B) 734", + "(C) 1052", + "(D) 900", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0042.png" + ] + }, + { + "Question_id": "S-wave phase picking/0043", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1207", + "(B) 1517", + "(C) 1036", + "(D) 853", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0043.png" + ] + }, + { + "Question_id": "S-wave phase picking/0044", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 848", + "(B) 558", + "(C) 723", + "(D) 998", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0044.png" + ] + }, + { + "Question_id": "S-wave phase picking/0045", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1515", + "(B) 797", + "(C) 1151", + "(D) 1349", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0045.png" + ] + }, + { + "Question_id": "S-wave phase picking/0046", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1152", + "(B) 1290", + "(C) 423", + "(D) 1014", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0046.png" + ] + }, + { + "Question_id": "S-wave phase picking/0047", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 888", + "(B) 691", + "(C) 1306", + "(D) 1045", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0047.png" + ] + }, + { + "Question_id": "S-wave phase picking/0048", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1601", + "(B) 760", + "(C) 1710", + "(D) 1493", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0048.png" + ] + }, + { + "Question_id": "S-wave phase picking/0049", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2096", + "(B) 2995", + "(C) 2219", + "(D) 1952", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0049.png" + ] + }, + { + "Question_id": "S-wave phase picking/0050", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 305", + "(B) 452", + "(C) 584", + "(D) 883", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0050.png" + ] + }, + { + "Question_id": "S-wave phase picking/0051", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 766", + "(B) 1054", + "(C) 888", + "(D) -73", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0051.png" + ] + }, + { + "Question_id": "S-wave phase picking/0052", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2001", + "(B) 1835", + "(C) 1651", + "(D) 2686", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0052.png" + ] + }, + { + "Question_id": "S-wave phase picking/0053", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 972", + "(B) 1160", + "(C) 1645", + "(D) 818", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0053.png" + ] + }, + { + "Question_id": "S-wave phase picking/0054", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1242", + "(B) 1378", + "(C) 1172", + "(D) 1552", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0054.png" + ] + }, + { + "Question_id": "S-wave phase picking/0055", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3037", + "(B) 2105", + "(C) 2214", + "(D) 1912", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0055.png" + ] + }, + { + "Question_id": "S-wave phase picking/0056", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2022", + "(B) 1194", + "(C) 1346", + "(D) 1046", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0056.png" + ] + }, + { + "Question_id": "S-wave phase picking/0057", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1499", + "(B) 779", + "(C) 977", + "(D) 1137", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0057.png" + ] + }, + { + "Question_id": "S-wave phase picking/0058", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1156", + "(B) 2123", + "(C) 1307", + "(D) 1411", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0058.png" + ] + }, + { + "Question_id": "S-wave phase picking/0059", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 764", + "(B) 610", + "(C) 822", + "(D) 502", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0059.png" + ] + }, + { + "Question_id": "S-wave phase picking/0060", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 733", + "(B) 1313", + "(C) 1116", + "(D) 1418", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0060.png" + ] + }, + { + "Question_id": "S-wave phase picking/0061", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1052", + "(B) 860", + "(C) 502", + "(D) 691", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0061.png" + ] + }, + { + "Question_id": "S-wave phase picking/0062", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 930", + "(B) 683", + "(C) 1584", + "(D) 797", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0062.png" + ] + }, + { + "Question_id": "S-wave phase picking/0063", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1102", + "(B) 1241", + "(C) 1531", + "(D) 1342", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0063.png" + ] + }, + { + "Question_id": "S-wave phase picking/0064", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1111", + "(B) 981", + "(C) 859", + "(D) 1963", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0064.png" + ] + }, + { + "Question_id": "S-wave phase picking/0065", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 770", + "(B) 1079", + "(C) 918", + "(D) 1201", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0065.png" + ] + }, + { + "Question_id": "S-wave phase picking/0066", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1788", + "(B) 1904", + "(C) 1305", + "(D) 1676", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0066.png" + ] + }, + { + "Question_id": "S-wave phase picking/0067", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1988", + "(B) 2181", + "(C) 1817", + "(D) 2284", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0067.png" + ] + }, + { + "Question_id": "S-wave phase picking/0068", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 448", + "(B) 191", + "(C) 295", + "(D) 630", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0068.png" + ] + }, + { + "Question_id": "S-wave phase picking/0069", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 639", + "(B) 1268", + "(C) 529", + "(D) 816", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0069.png" + ] + }, + { + "Question_id": "S-wave phase picking/0070", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 700", + "(B) 1347", + "(C) 569", + "(D) 421", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0070.png" + ] + }, + { + "Question_id": "S-wave phase picking/0071", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2121", + "(B) 2405", + "(C) 2282", + "(D) 2517", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0071.png" + ] + }, + { + "Question_id": "S-wave phase picking/0072", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1132", + "(B) 811", + "(C) 1465", + "(D) 1289", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0072.png" + ] + }, + { + "Question_id": "S-wave phase picking/0073", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1358", + "(B) 1576", + "(C) 1684", + "(D) 1436", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0073.png" + ] + }, + { + "Question_id": "S-wave phase picking/0074", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 295", + "(B) 404", + "(C) 587", + "(D) 700", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0074.png" + ] + }, + { + "Question_id": "S-wave phase picking/0075", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -24", + "(B) 1078", + "(C) 892", + "(D) 769", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0075.png" + ] + }, + { + "Question_id": "S-wave phase picking/0076", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 212", + "(B) 1077", + "(C) 1182", + "(D) 1309", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0076.png" + ] + }, + { + "Question_id": "S-wave phase picking/0077", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1000", + "(B) 1335", + "(C) 1186", + "(D) 1823", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0077.png" + ] + }, + { + "Question_id": "S-wave phase picking/0078", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2080", + "(B) 2256", + "(C) 1934", + "(D) 1347", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0078.png" + ] + }, + { + "Question_id": "S-wave phase picking/0079", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1948", + "(B) 1715", + "(C) 1603", + "(D) 1461", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0079.png" + ] + }, + { + "Question_id": "S-wave phase picking/0080", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1003", + "(B) 1441", + "(C) 1344", + "(D) 1164", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0080.png" + ] + }, + { + "Question_id": "S-wave phase picking/0081", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1996", + "(B) 1172", + "(C) 1068", + "(D) 918", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0081.png" + ] + }, + { + "Question_id": "S-wave phase picking/0082", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1314", + "(B) 1448", + "(C) 1600", + "(D) 1178", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0082.png" + ] + }, + { + "Question_id": "S-wave phase picking/0083", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1502", + "(B) 797", + "(C) 919", + "(D) 1036", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0083.png" + ] + }, + { + "Question_id": "S-wave phase picking/0084", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1017", + "(B) 1206", + "(C) 1485", + "(D) 1375", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0084.png" + ] + }, + { + "Question_id": "S-wave phase picking/0085", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1963", + "(B) 1788", + "(C) 2081", + "(D) 1644", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0085.png" + ] + }, + { + "Question_id": "S-wave phase picking/0086", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1068", + "(B) 143", + "(C) 894", + "(D) 781", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0086.png" + ] + }, + { + "Question_id": "S-wave phase picking/0087", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 735", + "(B) 1063", + "(C) 257", + "(D) 881", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0087.png" + ] + }, + { + "Question_id": "S-wave phase picking/0088", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 789", + "(B) 1460", + "(C) 1561", + "(D) 1289", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0088.png" + ] + }, + { + "Question_id": "S-wave phase picking/0089", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4022", + "(B) 3742", + "(C) 3895", + "(D) 3408", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0089.png" + ] + }, + { + "Question_id": "S-wave phase picking/0090", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 920", + "(B) 690", + "(C) 792", + "(D) 1002", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0090.png" + ] + }, + { + "Question_id": "S-wave phase picking/0091", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 810", + "(B) 935", + "(C) 1106", + "(D) 721", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0091.png" + ] + }, + { + "Question_id": "S-wave phase picking/0092", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -135", + "(B) 938", + "(C) 615", + "(D) 772", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0092.png" + ] + }, + { + "Question_id": "S-wave phase picking/0093", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1453", + "(B) 471", + "(C) 1189", + "(D) 1321", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0093.png" + ] + }, + { + "Question_id": "S-wave phase picking/0094", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1327", + "(B) 1182", + "(C) 760", + "(D) 1434", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0094.png" + ] + }, + { + "Question_id": "S-wave phase picking/0095", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1727", + "(B) 1132", + "(C) 1317", + "(D) 994", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0095.png" + ] + }, + { + "Question_id": "S-wave phase picking/0096", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 49", + "(B) 627", + "(C) 939", + "(D) 753", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0096.png" + ] + }, + { + "Question_id": "S-wave phase picking/0097", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1110", + "(B) 1559", + "(C) 1424", + "(D) 1671", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0097.png" + ] + }, + { + "Question_id": "S-wave phase picking/0098", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 898", + "(B) 1840", + "(C) 1064", + "(D) 1174", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0098.png" + ] + }, + { + "Question_id": "S-wave phase picking/0099", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1609", + "(B) 1960", + "(C) 1749", + "(D) 1501", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0099.png" + ] + }, + { + "Question_id": "S-wave phase picking/0100", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1200", + "(B) 407", + "(C) 1045", + "(D) 934", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0100.png" + ] + }, + { + "Question_id": "S-wave phase picking/0101", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1125", + "(B) 1302", + "(C) 992", + "(D) 758", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0101.png" + ] + }, + { + "Question_id": "S-wave phase picking/0102", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 145", + "(B) 855", + "(C) 1140", + "(D) 1030", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0102.png" + ] + }, + { + "Question_id": "S-wave phase picking/0103", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 560", + "(B) 683", + "(C) 1344", + "(D) 792", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0103.png" + ] + }, + { + "Question_id": "S-wave phase picking/0104", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 948", + "(B) 1364", + "(C) 1491", + "(D) 1591", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0104.png" + ] + }, + { + "Question_id": "S-wave phase picking/0105", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1312", + "(B) 727", + "(C) 956", + "(D) 829", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0105.png" + ] + }, + { + "Question_id": "S-wave phase picking/0106", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 908", + "(B) 757", + "(C) 1252", + "(D) 597", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0106.png" + ] + }, + { + "Question_id": "S-wave phase picking/0107", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 567", + "(B) 383", + "(C) 714", + "(D) 1218", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0107.png" + ] + }, + { + "Question_id": "S-wave phase picking/0108", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1090", + "(B) 1192", + "(C) 1292", + "(D) 796", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0108.png" + ] + }, + { + "Question_id": "S-wave phase picking/0109", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1664", + "(B) 1972", + "(C) 2390", + "(D) 1845", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0109.png" + ] + }, + { + "Question_id": "S-wave phase picking/0110", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1442", + "(B) 1127", + "(C) 1327", + "(D) 404", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0110.png" + ] + }, + { + "Question_id": "S-wave phase picking/0111", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 935", + "(B) -190", + "(C) 803", + "(D) 701", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0111.png" + ] + }, + { + "Question_id": "S-wave phase picking/0112", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 696", + "(B) 1024", + "(C) 883", + "(D) 1160", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0112.png" + ] + }, + { + "Question_id": "S-wave phase picking/0113", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1281", + "(B) 140", + "(C) 965", + "(D) 1106", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0113.png" + ] + }, + { + "Question_id": "S-wave phase picking/0114", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 996", + "(B) 823", + "(C) 1105", + "(D) 1244", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0114.png" + ] + }, + { + "Question_id": "S-wave phase picking/0115", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1728", + "(B) 1243", + "(C) 1015", + "(D) 1129", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0115.png" + ] + }, + { + "Question_id": "S-wave phase picking/0116", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1019", + "(B) 731", + "(C) 616", + "(D) 872", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0116.png" + ] + }, + { + "Question_id": "S-wave phase picking/0117", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1304", + "(B) 1075", + "(C) 952", + "(D) 1184", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0117.png" + ] + }, + { + "Question_id": "S-wave phase picking/0118", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1853", + "(B) 1041", + "(C) 1361", + "(D) 1230", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0118.png" + ] + }, + { + "Question_id": "S-wave phase picking/0119", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 986", + "(B) 1699", + "(C) 1150", + "(D) 831", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0119.png" + ] + }, + { + "Question_id": "S-wave phase picking/0120", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1056", + "(B) 1237", + "(C) 930", + "(D) 803", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0120.png" + ] + }, + { + "Question_id": "S-wave phase picking/0121", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2600", + "(B) 2201", + "(C) 2005", + "(D) 1851", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0121.png" + ] + }, + { + "Question_id": "S-wave phase picking/0122", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1235", + "(B) 1406", + "(C) 1042", + "(D) 2056", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0122.png" + ] + }, + { + "Question_id": "S-wave phase picking/0123", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1605", + "(B) 1323", + "(C) 1452", + "(D) 1917", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0123.png" + ] + }, + { + "Question_id": "S-wave phase picking/0124", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1894", + "(B) 1594", + "(C) 1732", + "(D) 1994", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0124.png" + ] + }, + { + "Question_id": "S-wave phase picking/0125", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1553", + "(B) 1421", + "(C) 1719", + "(D) 837", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0125.png" + ] + }, + { + "Question_id": "S-wave phase picking/0126", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1699", + "(B) 709", + "(C) 840", + "(D) 988", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0126.png" + ] + }, + { + "Question_id": "S-wave phase picking/0127", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1722", + "(B) 1860", + "(C) 1309", + "(D) 1966", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0127.png" + ] + }, + { + "Question_id": "S-wave phase picking/0128", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1053", + "(B) 1175", + "(C) 1940", + "(D) 909", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0128.png" + ] + }, + { + "Question_id": "S-wave phase picking/0129", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1808", + "(B) 1697", + "(C) 2171", + "(D) 2004", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0129.png" + ] + }, + { + "Question_id": "S-wave phase picking/0130", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4236", + "(B) 4016", + "(C) 3849", + "(D) 3657", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0130.png" + ] + }, + { + "Question_id": "S-wave phase picking/0131", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1050", + "(B) 942", + "(C) 639", + "(D) 1230", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0131.png" + ] + }, + { + "Question_id": "S-wave phase picking/0132", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2152", + "(B) 2042", + "(C) 1930", + "(D) 3005", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0132.png" + ] + }, + { + "Question_id": "S-wave phase picking/0133", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1236", + "(B) 1436", + "(C) 1597", + "(D) 710", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0133.png" + ] + }, + { + "Question_id": "S-wave phase picking/0134", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 591", + "(B) 1419", + "(C) 439", + "(D) 778", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0134.png" + ] + }, + { + "Question_id": "S-wave phase picking/0135", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 969", + "(B) 1072", + "(C) 1655", + "(D) 1182", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0135.png" + ] + }, + { + "Question_id": "S-wave phase picking/0136", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 911", + "(B) 804", + "(C) 647", + "(D) 1262", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0136.png" + ] + }, + { + "Question_id": "S-wave phase picking/0137", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1576", + "(B) 1075", + "(C) 817", + "(D) 928", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0137.png" + ] + }, + { + "Question_id": "S-wave phase picking/0138", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1588", + "(B) 1053", + "(C) 1353", + "(D) 1226", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0138.png" + ] + }, + { + "Question_id": "S-wave phase picking/0139", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 820", + "(B) 1317", + "(C) 996", + "(D) 1138", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0139.png" + ] + }, + { + "Question_id": "S-wave phase picking/0140", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1548", + "(B) 1788", + "(C) 1937", + "(D) 2113", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0140.png" + ] + }, + { + "Question_id": "S-wave phase picking/0141", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 749", + "(B) 559", + "(C) 1436", + "(D) 417", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0141.png" + ] + }, + { + "Question_id": "S-wave phase picking/0142", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1392", + "(B) 1051", + "(C) 935", + "(D) 1246", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0142.png" + ] + }, + { + "Question_id": "S-wave phase picking/0143", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 483", + "(B) 623", + "(C) 832", + "(D) 750", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0143.png" + ] + }, + { + "Question_id": "S-wave phase picking/0144", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 849", + "(B) 1025", + "(C) 669", + "(D) 1487", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0144.png" + ] + }, + { + "Question_id": "S-wave phase picking/0145", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 739", + "(B) 999", + "(C) 1369", + "(D) 865", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0145.png" + ] + }, + { + "Question_id": "S-wave phase picking/0146", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 873", + "(B) 1506", + "(C) 1664", + "(D) 1791", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0146.png" + ] + }, + { + "Question_id": "S-wave phase picking/0147", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2840", + "(B) 3525", + "(C) 3379", + "(D) 3656", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0147.png" + ] + }, + { + "Question_id": "S-wave phase picking/0148", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 531", + "(B) 647", + "(C) 382", + "(D) 1199", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0148.png" + ] + }, + { + "Question_id": "S-wave phase picking/0149", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2403", + "(B) 2576", + "(C) 2254", + "(D) 1847", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0149.png" + ] + }, + { + "Question_id": "S-wave phase picking/0150", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1810", + "(B) 2004", + "(C) 1654", + "(D) 1415", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0150.png" + ] + }, + { + "Question_id": "S-wave phase picking/0151", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1453", + "(B) 1085", + "(C) 2219", + "(D) 1260", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0151.png" + ] + }, + { + "Question_id": "S-wave phase picking/0152", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 875", + "(B) 27", + "(C) 734", + "(D) 1044", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0152.png" + ] + }, + { + "Question_id": "S-wave phase picking/0153", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3428", + "(B) 3252", + "(C) 3617", + "(D) 4117", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0153.png" + ] + }, + { + "Question_id": "S-wave phase picking/0154", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1360", + "(B) 2321", + "(C) 2487", + "(D) 2200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0154.png" + ] + }, + { + "Question_id": "S-wave phase picking/0155", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 854", + "(B) 364", + "(C) 961", + "(D) 1082", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0155.png" + ] + }, + { + "Question_id": "S-wave phase picking/0156", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 689", + "(B) 584", + "(C) 460", + "(D) 137", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0156.png" + ] + }, + { + "Question_id": "S-wave phase picking/0157", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 645", + "(B) 839", + "(C) 988", + "(D) 454", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0157.png" + ] + }, + { + "Question_id": "S-wave phase picking/0158", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1090", + "(B) 804", + "(C) 953", + "(D) 1753", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0158.png" + ] + }, + { + "Question_id": "S-wave phase picking/0159", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1880", + "(B) 2072", + "(C) 1134", + "(D) 2216", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0159.png" + ] + }, + { + "Question_id": "S-wave phase picking/0160", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 990", + "(B) 2", + "(C) 716", + "(D) 850", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0160.png" + ] + }, + { + "Question_id": "S-wave phase picking/0161", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1998", + "(B) 2156", + "(C) 2858", + "(D) 2260", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0161.png" + ] + }, + { + "Question_id": "S-wave phase picking/0162", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1647", + "(B) 2119", + "(C) 1963", + "(D) 1781", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0162.png" + ] + }, + { + "Question_id": "S-wave phase picking/0163", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1351", + "(B) 1604", + "(C) 1491", + "(D) 1833", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0163.png" + ] + }, + { + "Question_id": "S-wave phase picking/0164", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1734", + "(B) 1486", + "(C) 2485", + "(D) 1605", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0164.png" + ] + }, + { + "Question_id": "S-wave phase picking/0165", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1237", + "(B) 1662", + "(C) 1050", + "(D) 1382", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0165.png" + ] + }, + { + "Question_id": "S-wave phase picking/0166", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 526", + "(B) 1283", + "(C) 1003", + "(D) 1179", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0166.png" + ] + }, + { + "Question_id": "S-wave phase picking/0167", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -104", + "(B) 583", + "(C) 860", + "(D) 752", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0167.png" + ] + }, + { + "Question_id": "S-wave phase picking/0168", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1206", + "(B) 2030", + "(C) 1096", + "(D) 960", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0168.png" + ] + }, + { + "Question_id": "S-wave phase picking/0169", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1182", + "(B) 1335", + "(C) 1002", + "(D) 1478", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0169.png" + ] + }, + { + "Question_id": "S-wave phase picking/0170", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1595", + "(B) 1269", + "(C) 1457", + "(D) 547", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0170.png" + ] + }, + { + "Question_id": "S-wave phase picking/0171", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2779", + "(B) 1981", + "(C) 1849", + "(D) 2126", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0171.png" + ] + }, + { + "Question_id": "S-wave phase picking/0172", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1089", + "(B) 771", + "(C) 1399", + "(D) 955", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0172.png" + ] + }, + { + "Question_id": "S-wave phase picking/0173", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1969", + "(B) 2165", + "(C) 2474", + "(D) 2354", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0173.png" + ] + }, + { + "Question_id": "S-wave phase picking/0174", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 561", + "(B) 664", + "(C) -4", + "(D) 453", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0174.png" + ] + }, + { + "Question_id": "S-wave phase picking/0175", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 722", + "(B) 1299", + "(C) 1153", + "(D) 1044", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0175.png" + ] + }, + { + "Question_id": "S-wave phase picking/0176", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1154", + "(B) 1347", + "(C) 1476", + "(D) 364", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0176.png" + ] + }, + { + "Question_id": "S-wave phase picking/0177", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 741", + "(B) 1529", + "(C) 916", + "(D) 1046", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0177.png" + ] + }, + { + "Question_id": "S-wave phase picking/0178", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1349", + "(B) 883", + "(C) 1151", + "(D) 1031", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0178.png" + ] + }, + { + "Question_id": "S-wave phase picking/0179", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 970", + "(B) 1128", + "(C) 25", + "(D) 772", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0179.png" + ] + }, + { + "Question_id": "S-wave phase picking/0180", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 538", + "(B) 1529", + "(C) 686", + "(D) 849", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0180.png" + ] + }, + { + "Question_id": "S-wave phase picking/0181", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1166", + "(B) 751", + "(C) 1284", + "(D) 977", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0181.png" + ] + }, + { + "Question_id": "S-wave phase picking/0182", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2183", + "(B) 2696", + "(C) 2037", + "(D) 1904", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0182.png" + ] + }, + { + "Question_id": "S-wave phase picking/0183", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 739", + "(B) 935", + "(C) 1067", + "(D) 1646", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0183.png" + ] + }, + { + "Question_id": "S-wave phase picking/0184", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1489", + "(B) 2256", + "(C) 1296", + "(D) 1608", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0184.png" + ] + }, + { + "Question_id": "S-wave phase picking/0185", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 623", + "(B) 1154", + "(C) 826", + "(D) 958", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0185.png" + ] + }, + { + "Question_id": "S-wave phase picking/0186", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1450", + "(B) 1272", + "(C) 1559", + "(D) 2160", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0186.png" + ] + }, + { + "Question_id": "S-wave phase picking/0187", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 666", + "(B) 1588", + "(C) 1709", + "(D) 1402", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0187.png" + ] + }, + { + "Question_id": "S-wave phase picking/0188", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1671", + "(B) 1781", + "(C) 1359", + "(D) 1535", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0188.png" + ] + }, + { + "Question_id": "S-wave phase picking/0189", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1411", + "(B) 1078", + "(C) 1923", + "(D) 1212", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0189.png" + ] + }, + { + "Question_id": "S-wave phase picking/0190", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1072", + "(B) 925", + "(C) 1273", + "(D) 1270", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0190.png" + ] + }, + { + "Question_id": "S-wave phase picking/0191", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1418", + "(B) 1122", + "(C) 942", + "(D) 817", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0191.png" + ] + }, + { + "Question_id": "S-wave phase picking/0192", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1143", + "(B) 23", + "(C) 1015", + "(D) 845", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0192.png" + ] + }, + { + "Question_id": "S-wave phase picking/0193", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1199", + "(B) 1369", + "(C) 966", + "(D) 1533", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0193.png" + ] + }, + { + "Question_id": "S-wave phase picking/0194", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 476", + "(B) 672", + "(C) -254", + "(D) 841", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0194.png" + ] + }, + { + "Question_id": "S-wave phase picking/0195", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1062", + "(B) 963", + "(C) 1337", + "(D) 1179", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0195.png" + ] + }, + { + "Question_id": "S-wave phase picking/0196", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1451", + "(B) 1122", + "(C) 307", + "(D) 1292", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0196.png" + ] + }, + { + "Question_id": "S-wave phase picking/0197", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1572", + "(B) 1744", + "(C) 1936", + "(D) 2041", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0197.png" + ] + }, + { + "Question_id": "S-wave phase picking/0198", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1724", + "(B) 787", + "(C) 1561", + "(D) 1439", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0198.png" + ] + }, + { + "Question_id": "S-wave phase picking/0199", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2763", + "(B) 2015", + "(C) 1713", + "(D) 1834", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0199.png" + ] + }, + { + "Question_id": "S-wave phase picking/0200", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 575", + "(B) 345", + "(C) 447", + "(D) -151", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0200.png" + ] + }, + { + "Question_id": "S-wave phase picking/0201", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2133", + "(B) 1612", + "(C) 1749", + "(D) 1455", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0201.png" + ] + }, + { + "Question_id": "S-wave phase picking/0202", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 455", + "(B) 652", + "(C) 742", + "(D) 326", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0202.png" + ] + }, + { + "Question_id": "S-wave phase picking/0203", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1515", + "(B) 1745", + "(C) 1924", + "(D) 1614", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0203.png" + ] + }, + { + "Question_id": "S-wave phase picking/0204", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 254", + "(B) 1020", + "(C) 1206", + "(D) 859", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0204.png" + ] + }, + { + "Question_id": "S-wave phase picking/0205", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3261", + "(B) 3412", + "(C) 2755", + "(D) 3596", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0205.png" + ] + }, + { + "Question_id": "S-wave phase picking/0206", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1249", + "(B) 2237", + "(C) 1565", + "(D) 1428", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0206.png" + ] + }, + { + "Question_id": "S-wave phase picking/0207", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1419", + "(B) 1541", + "(C) 2312", + "(D) 1296", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0207.png" + ] + }, + { + "Question_id": "S-wave phase picking/0208", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -171", + "(B) 732", + "(C) 846", + "(D) 540", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0208.png" + ] + }, + { + "Question_id": "S-wave phase picking/0209", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2308", + "(B) 1525", + "(C) 1367", + "(D) 1710", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0209.png" + ] + }, + { + "Question_id": "S-wave phase picking/0210", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 927", + "(B) 1113", + "(C) 741", + "(D) 1662", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0210.png" + ] + }, + { + "Question_id": "S-wave phase picking/0211", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1420", + "(B) 1154", + "(C) 1263", + "(D) 2216", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0211.png" + ] + }, + { + "Question_id": "S-wave phase picking/0212", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1389", + "(B) 1016", + "(C) 1200", + "(D) 935", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0212.png" + ] + }, + { + "Question_id": "S-wave phase picking/0213", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1199", + "(B) 759", + "(C) 1018", + "(D) 858", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0213.png" + ] + }, + { + "Question_id": "S-wave phase picking/0214", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1369", + "(B) 1052", + "(C) 1214", + "(D) 274", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0214.png" + ] + }, + { + "Question_id": "S-wave phase picking/0215", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 565", + "(B) 364", + "(C) 425", + "(D) 697", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0215.png" + ] + }, + { + "Question_id": "S-wave phase picking/0216", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 541", + "(B) 865", + "(C) 1065", + "(D) 715", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0216.png" + ] + }, + { + "Question_id": "S-wave phase picking/0217", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2131", + "(B) 1992", + "(C) 2194", + "(D) 1831", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0217.png" + ] + }, + { + "Question_id": "S-wave phase picking/0218", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1530", + "(B) 1020", + "(C) 732", + "(D) 860", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0218.png" + ] + }, + { + "Question_id": "S-wave phase picking/0219", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1982", + "(B) 1782", + "(C) 2478", + "(D) 2179", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0219.png" + ] + }, + { + "Question_id": "S-wave phase picking/0220", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2595", + "(B) 2756", + "(C) 1645", + "(D) 2458", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0220.png" + ] + }, + { + "Question_id": "S-wave phase picking/0221", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2142", + "(B) 1778", + "(C) 1965", + "(D) 1709", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0221.png" + ] + }, + { + "Question_id": "S-wave phase picking/0222", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 817", + "(B) 1291", + "(C) 1485", + "(D) 1171", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0222.png" + ] + }, + { + "Question_id": "S-wave phase picking/0223", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1652", + "(B) 994", + "(C) 1851", + "(D) 1515", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0223.png" + ] + }, + { + "Question_id": "S-wave phase picking/0224", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3414", + "(B) 2837", + "(C) 3743", + "(D) 3595", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0224.png" + ] + }, + { + "Question_id": "S-wave phase picking/0225", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2631", + "(B) 2202", + "(C) 3003", + "(D) 2805", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0225.png" + ] + }, + { + "Question_id": "S-wave phase picking/0226", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3048", + "(B) 2722", + "(C) 2882", + "(D) 2225", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0226.png" + ] + }, + { + "Question_id": "S-wave phase picking/0227", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1381", + "(B) 1526", + "(C) 1633", + "(D) 1209", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0227.png" + ] + }, + { + "Question_id": "S-wave phase picking/0228", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 694", + "(B) 1028", + "(C) 889", + "(D) 1205", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0228.png" + ] + }, + { + "Question_id": "S-wave phase picking/0229", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1397", + "(B) 1657", + "(C) 1117", + "(D) 1259", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0229.png" + ] + }, + { + "Question_id": "S-wave phase picking/0230", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1288", + "(B) 1399", + "(C) 1504", + "(D) 1102", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0230.png" + ] + }, + { + "Question_id": "S-wave phase picking/0231", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1812", + "(B) 885", + "(C) 1119", + "(D) 992", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0231.png" + ] + }, + { + "Question_id": "S-wave phase picking/0232", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1001", + "(B) 883", + "(C) 1810", + "(D) 1186", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0232.png" + ] + }, + { + "Question_id": "S-wave phase picking/0233", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1936", + "(B) 1779", + "(C) 2317", + "(D) 2070", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0233.png" + ] + }, + { + "Question_id": "S-wave phase picking/0234", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 942", + "(B) 1402", + "(C) 788", + "(D) 665", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0234.png" + ] + }, + { + "Question_id": "S-wave phase picking/0235", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 764", + "(B) 951", + "(C) 1144", + "(D) 1785", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0235.png" + ] + }, + { + "Question_id": "S-wave phase picking/0236", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 884", + "(B) 698", + "(C) 498", + "(D) 1436", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0236.png" + ] + }, + { + "Question_id": "S-wave phase picking/0237", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1856", + "(B) 2024", + "(C) 1749", + "(D) 2298", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0237.png" + ] + }, + { + "Question_id": "S-wave phase picking/0238", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 943", + "(B) 1556", + "(C) 1116", + "(D) 1248", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0238.png" + ] + }, + { + "Question_id": "S-wave phase picking/0239", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1443", + "(B) 1747", + "(C) 1620", + "(D) 2306", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0239.png" + ] + }, + { + "Question_id": "S-wave phase picking/0240", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1181", + "(B) 1386", + "(C) 1054", + "(D) 1345", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0240.png" + ] + }, + { + "Question_id": "S-wave phase picking/0241", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1284", + "(B) 1102", + "(C) 812", + "(D) 1399", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0241.png" + ] + }, + { + "Question_id": "S-wave phase picking/0242", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2333", + "(B) 2644", + "(C) 3466", + "(D) 2467", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0242.png" + ] + }, + { + "Question_id": "S-wave phase picking/0243", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1868", + "(B) 2020", + "(C) 2353", + "(D) 1707", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0243.png" + ] + }, + { + "Question_id": "S-wave phase picking/0244", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 650", + "(B) 928", + "(C) 778", + "(D) -27", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0244.png" + ] + }, + { + "Question_id": "S-wave phase picking/0245", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1289", + "(B) 1103", + "(C) 1375", + "(D) 969", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0245.png" + ] + }, + { + "Question_id": "S-wave phase picking/0246", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1812", + "(B) 2587", + "(C) 1709", + "(D) 1945", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0246.png" + ] + }, + { + "Question_id": "S-wave phase picking/0247", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1267", + "(B) 983", + "(C) 1137", + "(D) 881", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0247.png" + ] + }, + { + "Question_id": "S-wave phase picking/0248", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2252", + "(B) 2410", + "(C) 1491", + "(D) 2596", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0248.png" + ] + }, + { + "Question_id": "S-wave phase picking/0249", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1010", + "(B) 1349", + "(C) 1830", + "(D) 1192", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0249.png" + ] + }, + { + "Question_id": "S-wave phase picking/0250", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 772", + "(B) 949", + "(C) 1355", + "(D) 1082", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0250.png" + ] + }, + { + "Question_id": "S-wave phase picking/0251", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1059", + "(B) 1327", + "(C) 1204", + "(D) 951", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0251.png" + ] + }, + { + "Question_id": "S-wave phase picking/0252", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1015", + "(B) 2008", + "(C) 1166", + "(D) 1359", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0252.png" + ] + }, + { + "Question_id": "S-wave phase picking/0253", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1458", + "(B) 651", + "(C) 781", + "(D) 490", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0253.png" + ] + }, + { + "Question_id": "S-wave phase picking/0254", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1072", + "(B) 818", + "(C) 894", + "(D) 1215", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0254.png" + ] + }, + { + "Question_id": "S-wave phase picking/0255", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 972", + "(B) 1365", + "(C) 1672", + "(D) 1492", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0255.png" + ] + }, + { + "Question_id": "S-wave phase picking/0256", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1292", + "(B) 990", + "(C) 1114", + "(D) 867", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0256.png" + ] + }, + { + "Question_id": "S-wave phase picking/0257", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1140", + "(B) 1435", + "(C) 739", + "(D) 1269", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0257.png" + ] + }, + { + "Question_id": "S-wave phase picking/0258", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1939", + "(B) 2412", + "(C) 1774", + "(D) 1618", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0258.png" + ] + }, + { + "Question_id": "S-wave phase picking/0259", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1744", + "(B) 2123", + "(C) 1557", + "(D) 1885", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0259.png" + ] + }, + { + "Question_id": "S-wave phase picking/0260", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 468", + "(B) 275", + "(C) 176", + "(D) 576", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0260.png" + ] + }, + { + "Question_id": "S-wave phase picking/0261", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1491", + "(B) 1126", + "(C) 1990", + "(D) 1326", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0261.png" + ] + }, + { + "Question_id": "S-wave phase picking/0262", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 831", + "(B) 596", + "(C) 488", + "(D) 765", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0262.png" + ] + }, + { + "Question_id": "S-wave phase picking/0263", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1880", + "(B) 2219", + "(C) 2715", + "(D) 2021", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0263.png" + ] + }, + { + "Question_id": "S-wave phase picking/0264", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1448", + "(B) 488", + "(C) 1077", + "(D) 1261", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0264.png" + ] + }, + { + "Question_id": "S-wave phase picking/0265", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2004", + "(B) 1690", + "(C) 1527", + "(D) 1411", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0265.png" + ] + }, + { + "Question_id": "S-wave phase picking/0266", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1229", + "(B) 956", + "(C) 394", + "(D) 1087", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0266.png" + ] + }, + { + "Question_id": "S-wave phase picking/0267", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 450", + "(B) 1027", + "(C) 593", + "(D) 752", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0267.png" + ] + }, + { + "Question_id": "S-wave phase picking/0268", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1203", + "(B) 1371", + "(C) 1077", + "(D) 549", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0268.png" + ] + }, + { + "Question_id": "S-wave phase picking/0269", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 544", + "(B) 842", + "(C) 673", + "(D) 1567", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0269.png" + ] + }, + { + "Question_id": "S-wave phase picking/0270", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -45", + "(B) 953", + "(C) 822", + "(D) 632", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0270.png" + ] + }, + { + "Question_id": "S-wave phase picking/0271", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1819", + "(B) 1077", + "(C) 878", + "(D) 725", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0271.png" + ] + }, + { + "Question_id": "S-wave phase picking/0272", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1269", + "(B) 1088", + "(C) 566", + "(D) 904", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0272.png" + ] + }, + { + "Question_id": "S-wave phase picking/0273", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 589", + "(B) 1596", + "(C) 794", + "(D) 693", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0273.png" + ] + }, + { + "Question_id": "S-wave phase picking/0274", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1007", + "(B) 1166", + "(C) 801", + "(D) 1313", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0274.png" + ] + }, + { + "Question_id": "S-wave phase picking/0275", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 593", + "(B) 936", + "(C) 1226", + "(D) 1121", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0275.png" + ] + }, + { + "Question_id": "S-wave phase picking/0276", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 524", + "(B) 648", + "(C) 1012", + "(D) 784", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0276.png" + ] + }, + { + "Question_id": "S-wave phase picking/0277", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1437", + "(B) 1028", + "(C) 1206", + "(D) 917", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0277.png" + ] + }, + { + "Question_id": "S-wave phase picking/0278", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 854", + "(B) 969", + "(C) 1460", + "(D) 666", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0278.png" + ] + }, + { + "Question_id": "S-wave phase picking/0279", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1416", + "(B) 1655", + "(C) 1545", + "(D) 1130", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0279.png" + ] + }, + { + "Question_id": "S-wave phase picking/0280", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1997", + "(B) 2582", + "(C) 1680", + "(D) 1810", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0280.png" + ] + }, + { + "Question_id": "S-wave phase picking/0281", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1799", + "(B) 1381", + "(C) 1469", + "(D) 1637", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0281.png" + ] + }, + { + "Question_id": "S-wave phase picking/0282", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2244", + "(B) 1550", + "(C) 1270", + "(D) 1385", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0282.png" + ] + }, + { + "Question_id": "S-wave phase picking/0283", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2153", + "(B) 1813", + "(C) 1924", + "(D) 2059", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0283.png" + ] + }, + { + "Question_id": "S-wave phase picking/0284", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1324", + "(B) 1213", + "(C) 2187", + "(D) 1467", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0284.png" + ] + }, + { + "Question_id": "S-wave phase picking/0285", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 567", + "(B) 440", + "(C) 694", + "(D) 799", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0285.png" + ] + }, + { + "Question_id": "S-wave phase picking/0286", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 903", + "(B) 787", + "(C) 1090", + "(D) 1268", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0286.png" + ] + }, + { + "Question_id": "S-wave phase picking/0287", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 985", + "(B) 1173", + "(C) 1310", + "(D) 1433", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0287.png" + ] + }, + { + "Question_id": "S-wave phase picking/0288", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1853", + "(B) 2579", + "(C) 1993", + "(D) 1713", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0288.png" + ] + }, + { + "Question_id": "S-wave phase picking/0289", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 412", + "(B) 1173", + "(C) 715", + "(D) 549", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0289.png" + ] + }, + { + "Question_id": "S-wave phase picking/0290", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1692", + "(B) 979", + "(C) 1250", + "(D) 1123", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0290.png" + ] + }, + { + "Question_id": "S-wave phase picking/0291", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1117", + "(B) 869", + "(C) 999", + "(D) 273", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0291.png" + ] + }, + { + "Question_id": "S-wave phase picking/0292", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1911", + "(B) 2232", + "(C) 2045", + "(D) 2927", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0292.png" + ] + }, + { + "Question_id": "S-wave phase picking/0293", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1526", + "(B) 1399", + "(C) 1765", + "(D) 1633", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0293.png" + ] + }, + { + "Question_id": "S-wave phase picking/0294", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2222", + "(B) 1627", + "(C) 1512", + "(D) 1347", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0294.png" + ] + }, + { + "Question_id": "S-wave phase picking/0295", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1850", + "(B) 1726", + "(C) 1600", + "(D) 1330", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0295.png" + ] + }, + { + "Question_id": "S-wave phase picking/0296", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1212", + "(B) 1042", + "(C) 904", + "(D) 545", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0296.png" + ] + }, + { + "Question_id": "S-wave phase picking/0297", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 876", + "(B) 182", + "(C) 980", + "(D) 1167", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0297.png" + ] + }, + { + "Question_id": "S-wave phase picking/0298", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 209", + "(B) 1149", + "(C) 856", + "(D) 973", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0298.png" + ] + }, + { + "Question_id": "S-wave phase picking/0299", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, determine the exact onset of S-wave phases in three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize horizontal-component (E & N) polarization analysis validated by transverse energy ratios, with supplementary vertical-component consistency verification. Output a integer [x] relative to sample index 0, rounded to nearest valid phase estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "S-wave phase picking", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1747", + "(B) 1380", + "(C) 1872", + "(D) 2052", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/S-wave/STEAD_Waveform_0299.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/earthquake_or_noise_classification.json b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/earthquake_or_noise_classification.json new file mode 100644 index 0000000000000000000000000000000000000000..8676f4e95f35b248f732d3f3c5420d435f11b503 --- /dev/null +++ b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Perception/earthquake_or_noise_classification.json @@ -0,0 +1,5702 @@ +[ + { + "Question_id": "earthquake or noise classification/0000", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0000.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0001", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0001.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0002", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0002.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0003", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0003.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0004", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0004.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0005", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0005.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0006", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0006.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0007", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0007.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0008", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0008.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0009", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0009.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0010", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0010.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0011", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0011.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0012", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0012.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0013", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0013.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0014", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0014.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0015", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0015.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0016", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0016.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0017", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0017.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0018", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0018.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0019", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0019.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0020", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0020.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0021", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0021.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0022", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0022.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0023", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0023.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0024", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0024.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0025", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0025.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0026", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0026.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0027", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0027.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0028", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0028.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0029", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0029.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0030", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0030.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0031", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0031.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0032", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0032.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0033", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0033.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0034", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0034.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0035", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0035.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0036", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0036.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0037", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0037.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0038", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0038.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0039", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0039.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0040", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0040.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0041", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0041.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0042", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0042.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0043", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0043.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0044", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0044.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0045", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0045.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0046", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0046.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0047", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0047.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0048", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0048.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0049", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0049.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0050", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0050.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0051", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0051.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0052", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0052.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0053", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0053.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0054", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0054.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0055", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0055.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0056", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0056.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0057", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0057.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0058", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0058.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0059", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0059.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0060", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0060.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0061", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0061.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0062", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0062.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0063", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0063.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0064", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0064.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0065", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0065.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0066", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0066.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0067", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0067.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0068", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0068.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0069", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0069.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0070", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0070.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0071", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0071.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0072", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0072.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0073", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0073.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0074", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0074.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0075", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0075.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0076", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0076.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0077", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0077.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0078", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0078.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0079", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0079.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0080", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0080.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0081", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0081.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0082", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0082.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0083", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0083.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0084", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0084.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0085", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0085.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0086", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0086.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0087", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0087.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0088", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0088.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0089", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0089.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0090", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0090.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0091", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0091.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0092", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0092.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0093", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0093.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0094", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0094.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0095", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0095.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0096", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0096.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0097", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0097.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0098", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0098.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0099", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0099.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0100", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0100.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0101", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0101.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0102", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0102.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0103", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0103.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0104", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0104.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0105", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0105.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0106", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0106.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0107", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0107.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0108", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0108.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0109", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0109.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0110", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0110.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0111", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0111.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0112", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0112.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0113", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0113.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0114", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0114.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0115", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0115.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0116", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0116.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0117", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0117.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0118", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0118.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0119", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0119.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0120", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0120.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0121", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0121.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0122", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0122.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0123", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0123.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0124", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0124.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0125", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0125.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0126", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0126.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0127", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0127.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0128", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0128.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0129", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0129.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0130", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0130.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0131", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0131.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0132", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0132.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0133", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0133.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0134", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0134.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0135", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0135.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0136", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0136.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0137", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0137.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0138", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0138.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0139", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0139.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0140", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0140.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0141", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0141.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0142", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0142.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0143", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0143.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0144", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0144.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0145", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0145.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0146", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0146.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0147", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0147.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0148", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0148.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0149", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0149.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0150", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0150.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0151", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0151.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0152", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0152.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0153", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0153.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0154", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0154.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0155", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0155.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0156", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0156.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0157", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0157.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0158", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0158.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0159", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0159.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0160", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0160.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0161", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0161.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0162", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0162.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0163", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0163.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0164", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0164.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0165", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0165.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0166", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0166.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0167", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0167.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0168", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0168.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0169", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0169.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0170", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0170.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0171", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0171.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0172", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0172.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0173", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0173.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0174", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0174.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0175", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0175.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0176", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0176.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0177", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0177.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0178", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0178.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0179", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0179.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0180", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0180.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0181", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0181.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0182", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0182.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0183", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0183.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0184", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0184.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0185", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0185.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0186", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0186.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0187", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0187.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0188", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0188.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0189", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0189.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0190", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0190.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0191", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0191.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0192", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0192.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0193", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0193.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0194", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0194.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0195", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0195.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0196", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0196.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0197", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0197.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0198", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0198.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0199", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0199.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0200", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0200.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0201", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0201.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0202", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0202.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0203", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0203.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0204", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0204.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0205", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0205.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0206", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0206.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0207", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0207.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0208", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0208.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0209", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0209.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0210", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0210.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0211", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0211.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0212", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0212.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0213", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0213.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0214", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0214.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0215", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0215.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0216", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0216.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0217", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0217.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0218", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0218.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0219", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0219.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0220", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0220.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0221", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0221.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0222", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0222.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0223", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0223.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0224", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0224.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0225", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0225.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0226", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0226.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0227", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0227.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0228", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0228.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0229", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0229.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0230", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0230.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0231", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0231.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0232", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0232.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0233", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0233.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0234", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0234.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0235", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0235.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0236", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0236.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0237", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0237.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0238", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0238.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0239", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0239.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0240", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0240.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0241", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0241.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0242", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0242.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0243", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0243.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0244", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0244.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0245", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0245.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0246", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0246.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0247", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0247.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0248", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0248.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0249", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0249.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0250", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0250.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0251", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0251.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0252", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0252.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0253", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0253.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0254", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0254.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0255", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0255.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0256", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0256.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0257", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0257.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0258", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0258.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0259", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0259.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0260", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0260.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0261", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0261.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0262", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0262.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0263", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0263.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0264", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0264.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0265", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0265.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0266", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0266.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0267", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0267.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0268", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0268.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0269", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0269.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0270", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0270.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0271", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0271.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0272", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0272.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0273", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0273.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0274", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0274.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0275", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0275.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0276", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0276.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0277", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0277.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0278", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0278.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0279", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0279.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0280", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0280.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0281", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0281.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0282", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0282.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0283", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0283.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0284", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0284.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0285", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0285.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0286", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0286.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0287", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0287.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0288", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0288.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0289", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0289.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0290", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0290.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0291", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0291.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0292", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0292.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0293", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0293.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0294", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0294.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0295", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0295.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0296", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0296.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0297", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0297.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0298", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0298.png" + ] + }, + { + "Question_id": "earthquake or noise classification/0299", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, examine the three-component ENZ seismic data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate) and determine whether this waveform exists an earthquake event or background noise. Consider the signal characteristics, amplitude patterns, and phase coherence across components to make your determination.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Perception", + "L4-task": "earthquake or noise classification", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) Earthquake", + "(B) Noise", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Earthquake_or_Noise/STEAD_Waveform_0299.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_magnitude_estimation.json b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_magnitude_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..423420ee828b62b990b22c858f0d984fc5730867 --- /dev/null +++ b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_magnitude_estimation.json @@ -0,0 +1,6302 @@ +[ + { + "Question_id": "earthquake magnitude estimation/0000", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.8", + "(B) 1.8", + "(C) 3.2", + "(D) 1.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0000.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0001", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 2.9", + "(C) 0.5", + "(D) 4.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0001.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0002", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.5", + "(B) -1.1", + "(C) 2.6", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0002.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0003", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.4", + "(B) 1.8", + "(C) 1.8", + "(D) 3.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0003.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0004", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 3.8", + "(C) 1.0", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0004.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0005", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.1", + "(B) 2.8", + "(C) 1.9", + "(D) 0.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0005.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0006", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 1.9", + "(C) 2.5", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0006.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0007", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.5", + "(B) -1.6", + "(C) 0.2", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0007.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0008", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.1", + "(B) 1.1", + "(C) -1.9", + "(D) -0.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0008.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0009", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) 3.6", + "(C) 0.7", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0009.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0010", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.5", + "(B) 1.9", + "(C) 1.0", + "(D) 4.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0010.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0011", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) 1.4", + "(C) -0.6", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0011.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0012", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 0.3", + "(C) -1.6", + "(D) 1.6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0012.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0013", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) 4.5", + "(C) 2.0", + "(D) 5.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0013.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0014", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 0.5", + "(C) 1.8", + "(D) 3.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0014.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0015", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.4", + "(B) 3.2", + "(C) 1.7", + "(D) 5.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0015.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0016", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.6", + "(B) -0.7", + "(C) 1.3", + "(D) 2.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0016.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0017", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 4.0", + "(C) 2.0", + "(D) 3.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0017.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0018", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) -0.1", + "(C) 1.6", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0018.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0019", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.5", + "(B) 3.1", + "(C) 2.5", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0019.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0020", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.9", + "(B) 3.9", + "(C) 4.1", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0020.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0021", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 2.4", + "(C) -0.7", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0021.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0022", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.3", + "(B) 0.7", + "(C) 0.0", + "(D) 2.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0022.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0023", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.6", + "(B) 1.5", + "(C) 2.5", + "(D) -0.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0023.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0024", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 0.7", + "(C) 0.0", + "(D) -0.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0024.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0025", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.6", + "(B) -2.4", + "(C) 1.2", + "(D) -0.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0025.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0026", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 2.4", + "(C) 3.1", + "(D) 0.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0026.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0027", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) 0.4", + "(C) 3.1", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0027.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0028", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 0.8", + "(C) 0.0", + "(D) -2.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0028.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0029", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.3", + "(B) -0.3", + "(C) -0.2", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0029.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0030", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.3", + "(B) 1.3", + "(C) -1.7", + "(D) -0.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0030.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0031", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 1.0", + "(C) 3.0", + "(D) 0.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0031.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0032", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.4", + "(B) 1.6", + "(C) 2.3", + "(D) -0.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0032.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0033", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.0", + "(B) 1.8", + "(C) 2.5", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0033.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0034", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 6.3", + "(B) 5.2", + "(C) 3.0", + "(D) 4.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0034.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0035", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 1.5", + "(C) 0.7", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0035.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0036", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.0", + "(B) 1.0", + "(C) 0.5", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0036.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0037", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) -0.8", + "(C) 1.9", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0037.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0038", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 0.8", + "(C) 2.4", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0038.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0039", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) 0.3", + "(C) 2.3", + "(D) -0.8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0039.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0040", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.8", + "(B) 1.2", + "(C) 2.3", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0040.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0041", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.5", + "(B) 2.5", + "(C) 3.4", + "(D) 6.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0041.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0042", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.2", + "(B) 4.2", + "(C) 2.2", + "(D) 4.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0042.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0043", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 2.3", + "(C) -0.6", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0043.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0044", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 0.2", + "(C) 3.8", + "(D) 3.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0044.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0045", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.6", + "(B) 1.6", + "(C) 0.6", + "(D) -1.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0045.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0046", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) 1.1", + "(C) 0.3", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0046.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0047", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.2", + "(B) 3.2", + "(C) -1.6", + "(D) 1.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0047.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0048", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 3.8", + "(C) 0.8", + "(D) -1.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0048.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0049", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.2", + "(B) 4.4", + "(C) -0.3", + "(D) 1.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0049.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0050", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) -2.5", + "(C) -0.8", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0050.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0051", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 4.2", + "(C) 5.6", + "(D) 2.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0051.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0052", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.4", + "(B) 3.4", + "(C) 1.4", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0052.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0053", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) -0.3", + "(C) 2.4", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0053.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0054", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.0", + "(B) -2.7", + "(C) 0.3", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0054.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0055", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.7", + "(B) 3.5", + "(C) 2.6", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0055.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0056", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) -1.9", + "(C) 1.6", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0056.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0057", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 6.1", + "(B) 4.1", + "(C) 2.8", + "(D) 5.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0057.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0058", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.0", + "(B) -1.4", + "(C) 3.4", + "(D) 0.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0058.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0059", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.9", + "(B) 0.1", + "(C) 0.9", + "(D) -2.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0059.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0060", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.3", + "(B) -0.1", + "(C) 3.1", + "(D) -0.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0060.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0061", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) -0.1", + "(C) -1.4", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0061.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0062", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.0", + "(B) 0.6", + "(C) -2.4", + "(D) 0.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0062.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0063", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 2.9", + "(C) 1.4", + "(D) 5.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0063.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0064", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.3", + "(B) 3.6", + "(C) 0.6", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0064.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0065", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) -0.4", + "(C) 2.7", + "(D) 3.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0065.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0066", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.5", + "(B) -1.2", + "(C) 0.5", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0066.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0067", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 0.8", + "(C) 0.2", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0067.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0068", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 2.2", + "(C) -1.1", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0068.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0069", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.0", + "(B) 0.9", + "(C) 3.9", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0069.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0070", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 1.1", + "(C) 2.4", + "(D) -0.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0070.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0071", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.0", + "(B) 2.0", + "(C) 3.2", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0071.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0072", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) 3.3", + "(C) 5.3", + "(D) 3.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0072.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0073", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 0.1", + "(C) -1.1", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0073.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0074", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.4", + "(B) 3.7", + "(C) 5.4", + "(D) 0.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0074.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0075", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) 1.5", + "(C) 4.9", + "(D) 4.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0075.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0076", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.5", + "(B) 2.7", + "(C) -0.4", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0076.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0077", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 3.5", + "(C) 4.7", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0077.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0078", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 2.7", + "(C) 0.8", + "(D) -0.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0078.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0079", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 1.9", + "(C) -1.9", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0079.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0080", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.3", + "(B) -0.3", + "(C) 1.7", + "(D) 2.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0080.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0081", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) 4.1", + "(C) 0.8", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0081.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0082", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.1", + "(B) 0.5", + "(C) 1.1", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0082.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0083", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 1.8", + "(C) 0.8", + "(D) -0.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0083.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0084", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 2.8", + "(C) 1.9", + "(D) 4.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0084.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0085", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.6", + "(B) 0.6", + "(C) 2.4", + "(D) -0.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0085.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0086", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 3.5", + "(C) 1.5", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0086.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0087", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) -0.9", + "(C) 1.1", + "(D) 3.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0087.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0088", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 2.9", + "(C) 0.9", + "(D) 2.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0088.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0089", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 4.1", + "(C) 5.8", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0089.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0090", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 2.4", + "(C) 3.7", + "(D) 2.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0090.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0091", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.9", + "(B) 6.2", + "(C) 3.2", + "(D) 2.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0091.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0092", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.2", + "(B) 4.8", + "(C) 3.4", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0092.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0093", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 1.8", + "(C) -1.2", + "(D) 3.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0093.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0094", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.8", + "(B) 1.8", + "(C) 1.7", + "(D) 3.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0094.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0095", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.6", + "(B) 0.2", + "(C) 1.8", + "(D) -1.8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0095.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0096", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.4", + "(B) 3.4", + "(C) -0.7", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0096.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0097", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) -2.2", + "(C) 1.0", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0097.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0098", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.2", + "(B) 1.6", + "(C) 1.7", + "(D) -0.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0098.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0099", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.2", + "(B) 3.7", + "(C) 0.7", + "(D) 2.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0099.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0100", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 0.5", + "(C) 3.5", + "(D) 4.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0100.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0101", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) 1.6", + "(C) 4.6", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0101.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0102", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 3.4", + "(C) 0.9", + "(D) 3.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0102.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0103", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.4", + "(B) 1.3", + "(C) 2.0", + "(D) -0.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0103.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0104", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.4", + "(B) 2.8", + "(C) 3.1", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0104.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0105", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.5", + "(B) 1.2", + "(C) 1.7", + "(D) -0.8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0105.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0106", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 1.9", + "(C) 2.3", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0106.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0107", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) 2.9", + "(C) 0.9", + "(D) 2.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0107.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0108", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) -1.0", + "(C) 1.8", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0108.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0109", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.0", + "(B) 2.0", + "(C) 2.6", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0109.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0110", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) 3.3", + "(C) 2.4", + "(D) 1.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0110.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0111", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 1.8", + "(C) -1.1", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0111.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0112", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.2", + "(B) -1.2", + "(C) -0.1", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0112.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0113", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 3.7", + "(C) 0.7", + "(D) 0.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0113.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0114", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 2.0", + "(C) 2.8", + "(D) 4.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0114.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0115", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 7.4", + "(B) 3.1", + "(C) 6.2", + "(D) 4.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0115.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0116", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) 1.6", + "(C) -0.6", + "(D) -1.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0116.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0117", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.3", + "(B) 1.8", + "(C) 4.0", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0117.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0118", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.3", + "(B) -0.3", + "(C) 0.5", + "(D) 3.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0118.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0119", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.6", + "(B) 1.4", + "(C) 3.1", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0119.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0120", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.5", + "(B) 4.8", + "(C) 1.8", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0120.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0121", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.3", + "(B) 2.0", + "(C) -1.7", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0121.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0122", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.2", + "(B) -0.1", + "(C) 1.8", + "(D) 3.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0122.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0123", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.0", + "(B) 1.7", + "(C) -2.0", + "(D) -0.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0123.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0124", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.3", + "(B) 0.4", + "(C) 2.2", + "(D) 5.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0124.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0125", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.2", + "(B) 0.3", + "(C) -0.8", + "(D) -1.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0125.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0126", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) -1.7", + "(C) 1.6", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0126.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0127", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) -0.6", + "(C) 1.4", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0127.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0128", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.5", + "(B) 1.3", + "(C) 4.3", + "(D) 3.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0128.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0129", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 3.3", + "(C) 1.9", + "(D) -1.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0129.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0130", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.4", + "(B) 0.1", + "(C) 1.3", + "(D) -1.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0130.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0131", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.3", + "(B) -1.7", + "(C) 2.9", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0131.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0132", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.9", + "(B) 1.5", + "(C) 3.2", + "(D) -1.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0132.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0133", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 2.5", + "(C) 0.8", + "(D) -1.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0133.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0134", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.3", + "(B) -1.1", + "(C) 1.9", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0134.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0135", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.9", + "(B) 2.5", + "(C) 3.4", + "(D) 5.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0135.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0136", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.5", + "(B) 0.6", + "(C) 2.6", + "(D) 1.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0136.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0137", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.5", + "(B) 3.7", + "(C) 0.7", + "(D) 1.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0137.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0138", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 2.9", + "(C) 1.0", + "(D) -2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0138.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0139", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.8", + "(B) 0.1", + "(C) -2.9", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0139.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0140", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.4", + "(B) 1.6", + "(C) 2.3", + "(D) 1.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0140.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0141", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) 3.3", + "(C) 1.4", + "(D) -0.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0141.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0142", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.7", + "(B) 1.3", + "(C) -0.0", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0142.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0143", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) -2.6", + "(C) 0.4", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0143.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0144", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) -1.0", + "(C) 0.8", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0144.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0145", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.3", + "(B) 2.0", + "(C) 5.2", + "(D) 2.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0145.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0146", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) 1.7", + "(C) 2.8", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0146.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0147", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 6.5", + "(B) 5.8", + "(C) 4.2", + "(D) 4.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0147.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0148", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.6", + "(B) -2.1", + "(C) 0.1", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0148.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0149", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.3", + "(B) 1.7", + "(C) 1.3", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0149.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0150", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) -0.7", + "(C) 2.8", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0150.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0151", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.0", + "(B) 3.6", + "(C) 4.0", + "(D) 1.6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0151.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0152", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.8", + "(B) 1.2", + "(C) 3.0", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0152.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0153", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.2", + "(B) 3.2", + "(C) 1.4", + "(D) -1.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0153.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0154", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 1.9", + "(C) 2.6", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0154.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0155", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 2.4", + "(C) -0.0", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0155.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0156", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 4.7", + "(C) 2.9", + "(D) 4.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0156.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0157", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) 2.1", + "(C) 0.9", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0157.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0158", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.2", + "(B) 4.0", + "(C) 2.2", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0158.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0159", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) -1.6", + "(C) 2.6", + "(D) -0.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0159.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0160", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.3", + "(B) 2.5", + "(C) 1.9", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0160.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0161", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 1.2", + "(C) 0.2", + "(D) 4.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0161.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0162", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 1.3", + "(C) 0.9", + "(D) -2.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0162.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0163", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) 0.3", + "(C) 1.9", + "(D) -1.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0163.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0164", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.1", + "(B) 0.9", + "(C) 2.6", + "(D) 0.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0164.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0165", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.5", + "(B) 0.8", + "(C) 1.5", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0165.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0166", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.2", + "(B) 1.4", + "(C) 3.3", + "(D) -0.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0166.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0167", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.0", + "(B) 0.2", + "(C) 2.7", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0167.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0168", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.1", + "(B) -1.3", + "(C) 0.1", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0168.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0169", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.3", + "(B) -2.0", + "(C) 2.1", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0169.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0170", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.8", + "(B) 2.9", + "(C) 2.1", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0170.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0171", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) -0.4", + "(C) 2.1", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0171.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0172", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.1", + "(B) 1.8", + "(C) 0.1", + "(D) -1.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0172.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0173", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 2.1", + "(C) 4.9", + "(D) 4.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0173.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0174", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 1.4", + "(C) 4.2", + "(D) 3.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0174.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0175", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.1", + "(B) 0.2", + "(C) 1.1", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0175.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0176", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.6", + "(B) 1.4", + "(C) 1.5", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0176.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0177", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 2.3", + "(C) -0.3", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0177.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0178", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.4", + "(B) 1.3", + "(C) -0.4", + "(D) 4.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0178.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0179", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.4", + "(B) 1.3", + "(C) -1.0", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0179.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0180", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 0.9", + "(C) 0.6", + "(D) 2.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0180.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0181", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) -0.4", + "(C) 1.2", + "(D) 3.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0181.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0182", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) 4.6", + "(C) 1.6", + "(D) 2.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0182.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0183", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.7", + "(B) 0.9", + "(C) 1.3", + "(D) 2.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0183.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0184", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) -0.4", + "(C) 2.6", + "(D) 4.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0184.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0185", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.1", + "(B) 3.7", + "(C) 2.4", + "(D) 1.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0185.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0186", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.0", + "(B) 2.0", + "(C) 0.1", + "(D) 3.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0186.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0187", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.0", + "(B) 0.1", + "(C) 4.0", + "(D) 3.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0187.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0188", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) 1.7", + "(C) 0.6", + "(D) -1.2", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0188.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0189", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.4", + "(B) 0.7", + "(C) 0.4", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0189.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0190", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) 3.4", + "(C) 2.3", + "(D) 0.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0190.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0191", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) -1.1", + "(C) 0.8", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0191.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0192", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.2", + "(B) 3.2", + "(C) 0.2", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0192.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0193", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.4", + "(B) 2.5", + "(C) -0.2", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0193.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0194", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 1.9", + "(C) 3.3", + "(D) 4.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0194.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0195", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.6", + "(B) 1.4", + "(C) 3.4", + "(D) 4.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0195.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0196", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) -2.5", + "(C) 0.5", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0196.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0197", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 3.7", + "(C) 2.4", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0197.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0198", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) 0.5", + "(C) 1.6", + "(D) 3.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0198.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0199", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.3", + "(B) 3.3", + "(C) 1.6", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0199.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0200", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) -2.2", + "(C) 1.5", + "(D) -0.4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0200.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0201", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.6", + "(B) 1.5", + "(C) 3.6", + "(D) 3.6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0201.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0202", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.2", + "(B) 3.0", + "(C) 1.0", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0202.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0203", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 1.9", + "(C) 1.8", + "(D) 4.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0203.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0204", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.6", + "(B) 0.7", + "(C) 2.2", + "(D) -2.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0204.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0205", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 1.5", + "(C) 0.4", + "(D) -1.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0205.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0206", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 0.6", + "(C) 0.1", + "(D) 2.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0206.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0207", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.1", + "(B) 3.4", + "(C) 2.9", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0207.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0208", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.3", + "(B) 3.9", + "(C) 0.8", + "(D) 2.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0208.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0209", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.4", + "(B) 4.4", + "(C) 1.8", + "(D) 3.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0209.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0210", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) -1.0", + "(C) 0.9", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0210.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0211", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.6", + "(B) 0.4", + "(C) -1.2", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0211.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0212", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.1", + "(B) 1.8", + "(C) 0.8", + "(D) -1.2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0212.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0213", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.0", + "(B) 0.0", + "(C) 3.2", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0213.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0214", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 1.2", + "(C) 0.7", + "(D) 3.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0214.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0215", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.9", + "(B) 4.1", + "(C) -0.2", + "(D) 1.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0215.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0216", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 8.0", + "(B) 5.0", + "(C) 6.3", + "(D) 4.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0216.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0217", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 0.2", + "(C) -1.4", + "(D) 3.2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0217.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0218", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) -1.0", + "(C) 1.3", + "(D) -1.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0218.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0219", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.6", + "(B) -2.3", + "(C) 0.7", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0219.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0220", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.7", + "(B) -1.4", + "(C) 0.8", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0220.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0221", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.3", + "(B) 2.1", + "(C) -1.4", + "(D) -1.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0221.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0222", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.5", + "(B) -2.5", + "(C) 2.2", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0222.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0223", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.2", + "(B) 4.7", + "(C) 3.0", + "(D) 1.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0223.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0224", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.4", + "(B) 2.1", + "(C) 0.6", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0224.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0225", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.4", + "(B) 2.0", + "(C) 0.5", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0225.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0226", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) -1.2", + "(C) 1.3", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0226.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0227", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.9", + "(B) 3.1", + "(C) 4.9", + "(D) 1.9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0227.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0228", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.1", + "(B) 1.9", + "(C) -0.1", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0228.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0229", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 3.0", + "(C) 1.3", + "(D) -1.9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0229.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0230", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) -2.7", + "(C) 0.3", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0230.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0231", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 2.0", + "(C) -0.1", + "(D) 3.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0231.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0232", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.7", + "(B) 3.3", + "(C) 1.7", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0232.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0233", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 1.6", + "(C) -1.4", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0233.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0234", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.3", + "(B) 0.8", + "(C) 0.4", + "(D) -1.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0234.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0235", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.9", + "(B) 0.9", + "(C) 1.8", + "(D) -1.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0235.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0236", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.0", + "(B) 3.6", + "(C) 6.6", + "(D) 2.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0236.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0237", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) -1.9", + "(C) -0.9", + "(D) 0.1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0237.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0238", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 0.9", + "(C) 0.4", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0238.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0239", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.1", + "(B) 3.5", + "(C) -1.2", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0239.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0240", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 0.5", + "(C) -1.0", + "(D) -1.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0240.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0241", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.4", + "(B) 3.0", + "(C) 5.0", + "(D) 4.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0241.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0242", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 2.6", + "(C) 4.5", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0242.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0243", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 1.4", + "(C) 3.4", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0243.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0244", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 2.3", + "(C) 0.1", + "(D) 3.1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0244.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0245", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 0.6", + "(C) 1.4", + "(D) 0.0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0245.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0246", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 2.4", + "(C) 1.3", + "(D) 4.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0246.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0247", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 2.0", + "(C) 1.3", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0247.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0248", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) 3.6", + "(C) 4.7", + "(D) 0.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0248.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0249", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.8", + "(B) 1.3", + "(C) 2.1", + "(D) 5.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0249.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0250", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.3", + "(B) 1.8", + "(C) 0.7", + "(D) -0.3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0250.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0251", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.2", + "(B) -1.0", + "(C) 2.0", + "(D) 0.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0251.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0252", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 1.2", + "(C) 4.2", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0252.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0253", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.0", + "(B) 0.5", + "(C) -1.5", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0253.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0254", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.2", + "(B) 2.2", + "(C) 3.7", + "(D) 0.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0254.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0255", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 2.5", + "(C) 1.2", + "(D) 4.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0255.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0256", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 0.8", + "(C) -2.2", + "(D) -0.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0256.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0257", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 0.7", + "(C) 0.0", + "(D) 2.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0257.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0258", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.3", + "(B) 0.3", + "(C) 2.8", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0258.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0259", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.6", + "(B) 0.6", + "(C) 0.5", + "(D) 1.9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0259.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0260", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.0", + "(B) 3.7", + "(C) 3.3", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0260.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0261", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.8", + "(B) 3.3", + "(C) 1.3", + "(D) -0.4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0261.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0262", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5.0", + "(B) 2.0", + "(C) 1.3", + "(D) 3.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0262.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0263", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.5", + "(B) 2.5", + "(C) 4.1", + "(D) 4.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0263.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0264", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) -1.1", + "(C) -1.9", + "(D) 0.6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0264.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0265", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 0.6", + "(C) 0.5", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0265.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0266", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.1", + "(B) -2.9", + "(C) 1.3", + "(D) -0.5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0266.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0267", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.9", + "(B) 1.9", + "(C) 2.8", + "(D) -1.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0267.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0268", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.7", + "(B) 2.2", + "(C) 1.7", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0268.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0269", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.5", + "(B) 5.1", + "(C) 2.1", + "(D) 3.6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0269.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0270", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.3", + "(B) 0.1", + "(C) 3.2", + "(D) 3.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0270.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0271", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.8", + "(B) 3.1", + "(C) 0.7", + "(D) 1.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0271.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0272", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.7", + "(B) -2.6", + "(C) 0.4", + "(D) 0.4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0272.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0273", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.2", + "(B) 3.2", + "(C) 3.9", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0273.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0274", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.8", + "(B) 0.1", + "(C) 0.8", + "(D) 1.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0274.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0275", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.5", + "(B) 0.5", + "(C) 3.4", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0275.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0276", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.5", + "(B) 1.7", + "(C) 1.2", + "(D) -0.8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0276.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0277", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.5", + "(B) 3.5", + "(C) 2.5", + "(D) 1.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0277.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0278", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.0", + "(B) 0.8", + "(C) -2.8", + "(D) 0.2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0278.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0279", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.3", + "(B) 1.3", + "(C) 1.2", + "(D) 2.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0279.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0280", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.0", + "(B) 1.9", + "(C) 1.0", + "(D) -0.9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0280.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0281", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4.0", + "(B) 4.3", + "(C) 5.4", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0281.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0282", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.1", + "(B) 0.9", + "(C) -0.8", + "(D) 2.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0282.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0283", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.8", + "(B) 2.3", + "(C) 0.9", + "(D) 2.8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0283.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0284", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.6", + "(B) 0.7", + "(C) 2.5", + "(D) 1.6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0284.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0285", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -0.5", + "(B) -0.4", + "(C) 1.5", + "(D) 2.7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0285.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0286", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.4", + "(B) 3.1", + "(C) 0.4", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0286.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0287", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3.0", + "(B) 0.7", + "(C) 0.0", + "(D) -1.5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0287.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0288", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.4", + "(B) 0.6", + "(C) 2.5", + "(D) -0.6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0288.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0289", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.1", + "(B) 2.8", + "(C) -0.2", + "(D) 4.1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0289.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0290", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.0", + "(B) 3.8", + "(C) 3.0", + "(D) 2.0", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0290.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0291", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -2.2", + "(B) 0.8", + "(C) 0.5", + "(D) 1.5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0291.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0292", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.7", + "(B) 0.9", + "(C) 2.0", + "(D) 0.7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0292.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0293", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2.2", + "(B) 1.3", + "(C) 0.4", + "(D) -0.7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0293.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0294", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.2", + "(B) 0.5", + "(C) -1.5", + "(D) 1.3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0294.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0295", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.0", + "(B) 2.0", + "(C) 4.0", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0295.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0296", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0.7", + "(B) 2.4", + "(C) 0.1", + "(D) 3.7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0296.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0297", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 2.3", + "(C) 3.4", + "(D) 4.1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0297.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0298", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1.1", + "(B) 0.5", + "(C) -2.5", + "(D) 2.4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0298.png" + ] + }, + { + "Question_id": "earthquake magnitude estimation/0299", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, calculate the Richter magnitude (M_L) using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Apply vector synthetic amplitude summation across components, calibrated with Wood-Anderson response simulation in 0.1-10Hz band. Output a float [x] rounded to nearest 0.1 magnitude units with error bounds derived from signal-to-noise ratios.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake magnitude estimation", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1.4", + "(B) 3.1", + "(C) 3.4", + "(D) 0.3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Magnitude/STEAD_Waveform_0299.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_source-receiver_distance_inference.json b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_source-receiver_distance_inference.json new file mode 100644 index 0000000000000000000000000000000000000000..8b8e4522459cc71f02c608988193e46c77854d37 --- /dev/null +++ b/jsons/Lithosphere/earthquake_monitoring_and_prediction/Reasoning/earthquake_source-receiver_distance_inference.json @@ -0,0 +1,6302 @@ +[ + { + "Question_id": "earthquake source-receiver distance inference/0000", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 30", + "(C) 16", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0000.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0001", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 10", + "(B) 28", + "(C) 50", + "(D) -7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0001.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0002", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -4", + "(B) 23", + "(C) 36", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0002.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0003", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 99", + "(B) 106", + "(C) 61", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0003.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0004", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 62", + "(B) 33", + "(C) 69", + "(D) 48", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0004.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0005", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 37", + "(B) 71", + "(C) 48", + "(D) 62", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0005.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0006", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 170", + "(B) 123", + "(C) 117", + "(D) 130", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0006.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0007", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) -38", + "(C) 22", + "(D) -5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0007.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0008", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 57", + "(B) 44", + "(C) 76", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0008.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0009", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 118", + "(B) 137", + "(C) 101", + "(D) 91", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0009.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0010", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 31", + "(C) 58", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0010.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0011", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 31", + "(B) 4", + "(C) 12", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0011.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0012", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 10", + "(B) 33", + "(C) 14", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0012.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0013", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 11", + "(B) -16", + "(C) 21", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0013.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0014", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 39", + "(B) 63", + "(C) 51", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0014.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0015", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 72", + "(B) 33", + "(C) 49", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0015.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0016", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 149", + "(B) 121", + "(C) 140", + "(D) 160", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0016.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0017", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4", + "(B) 18", + "(C) 37", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0017.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0018", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 22", + "(B) 41", + "(C) 14", + "(D) -17", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0018.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0019", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 59", + "(B) 38", + "(C) 77", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0019.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0020", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 65", + "(B) 51", + "(C) 31", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0020.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0021", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 41", + "(B) -4", + "(C) 21", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0021.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0022", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -23", + "(B) 22", + "(C) 17", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0022.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0023", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 29", + "(B) 20", + "(C) 62", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0023.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0024", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1", + "(B) 35", + "(C) 16", + "(D) -1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0024.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0025", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 12", + "(B) -1", + "(C) -5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0025.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0026", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 44", + "(B) 33", + "(C) 27", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0026.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0027", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 14", + "(B) 7", + "(C) -18", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0027.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0028", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -3", + "(B) 24", + "(C) 32", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0028.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0029", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 42", + "(C) 49", + "(D) -6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0029.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0030", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 20", + "(B) -7", + "(C) 0", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0030.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0031", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 75", + "(B) 60", + "(C) 79", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0031.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0032", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 12", + "(B) 30", + "(C) -3", + "(D) -9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0032.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0033", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 41", + "(C) 25", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0033.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0034", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 65", + "(B) 53", + "(C) 67", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0034.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0035", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 32", + "(B) 32", + "(C) 58", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0035.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0036", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 19", + "(B) 10", + "(C) -1", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0036.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0037", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 75", + "(B) 112", + "(C) 61", + "(D) 80", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0037.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0038", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 49", + "(B) 65", + "(C) 70", + "(D) 108", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0038.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0039", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 62", + "(B) 62", + "(C) 81", + "(D) 74", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0039.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0040", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 55", + "(B) 68", + "(C) 62", + "(D) 82", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0040.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0041", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -20", + "(B) 15", + "(C) 29", + "(D) 45", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0041.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0042", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 74", + "(B) 54", + "(C) 68", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0042.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0043", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 85", + "(B) 53", + "(C) 48", + "(D) 34", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0043.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0044", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 0", + "(B) 15", + "(C) -1", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0044.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0045", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 82", + "(B) 119", + "(C) 58", + "(D) 101", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0045.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0046", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 95", + "(B) 81", + "(C) 109", + "(D) 108", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0046.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0047", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 220", + "(B) 163", + "(C) 203", + "(D) 188", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0047.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0048", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 138", + "(B) 152", + "(C) 169", + "(D) 117", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0048.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0049", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 51", + "(B) 30", + "(C) 44", + "(D) 81", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0049.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0050", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 105", + "(B) 86", + "(C) 59", + "(D) 71", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0050.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0051", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 17", + "(B) -9", + "(C) 4", + "(D) -24", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0051.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0052", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -26", + "(B) 7", + "(C) -11", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0052.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0053", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) -7", + "(C) -13", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0053.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0054", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 229", + "(B) 198", + "(C) 184", + "(D) 168", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0054.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0055", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 28", + "(B) 6", + "(C) -16", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0055.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0056", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 32", + "(B) 43", + "(C) 63", + "(D) 19", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0056.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0057", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 10", + "(B) 17", + "(C) -30", + "(D) -8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0057.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0058", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 69", + "(C) 62", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0058.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0059", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 77", + "(B) 69", + "(C) 84", + "(D) 61", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0059.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0060", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2", + "(B) -4", + "(C) 17", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0060.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0061", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 22", + "(B) 61", + "(C) 45", + "(D) 68", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0061.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0062", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 18", + "(B) 3", + "(C) 48", + "(D) -8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0062.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0063", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 20", + "(B) -9", + "(C) 14", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0063.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0064", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 21", + "(B) -23", + "(C) 8", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0064.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0065", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 37", + "(B) 21", + "(C) 54", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0065.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0066", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 149", + "(B) 130", + "(C) 89", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0066.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0067", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 125", + "(B) 130", + "(C) 112", + "(D) 110", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0067.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0068", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 64", + "(B) 37", + "(C) 48", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0068.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0069", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 23", + "(C) 46", + "(D) -5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0069.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0070", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 87", + "(B) 98", + "(C) 104", + "(D) 77", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0070.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0071", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 82", + "(B) 66", + "(C) 40", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0071.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0072", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 10", + "(B) 64", + "(C) 59", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0072.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0073", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 79", + "(B) 86", + "(C) 67", + "(D) 120", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0073.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0074", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) -30", + "(C) 9", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0074.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0075", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 68", + "(B) 98", + "(C) 86", + "(D) 94", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0075.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0076", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 106", + "(B) 146", + "(C) 111", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0076.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0077", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -9", + "(B) 7", + "(C) 25", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0077.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0078", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 133", + "(B) 89", + "(C) 104", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0078.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0079", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 31", + "(B) 47", + "(C) 41", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0079.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0080", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 19", + "(B) 50", + "(C) 57", + "(D) 73", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0080.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0081", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2", + "(B) 44", + "(C) 24", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0081.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0082", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 53", + "(B) 16", + "(C) 8", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0082.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0083", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 40", + "(B) 29", + "(C) 6", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0083.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0084", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 60", + "(B) 76", + "(C) 65", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0084.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0085", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) 11", + "(C) -7", + "(D) -14", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0085.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0086", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 38", + "(B) 11", + "(C) 11", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0086.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0087", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 45", + "(B) 2", + "(C) 7", + "(D) -14", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0087.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0088", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1", + "(B) -16", + "(C) 10", + "(D) -22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0088.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0089", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 90", + "(B) 84", + "(C) 127", + "(D) 72", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0089.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0090", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 18", + "(B) 3", + "(C) 34", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0090.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0091", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 84", + "(B) 53", + "(C) 108", + "(D) 94", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0091.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0092", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 86", + "(B) 71", + "(C) 77", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0092.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0093", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 25", + "(C) 72", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0093.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0094", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 67", + "(B) 50", + "(C) 34", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0094.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0095", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 37", + "(B) 15", + "(C) 21", + "(D) 54", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0095.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0096", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 22", + "(B) 15", + "(C) 1", + "(D) 54", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0096.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0097", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 29", + "(B) 45", + "(C) 0", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0097.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0098", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 20", + "(B) -8", + "(C) 3", + "(D) -14", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0098.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0099", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 95", + "(B) 73", + "(C) 56", + "(D) 64", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0099.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0100", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 78", + "(B) 62", + "(C) 90", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0100.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0101", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 62", + "(B) 111", + "(C) 102", + "(D) 91", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0101.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0102", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 30", + "(B) 40", + "(C) 21", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0102.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0103", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 36", + "(B) 21", + "(C) 48", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0103.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0104", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 31", + "(B) 9", + "(C) 17", + "(D) 32", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0104.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0105", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 44", + "(B) 14", + "(C) 39", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0105.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0106", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 64", + "(B) 69", + "(C) 16", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0106.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0107", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 51", + "(B) 27", + "(C) 38", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0107.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0108", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -3", + "(B) 26", + "(C) 49", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0108.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0109", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 113", + "(B) 157", + "(C) 128", + "(D) 140", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0109.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0110", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -6", + "(B) 11", + "(C) 34", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0110.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0111", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 20", + "(C) -8", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0111.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0112", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 78", + "(B) 42", + "(C) 102", + "(D) 91", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0112.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0113", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 85", + "(B) 60", + "(C) 74", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0113.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0114", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 9", + "(B) 34", + "(C) 45", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0114.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0115", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 273", + "(B) 280", + "(C) 286", + "(D) 295", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0115.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0116", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 116", + "(B) 93", + "(C) 65", + "(D) 104", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0116.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0117", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 182", + "(B) 185", + "(C) 198", + "(D) 212", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0117.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0118", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 5", + "(C) 21", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0118.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0119", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 208", + "(B) 189", + "(C) 174", + "(D) 200", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0119.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0120", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 13", + "(C) 25", + "(D) 32", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0120.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0121", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 2", + "(B) 36", + "(C) 19", + "(D) -13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0121.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0122", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -13", + "(B) 15", + "(C) 24", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0122.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0123", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 106", + "(B) 92", + "(C) 118", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0123.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0124", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 85", + "(B) 109", + "(C) 74", + "(D) 56", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0124.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0125", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 39", + "(B) 14", + "(C) 21", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0125.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0126", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 9", + "(C) 42", + "(D) 68", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0126.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0127", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 54", + "(B) 80", + "(C) 61", + "(D) 82", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0127.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0128", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -24", + "(B) 4", + "(C) 22", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0128.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0129", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 88", + "(B) 110", + "(C) 78", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0129.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0130", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) 4", + "(C) 27", + "(D) -15", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0130.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0131", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) 41", + "(C) 1", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0131.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0132", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 55", + "(C) 13", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0132.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0133", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 141", + "(B) 93", + "(C) 105", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0133.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0134", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 92", + "(B) 66", + "(C) 53", + "(D) 60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0134.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0135", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 9", + "(B) -10", + "(C) 37", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0135.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0136", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -29", + "(B) 27", + "(C) -7", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0136.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0137", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 29", + "(B) 13", + "(C) 43", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0137.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0138", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 48", + "(B) 40", + "(C) 79", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0138.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0139", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -7", + "(B) 46", + "(C) 14", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0139.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0140", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 12", + "(B) 4", + "(C) 22", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0140.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0141", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 21", + "(B) 54", + "(C) 72", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0141.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0142", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 43", + "(B) 27", + "(C) 36", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0142.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0143", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 66", + "(B) 31", + "(C) 25", + "(D) 49", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0143.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0144", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 57", + "(B) 46", + "(C) 77", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0144.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0145", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3", + "(B) 17", + "(C) -17", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0145.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0146", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 23", + "(B) 18", + "(C) 8", + "(D) -10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0146.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0147", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 41", + "(B) 60", + "(C) 9", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0147.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0148", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 20", + "(B) 7", + "(C) 25", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0148.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0149", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 120", + "(B) 90", + "(C) 91", + "(D) 101", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0149.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0150", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -39", + "(B) -9", + "(C) 22", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0150.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0151", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 9", + "(B) 0", + "(C) 22", + "(D) -8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0151.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0152", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 20", + "(B) 9", + "(C) -3", + "(D) -22", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0152.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0153", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 32", + "(B) 19", + "(C) 5", + "(D) -19", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0153.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0154", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -10", + "(B) 11", + "(C) 6", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0154.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0155", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 62", + "(C) 29", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0155.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0156", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 127", + "(B) 110", + "(C) 174", + "(D) 132", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0156.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0157", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 74", + "(B) 88", + "(C) 86", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0157.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0158", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 14", + "(B) -16", + "(C) 1", + "(D) 48", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0158.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0159", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 194", + "(B) 171", + "(C) 174", + "(D) 205", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0159.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0160", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 61", + "(B) 48", + "(C) 69", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0160.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0161", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) 16", + "(C) 34", + "(D) -24", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0161.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0162", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -11", + "(B) 23", + "(C) 6", + "(D) -19", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0162.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0163", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 11", + "(B) -2", + "(C) 4", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0163.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0164", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 95", + "(C) 73", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0164.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0165", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) 22", + "(C) -29", + "(D) -10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0165.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0166", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 29", + "(B) -3", + "(C) -13", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0166.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0167", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4", + "(B) 16", + "(C) 20", + "(D) -13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0167.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0168", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 34", + "(B) 39", + "(C) 50", + "(D) 64", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0168.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0169", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 39", + "(B) 54", + "(C) 77", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0169.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0170", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 81", + "(B) 58", + "(C) 55", + "(D) 74", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0170.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0171", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 90", + "(B) 85", + "(C) 58", + "(D) 75", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0171.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0172", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 14", + "(C) 54", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0172.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0173", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 54", + "(B) 18", + "(C) 45", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0173.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0174", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 22", + "(B) 57", + "(C) 1", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0174.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0175", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 31", + "(B) 66", + "(C) 15", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0175.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0176", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 54", + "(B) 65", + "(C) 83", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0176.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0177", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1", + "(B) 46", + "(C) 30", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0177.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0178", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 56", + "(C) 34", + "(D) 83", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0178.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0179", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) 33", + "(C) 27", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0179.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0180", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 75", + "(B) 48", + "(C) 39", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0180.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0181", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -14", + "(B) 1", + "(C) 9", + "(D) 19", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0181.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0182", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 23", + "(B) 47", + "(C) 9", + "(D) -2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0182.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0183", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 89", + "(B) 98", + "(C) 115", + "(D) 108", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0183.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0184", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 56", + "(B) 75", + "(C) 78", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0184.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0185", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 24", + "(B) 55", + "(C) 39", + "(D) 59", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0185.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0186", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 31", + "(B) 82", + "(C) 64", + "(D) 49", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0186.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0187", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 44", + "(B) 14", + "(C) 34", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0187.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0188", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 39", + "(B) 28", + "(C) 16", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0188.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0189", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 74", + "(B) 33", + "(C) 22", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0189.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0190", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 11", + "(B) -39", + "(C) -17", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0190.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0191", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 34", + "(B) 14", + "(C) 54", + "(D) 52", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0191.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0192", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4", + "(B) 12", + "(C) 24", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0192.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0193", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 74", + "(C) 55", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0193.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0194", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 40", + "(C) 20", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0194.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0195", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -12", + "(B) 4", + "(C) 16", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0195.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0196", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 7", + "(B) 42", + "(C) 56", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0196.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0197", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 43", + "(B) 24", + "(C) 18", + "(D) -1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0197.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0198", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 23", + "(B) -16", + "(C) 41", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0198.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0199", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 14", + "(B) -12", + "(C) 1", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0199.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0200", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 82", + "(C) 61", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0200.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0201", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 18", + "(C) 28", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0201.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0202", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 65", + "(B) 79", + "(C) 33", + "(D) 59", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0202.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0203", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 13", + "(B) 24", + "(C) 6", + "(D) -17", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0203.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0204", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 77", + "(B) 106", + "(C) 86", + "(D) 94", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0204.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0205", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -12", + "(B) 24", + "(C) 5", + "(D) -35", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0205.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0206", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 28", + "(B) 66", + "(C) 66", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0206.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0207", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 54", + "(C) 30", + "(D) 32", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0207.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0208", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 109", + "(B) 76", + "(C) 94", + "(D) 84", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0208.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0209", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4", + "(B) -11", + "(C) 46", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0209.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0210", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 13", + "(B) 31", + "(C) 35", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0210.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0211", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 36", + "(B) 21", + "(C) 2", + "(D) -8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0211.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0212", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 17", + "(B) -7", + "(C) 3", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0212.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0213", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 33", + "(B) 64", + "(C) 6", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0213.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0214", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 83", + "(B) 73", + "(C) 117", + "(D) 94", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0214.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0215", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 28", + "(B) 35", + "(C) 23", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0215.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0216", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 25", + "(B) 13", + "(C) 5", + "(D) -16", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0216.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0217", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 23", + "(C) 29", + "(D) 68", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0217.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0218", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 197", + "(B) 185", + "(C) 229", + "(D) 178", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0218.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0219", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 27", + "(B) 15", + "(C) 44", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0219.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0220", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 52", + "(B) 66", + "(C) 59", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0220.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0221", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -8", + "(B) 1", + "(C) 20", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0221.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0222", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 120", + "(B) 91", + "(C) 101", + "(D) 114", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0222.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0223", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 1", + "(B) -15", + "(C) 50", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0223.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0224", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 121", + "(B) 108", + "(C) 134", + "(D) 138", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0224.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0225", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 50", + "(B) 82", + "(C) 75", + "(D) 66", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0225.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0226", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 47", + "(B) 27", + "(C) -1", + "(D) 41", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0226.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0227", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 54", + "(C) 60", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0227.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0228", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 64", + "(B) 74", + "(C) 44", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0228.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0229", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 12", + "(B) 26", + "(C) 6", + "(D) -5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0229.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0230", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 50", + "(B) 28", + "(C) 42", + "(D) -7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0230.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0231", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 53", + "(C) 0", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0231.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0232", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -1", + "(B) 43", + "(C) 12", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0232.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0233", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 74", + "(B) 93", + "(C) 66", + "(D) 81", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0233.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0234", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 33", + "(B) 47", + "(C) 11", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0234.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0235", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 42", + "(B) 52", + "(C) 36", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0235.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0236", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 79", + "(B) 50", + "(C) 85", + "(D) 104", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0236.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0237", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -4", + "(B) 11", + "(C) 51", + "(D) 19", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0237.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0238", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 51", + "(B) 43", + "(C) 59", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0238.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0239", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 15", + "(C) 43", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0239.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0240", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 21", + "(B) 37", + "(C) 24", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0240.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0241", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 40", + "(B) -14", + "(C) 32", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0241.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0242", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 14", + "(B) -3", + "(C) -14", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0242.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0243", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 111", + "(B) 124", + "(C) 95", + "(D) 81", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0243.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0244", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 197", + "(B) 206", + "(C) 211", + "(D) 167", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0244.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0245", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 76", + "(B) 38", + "(C) 62", + "(D) 46", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0245.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0246", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 32", + "(B) 8", + "(C) 1", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0246.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0247", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 43", + "(B) 72", + "(C) 60", + "(D) 46", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0247.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0248", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 82", + "(B) 62", + "(C) 100", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0248.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0249", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 114", + "(B) 84", + "(C) 107", + "(D) 95", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0249.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0250", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 65", + "(B) 31", + "(C) 46", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0250.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0251", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -13", + "(B) -10", + "(C) 19", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0251.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0252", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 16", + "(B) 6", + "(C) -28", + "(D) 22", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0252.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0253", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 87", + "(B) 103", + "(C) 121", + "(D) 66", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0253.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0254", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 308", + "(B) 280", + "(C) 325", + "(D) 290", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0254.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0255", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 79", + "(B) 50", + "(C) 56", + "(D) 65", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0255.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0256", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -10", + "(B) 33", + "(C) 13", + "(D) 48", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0256.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0257", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 58", + "(B) 35", + "(C) 41", + "(D) -7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0257.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0258", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 133", + "(B) 149", + "(C) 120", + "(D) 157", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0258.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0259", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 37", + "(B) 84", + "(C) 54", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0259.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0260", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 276", + "(B) 258", + "(C) 265", + "(D) 292", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0260.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0261", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 11", + "(B) 3", + "(C) -7", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0261.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0262", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 5", + "(B) 21", + "(C) 8", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0262.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0263", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 96", + "(B) 78", + "(C) 130", + "(D) 111", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0263.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0264", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 3", + "(B) -8", + "(C) 9", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0264.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0265", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 76", + "(B) 58", + "(C) 27", + "(D) 84", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0265.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0266", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 6", + "(B) -7", + "(C) 1", + "(D) -32", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0266.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0267", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 100", + "(B) 35", + "(C) 63", + "(D) 51", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0267.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0268", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 72", + "(B) 54", + "(C) 48", + "(D) 84", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0268.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0269", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 80", + "(B) 105", + "(C) 62", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0269.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0270", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 63", + "(B) 84", + "(C) 42", + "(D) 48", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0270.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0271", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 99", + "(B) 79", + "(C) 84", + "(D) 73", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0271.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0272", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 70", + "(B) 76", + "(C) 49", + "(D) 50", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0272.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0273", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 154", + "(B) 168", + "(C) 142", + "(D) 168", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0273.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0274", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 8", + "(B) 40", + "(C) 24", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0274.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0275", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 109", + "(B) 74", + "(C) 103", + "(D) 88", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0275.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0276", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 14", + "(B) -45", + "(C) 2", + "(D) -14", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0276.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0277", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 32", + "(C) 21", + "(D) 41", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0277.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0278", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 104", + "(B) 123", + "(C) 112", + "(D) 131", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0278.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0279", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 25", + "(B) 10", + "(C) -34", + "(D) -4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0279.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0280", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 19", + "(B) 4", + "(C) -1", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0280.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0281", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) 4", + "(C) 43", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0281.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0282", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 33", + "(B) -1", + "(C) 61", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0282.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0283", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -30", + "(B) -7", + "(C) 14", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0283.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0284", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 76", + "(B) 46", + "(C) 70", + "(D) 53", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0284.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0285", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 26", + "(B) 32", + "(C) -8", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0285.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0286", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 46", + "(B) 73", + "(C) 81", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0286.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0287", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 170", + "(B) 146", + "(C) 184", + "(D) 157", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0287.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0288", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 90", + "(B) 99", + "(C) 81", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0288.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0289", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 33", + "(B) 15", + "(C) 66", + "(D) 51", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0289.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0290", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -12", + "(B) -9", + "(C) 3", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0290.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0291", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 28", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0291.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0292", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 6", + "(B) 26", + "(C) 12", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0292.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0293", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) -5", + "(B) 27", + "(C) -22", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0293.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0294", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 28", + "(B) 44", + "(C) 13", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0294.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0295", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 15", + "(B) 39", + "(C) 27", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0295.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0296", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 35", + "(B) 18", + "(C) -6", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0296.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0297", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 34", + "(B) 52", + "(C) 44", + "(D) 59", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0297.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0298", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 50", + "(B) 88", + "(C) 31", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0298.png" + ] + }, + { + "Question_id": "earthquake source-receiver distance inference/0299", + "Question Type": "Single Choice", + "Text": "As a seismic waveform analyst, inference the epicentral distance (in kilometers) between the seismic receiver and earthquake source using three-component ENZ data (East, North, Vertical; 0-6000 samples at 100Hz sampling rate). Prioritize P-S arrival time differential analysis with polarization validation, assuming standard crustal velocity models. Output must be a single integer [x] representing the closest whole-kilometer estimate.", + "L2-task": "earthquake monitoring and prediction", + "L3-task": "Reasoning", + "L4-task": "earthquake source-receiver distance inference", + "Dataset": "STandard EArthquake Dataset (STEAD)", + "L1-task": "Lithosphere", + "Answer Choices": [ + "(A) 102", + "(B) 131", + "(C) 79", + "(D) 96", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Lithosphere/Geology_Data/STEAD-Image/Distance/STEAD_Waveform_0299.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_detection.json b/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_detection.json new file mode 100644 index 0000000000000000000000000000000000000000..02fd72155222e7d5a7d2277b4e2c94d6fd66f512 --- /dev/null +++ b/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_detection.json @@ -0,0 +1,6253 @@ +[ + { + "Question_id": "Salt Body Detection/0000", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/000a68e46c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0001", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c06147b5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0002", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0092c53387.png" + ] + }, + { + "Question_id": "Salt Body Detection/0003", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00e900afb7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0004", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c153007b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0005", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02e1654bef.png" + ] + }, + { + "Question_id": "Salt Body Detection/0006", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/012c3ed07e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0007", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/010082e36a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0008", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/019766b43c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0009", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/002124aa19.png" + ] + }, + { + "Question_id": "Salt Body Detection/0010", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0203970177.png" + ] + }, + { + "Question_id": "Salt Body Detection/0011", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/233ef1fa32.png" + ] + }, + { + "Question_id": "Salt Body Detection/0012", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/009e9c5f22.png" + ] + }, + { + "Question_id": "Salt Body Detection/0013", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0227a27435.png" + ] + }, + { + "Question_id": "Salt Body Detection/0014", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02504aecbe.png" + ] + }, + { + "Question_id": "Salt Body Detection/0015", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/014cc353bd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0016", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02677351df.png" + ] + }, + { + "Question_id": "Salt Body Detection/0017", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c6536758.png" + ] + }, + { + "Question_id": "Salt Body Detection/0018", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02a73b97e5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0019", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02f62a671c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0020", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02e651b7bd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0021", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03138aebc4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0022", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02a4f7c7de.png" + ] + }, + { + "Question_id": "Salt Body Detection/0023", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/033029547c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0024", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0373bd8d6c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0025", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0123eeda35.png" + ] + }, + { + "Question_id": "Salt Body Detection/0026", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02dd21181c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0027", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04a5bb16d7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0028", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0414cc3198.png" + ] + }, + { + "Question_id": "Salt Body Detection/0029", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/24ab6d3ded.png" + ] + }, + { + "Question_id": "Salt Body Detection/0030", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03ab71b9d7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0031", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/041b1900de.png" + ] + }, + { + "Question_id": "Salt Body Detection/0032", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/031709c0fa.png" + ] + }, + { + "Question_id": "Salt Body Detection/0033", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0416ba85bb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0034", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04710d36cf.png" + ] + }, + { + "Question_id": "Salt Body Detection/0035", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/006d9df08a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0036", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04d3cd2444.png" + ] + }, + { + "Question_id": "Salt Body Detection/0037", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04b029690c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0038", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0432c28b41.png" + ] + }, + { + "Question_id": "Salt Body Detection/0039", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04f48c4646.png" + ] + }, + { + "Question_id": "Salt Body Detection/0040", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03969a67e1.png" + ] + }, + { + "Question_id": "Salt Body Detection/0041", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06decb795c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0042", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/244d2a8082.png" + ] + }, + { + "Question_id": "Salt Body Detection/0043", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/050bf9ca30.png" + ] + }, + { + "Question_id": "Salt Body Detection/0044", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04e5ecfbde.png" + ] + }, + { + "Question_id": "Salt Body Detection/0045", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03422321bb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0046", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/041bda3b04.png" + ] + }, + { + "Question_id": "Salt Body Detection/0047", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04e1d8f7ca.png" + ] + }, + { + "Question_id": "Salt Body Detection/0048", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/032177aab1.png" + ] + }, + { + "Question_id": "Salt Body Detection/0049", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03f991ef8f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0050", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0568930a95.png" + ] + }, + { + "Question_id": "Salt Body Detection/0051", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05572c229f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0052", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00323f1910.png" + ] + }, + { + "Question_id": "Salt Body Detection/0053", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04f7141ff7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0054", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05a54ab210.png" + ] + }, + { + "Question_id": "Salt Body Detection/0055", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05cdc83902.png" + ] + }, + { + "Question_id": "Salt Body Detection/0056", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0614cf0b6c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0057", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06cf6a9e15.png" + ] + }, + { + "Question_id": "Salt Body Detection/0058", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/070ab527b1.png" + ] + }, + { + "Question_id": "Salt Body Detection/0059", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2907c5cca5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0060", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07424fb781.png" + ] + }, + { + "Question_id": "Salt Body Detection/0061", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05e47b3be5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0062", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07b344fbb5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0063", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/08274e82fb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0064", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/062ff07243.png" + ] + }, + { + "Question_id": "Salt Body Detection/0065", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/085ef8448c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0066", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09ce3f15ee.png" + ] + }, + { + "Question_id": "Salt Body Detection/0067", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0823abbc29.png" + ] + }, + { + "Question_id": "Salt Body Detection/0068", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09e83b7ec9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0069", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/050da9c564.png" + ] + }, + { + "Question_id": "Salt Body Detection/0070", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/075c99bcfc.png" + ] + }, + { + "Question_id": "Salt Body Detection/0071", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0962d90501.png" + ] + }, + { + "Question_id": "Salt Body Detection/0072", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b1c21a106.png" + ] + }, + { + "Question_id": "Salt Body Detection/0073", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06ef1122ec.png" + ] + }, + { + "Question_id": "Salt Body Detection/0074", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a1ea2ce4f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0075", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a66231f08.png" + ] + }, + { + "Question_id": "Salt Body Detection/0076", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b45162089.png" + ] + }, + { + "Question_id": "Salt Body Detection/0077", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d091ab909.png" + ] + }, + { + "Question_id": "Salt Body Detection/0078", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0de8ecce67.png" + ] + }, + { + "Question_id": "Salt Body Detection/0079", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ed6516b91.png" + ] + }, + { + "Question_id": "Salt Body Detection/0080", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/101f683ee6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0081", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/11b8214fae.png" + ] + }, + { + "Question_id": "Salt Body Detection/0082", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a5b5df54b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0083", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a13effcb6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0084", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06fe4d8223.png" + ] + }, + { + "Question_id": "Salt Body Detection/0085", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/075c30e2f5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0086", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/095b44b0ce.png" + ] + }, + { + "Question_id": "Salt Body Detection/0087", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a4d368a58.png" + ] + }, + { + "Question_id": "Salt Body Detection/0088", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c43ec36f9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0089", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f04ad5127.png" + ] + }, + { + "Question_id": "Salt Body Detection/0090", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/10442d17d2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0091", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0adb8d3c2c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0092", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09ef36d784.png" + ] + }, + { + "Question_id": "Salt Body Detection/0093", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ab43360f6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0094", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ba253bf47.png" + ] + }, + { + "Question_id": "Salt Body Detection/0095", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d6db8f166.png" + ] + }, + { + "Question_id": "Salt Body Detection/0096", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e2808a025.png" + ] + }, + { + "Question_id": "Salt Body Detection/0097", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b584a37c8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0098", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a9712e8a5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0099", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/074a4a918a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0100", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02658f5ae3.png" + ] + }, + { + "Question_id": "Salt Body Detection/0101", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0475626c02.png" + ] + }, + { + "Question_id": "Salt Body Detection/0102", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06b111b02d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0103", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07adb8811b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0104", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07e0ac7743.png" + ] + }, + { + "Question_id": "Salt Body Detection/0105", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/093f8b1d6e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0106", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0adcdbf194.png" + ] + }, + { + "Question_id": "Salt Body Detection/0107", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c187c0ec0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0108", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d2f16deee.png" + ] + }, + { + "Question_id": "Salt Body Detection/0109", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0dc05f65a2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0110", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0eed90b7de.png" + ] + }, + { + "Question_id": "Salt Body Detection/0111", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f5b2d9561.png" + ] + }, + { + "Question_id": "Salt Body Detection/0112", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1001eb37e5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0113", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/10b41b221b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0114", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/11985f826d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0115", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12e44aaf72.png" + ] + }, + { + "Question_id": "Salt Body Detection/0116", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1471b3bf7e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0117", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15498a92ad.png" + ] + }, + { + "Question_id": "Salt Body Detection/0118", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15a76bc90c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0119", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17815a50e0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0120", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/25cc21facb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0121", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d0a173bfe.png" + ] + }, + { + "Question_id": "Salt Body Detection/0122", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d9250fea0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0123", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c8d55a780.png" + ] + }, + { + "Question_id": "Salt Body Detection/0124", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0db6588bf9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0125", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ec3cfbcc5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0126", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f337683b4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0127", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f776d1a05.png" + ] + }, + { + "Question_id": "Salt Body Detection/0128", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04c31e19f4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0129", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/069c7fbb03.png" + ] + }, + { + "Question_id": "Salt Body Detection/0130", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0702b8700f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0131", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09e2c7bfa3.png" + ] + }, + { + "Question_id": "Salt Body Detection/0132", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a4fd33486.png" + ] + }, + { + "Question_id": "Salt Body Detection/0133", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ccee86f32.png" + ] + }, + { + "Question_id": "Salt Body Detection/0134", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e69714d68.png" + ] + }, + { + "Question_id": "Salt Body Detection/0135", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f1c46ba13.png" + ] + }, + { + "Question_id": "Salt Body Detection/0136", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fdbfa2f0d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0137", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12b6c7311a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0138", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/143238e252.png" + ] + }, + { + "Question_id": "Salt Body Detection/0139", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/164de10f56.png" + ] + }, + { + "Question_id": "Salt Body Detection/0140", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1813a61a7c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0141", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18f73b05ae.png" + ] + }, + { + "Question_id": "Salt Body Detection/0142", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b203471b7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0143", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cc45d2a1f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0144", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e66c09f24.png" + ] + }, + { + "Question_id": "Salt Body Detection/0145", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f68e3a538.png" + ] + }, + { + "Question_id": "Salt Body Detection/0146", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fd17872d4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0147", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2056c97a10.png" + ] + }, + { + "Question_id": "Salt Body Detection/0148", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20c2ec94c6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0149", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/102a73cb82.png" + ] + }, + { + "Question_id": "Salt Body Detection/0150", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/113ff7f87d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0151", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a1b6ae0d5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0152", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c3cdc4486.png" + ] + }, + { + "Question_id": "Salt Body Detection/0153", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/102a7ad32b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0154", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/143196b1e8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0155", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/170a1cb9c7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0156", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1aed9a9daa.png" + ] + }, + { + "Question_id": "Salt Body Detection/0157", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cbb39d623.png" + ] + }, + { + "Question_id": "Salt Body Detection/0158", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c53156b05.png" + ] + }, + { + "Question_id": "Salt Body Detection/0159", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e2266401d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0160", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f074f459b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0161", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1045d28892.png" + ] + }, + { + "Question_id": "Salt Body Detection/0162", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1290e11543.png" + ] + }, + { + "Question_id": "Salt Body Detection/0163", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14b1c33a62.png" + ] + }, + { + "Question_id": "Salt Body Detection/0164", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15c58c3f7c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0165", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/16e0dd1047.png" + ] + }, + { + "Question_id": "Salt Body Detection/0166", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a948a1a2d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0167", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bcab21a24.png" + ] + }, + { + "Question_id": "Salt Body Detection/0168", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d1e3f95d3.png" + ] + }, + { + "Question_id": "Salt Body Detection/0169", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09dbb503a8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0170", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d9e65099f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0171", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fd22e2882.png" + ] + }, + { + "Question_id": "Salt Body Detection/0172", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/151099de84.png" + ] + }, + { + "Question_id": "Salt Body Detection/0173", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18ef5f86ab.png" + ] + }, + { + "Question_id": "Salt Body Detection/0174", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0aada349b6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0175", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bfba17615.png" + ] + }, + { + "Question_id": "Salt Body Detection/0176", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f24885947.png" + ] + }, + { + "Question_id": "Salt Body Detection/0177", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2071f9850b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0178", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/059f99344f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0179", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09020d5904.png" + ] + }, + { + "Question_id": "Salt Body Detection/0180", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ab8828eb5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0181", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c44f43875.png" + ] + }, + { + "Question_id": "Salt Body Detection/0182", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e471a54c7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0183", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/103035b94b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0184", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12a50502da.png" + ] + }, + { + "Question_id": "Salt Body Detection/0185", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14e3d2f19d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0186", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/189f543aa7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0187", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a279da1f9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0188", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cc76fe868.png" + ] + }, + { + "Question_id": "Salt Body Detection/0189", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f75d0bd30.png" + ] + }, + { + "Question_id": "Salt Body Detection/0190", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20676ad11f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0191", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20bde697e6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0192", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/213ac06da3.png" + ] + }, + { + "Question_id": "Salt Body Detection/0193", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/21ba72ed47.png" + ] + }, + { + "Question_id": "Salt Body Detection/0194", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2116631809.png" + ] + }, + { + "Question_id": "Salt Body Detection/0195", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/214bb6c663.png" + ] + }, + { + "Question_id": "Salt Body Detection/0196", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20f0e2dfdd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0197", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ed64d38cd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0198", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/276be2d7ab.png" + ] + }, + { + "Question_id": "Salt Body Detection/0199", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2168a05735.png" + ] + }, + { + "Question_id": "Salt Body Detection/0200", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/203a330c4a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0201", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fe408de00.png" + ] + }, + { + "Question_id": "Salt Body Detection/0202", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b118ea7b7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0203", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d247ee571.png" + ] + }, + { + "Question_id": "Salt Body Detection/0204", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e6f54a44e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0205", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f240d4463.png" + ] + }, + { + "Question_id": "Salt Body Detection/0206", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/101926ea19.png" + ] + }, + { + "Question_id": "Salt Body Detection/0207", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1120f58e5f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0208", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0be8956e00.png" + ] + }, + { + "Question_id": "Salt Body Detection/0209", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0227b5b765.png" + ] + }, + { + "Question_id": "Salt Body Detection/0210", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0feeb1040c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0211", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/103811d8af.png" + ] + }, + { + "Question_id": "Salt Body Detection/0212", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1093e4f138.png" + ] + }, + { + "Question_id": "Salt Body Detection/0213", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/10dc83d62f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0214", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fa2535b77.png" + ] + }, + { + "Question_id": "Salt Body Detection/0215", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/103c96d62c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0216", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1202914cf2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0217", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/13da82c8ae.png" + ] + }, + { + "Question_id": "Salt Body Detection/0218", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/158372da81.png" + ] + }, + { + "Question_id": "Salt Body Detection/0219", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/165ec50967.png" + ] + }, + { + "Question_id": "Salt Body Detection/0220", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/185ff08d47.png" + ] + }, + { + "Question_id": "Salt Body Detection/0221", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/193a5e4c04.png" + ] + }, + { + "Question_id": "Salt Body Detection/0222", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19c8c5aa98.png" + ] + }, + { + "Question_id": "Salt Body Detection/0223", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1aa5baa761.png" + ] + }, + { + "Question_id": "Salt Body Detection/0224", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/13351e9bc6.png" + ] + }, + { + "Question_id": "Salt Body Detection/0225", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/144c958fa8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0226", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15253b48f4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0227", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/155070a394.png" + ] + }, + { + "Question_id": "Salt Body Detection/0228", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15c2b6e55e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0229", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1602c8b05b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0230", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1717b6750a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0231", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/174bd4ed02.png" + ] + }, + { + "Question_id": "Salt Body Detection/0232", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1874b0614a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0233", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1963a9e03a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0234", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15b7f06ba0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0235", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17f3075bd2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0236", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19d2303888.png" + ] + }, + { + "Question_id": "Salt Body Detection/0237", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b44199942.png" + ] + }, + { + "Question_id": "Salt Body Detection/0238", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d2bf3cc94.png" + ] + }, + { + "Question_id": "Salt Body Detection/0239", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ef7e65f42.png" + ] + }, + { + "Question_id": "Salt Body Detection/0240", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fdb251261.png" + ] + }, + { + "Question_id": "Salt Body Detection/0241", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/203c13a28b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0242", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20fcf160f4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0243", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/22a2288e0f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0244", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/22caaba7fa.png" + ] + }, + { + "Question_id": "Salt Body Detection/0245", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fd49d28d8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0246", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/228c4daacd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0247", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20792970f8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0248", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2097e63334.png" + ] + }, + { + "Question_id": "Salt Body Detection/0249", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20bdf88bee.png" + ] + }, + { + "Question_id": "Salt Body Detection/0250", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a407db63b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0251", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1afb27f632.png" + ] + }, + { + "Question_id": "Salt Body Detection/0252", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bca27f98f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0253", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d8164b941.png" + ] + }, + { + "Question_id": "Salt Body Detection/0254", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ebd1031cd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0255", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/133b5ee507.png" + ] + }, + { + "Question_id": "Salt Body Detection/0256", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/154e585cc4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0257", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/16322de21c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0258", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18902bd56d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0259", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19c666a371.png" + ] + }, + { + "Question_id": "Salt Body Detection/0260", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1af68faa92.png" + ] + }, + { + "Question_id": "Salt Body Detection/0261", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c3df8172c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0262", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e933dc6cb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0263", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fdb7fe384.png" + ] + }, + { + "Question_id": "Salt Body Detection/0264", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20b67a6c1d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0265", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f7d2d2769.png" + ] + }, + { + "Question_id": "Salt Body Detection/0266", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e7e6a7b31.png" + ] + }, + { + "Question_id": "Salt Body Detection/0267", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1351d43f41.png" + ] + }, + { + "Question_id": "Salt Body Detection/0268", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1637d12136.png" + ] + }, + { + "Question_id": "Salt Body Detection/0269", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1892c3d197.png" + ] + }, + { + "Question_id": "Salt Body Detection/0270", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a80491edd.png" + ] + }, + { + "Question_id": "Salt Body Detection/0271", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bde429ee9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0272", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cfc959ec2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0273", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ee20d41ce.png" + ] + }, + { + "Question_id": "Salt Body Detection/0274", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f78b0cece.png" + ] + }, + { + "Question_id": "Salt Body Detection/0275", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ffaab4396.png" + ] + }, + { + "Question_id": "Salt Body Detection/0276", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1156737ae5.png" + ] + }, + { + "Question_id": "Salt Body Detection/0277", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17ea34c5d9.png" + ] + }, + { + "Question_id": "Salt Body Detection/0278", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17e8052ff2.png" + ] + }, + { + "Question_id": "Salt Body Detection/0279", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/29a734bae8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0280", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17df5aa486.png" + ] + }, + { + "Question_id": "Salt Body Detection/0281", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19fbc4280d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0282", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20c82f0e9c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0283", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b46f6af5c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0284", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c51a79860.png" + ] + }, + { + "Question_id": "Salt Body Detection/0285", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ddce7211e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0286", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c298a2807.png" + ] + }, + { + "Question_id": "Salt Body Detection/0287", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c4012bff4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0288", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0de9dd9520.png" + ] + }, + { + "Question_id": "Salt Body Detection/0289", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12eb26825d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0290", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14d5d41e14.png" + ] + }, + { + "Question_id": "Salt Body Detection/0291", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15da8f19c8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0292", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1811afb8fb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0293", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a8026456f.png" + ] + }, + { + "Question_id": "Salt Body Detection/0294", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d241376fb.png" + ] + }, + { + "Question_id": "Salt Body Detection/0295", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ee8d337ab.png" + ] + }, + { + "Question_id": "Salt Body Detection/0296", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/201b6ac1e0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0297", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20d0d1f973.png" + ] + }, + { + "Question_id": "Salt Body Detection/0298", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2480b2ea50.png" + ] + }, + { + "Question_id": "Salt Body Detection/0299", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/29e9c79a7e.png" + ] + }, + { + "Question_id": "Salt Body Detection/0300", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a4a5d2b71.png" + ] + }, + { + "Question_id": "Salt Body Detection/0301", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b0d71a390.png" + ] + }, + { + "Question_id": "Salt Body Detection/0302", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c8a7e025d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0303", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2cfa33fde4.png" + ] + }, + { + "Question_id": "Salt Body Detection/0304", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2cc9b18030.png" + ] + }, + { + "Question_id": "Salt Body Detection/0305", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c84e49a39.png" + ] + }, + { + "Question_id": "Salt Body Detection/0306", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c5fd36516.png" + ] + }, + { + "Question_id": "Salt Body Detection/0307", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b157ab430.png" + ] + }, + { + "Question_id": "Salt Body Detection/0308", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a0ae73183.png" + ] + }, + { + "Question_id": "Salt Body Detection/0309", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a5db8e4f7.png" + ] + }, + { + "Question_id": "Salt Body Detection/0310", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2abe2d917b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0311", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b8d74fcb3.png" + ] + }, + { + "Question_id": "Salt Body Detection/0312", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c51e2a97b.png" + ] + }, + { + "Question_id": "Salt Body Detection/0313", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2ca6256249.png" + ] + }, + { + "Question_id": "Salt Body Detection/0314", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c0da8535c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0315", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bd5791def.png" + ] + }, + { + "Question_id": "Salt Body Detection/0316", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2af94f9c4c.png" + ] + }, + { + "Question_id": "Salt Body Detection/0317", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c4b9599df.png" + ] + }, + { + "Question_id": "Salt Body Detection/0318", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2f4cdfb568.png" + ] + }, + { + "Question_id": "Salt Body Detection/0319", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bec33a46d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0320", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b4049f833.png" + ] + }, + { + "Question_id": "Salt Body Detection/0321", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2ebc20ce2a.png" + ] + }, + { + "Question_id": "Salt Body Detection/0322", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2baa4cda28.png" + ] + }, + { + "Question_id": "Salt Body Detection/0323", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bbe5967d8.png" + ] + }, + { + "Question_id": "Salt Body Detection/0324", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a2dd02617.png" + ] + }, + { + "Question_id": "Salt Body Detection/0325", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a48ce5e78.png" + ] + }, + { + "Question_id": "Salt Body Detection/0326", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a7d747db0.png" + ] + }, + { + "Question_id": "Salt Body Detection/0327", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b0e163a9d.png" + ] + }, + { + "Question_id": "Salt Body Detection/0328", + "Question Type": "Single Choice", + "Text": "Please examine this seismic image and determine if there are any saltdomes present. A salt dome is a geological structure where a large mass of salt is pushed up through the surrounding rock layers, creating a dome-shapedstructure. In seismic images, salt domes typically appear as distinct, brightfeatures with clear boundaries due to the strong acoustic impedance contrastbetween salt and surrounding rocks. The image resolution is 101 x 101 pixels.", + "Answer Choices": [ + "(A) True", + "(B) False", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body detection", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b23c2e75a.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_location.json b/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_location.json new file mode 100644 index 0000000000000000000000000000000000000000..6949903f978e8e6fd347ba972881abfed8e6a09e --- /dev/null +++ b/jsons/Lithosphere/geophysics_imaging/Perception/salt_body_location.json @@ -0,0 +1,4230 @@ +[ + { + "Question_id": "Salt Body Segmentation/0000", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome by specifying its bounding box coordinates. A salt dome is a geological structure where a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct,bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The image resolution is 101 x 101 pixels. Please provide the coordinates in the format [x1,y1,x2,y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><85><100><92>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/000a68e46c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0001", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><59><38><69>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c06147b5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0002", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><4><101><80>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0092c53387.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0003", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<75><0><101><52>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00e900afb7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0004", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><11><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c153007b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0005", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><65><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02e1654bef.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0006", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<61><0><100><27>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/012c3ed07e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0007", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><20><101><29>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/010082e36a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0008", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><9><77><31>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/019766b43c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0009", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<22><0><39><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/002124aa19.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0010", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><79><101><94>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0203970177.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0011", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><43><101><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/233ef1fa32.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0012", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><14><101><19>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/009e9c5f22.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0014", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><14><101><82>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02504aecbe.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0015", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<3><0><33><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/102a7ad32b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0016", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><34><15>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/014cc353bd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0017", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><32><35><56>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02677351df.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0018", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><64><60><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00c6536758.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0019", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><30>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02a73b97e5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0020", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><6><101><12>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02f62a671c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0021", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<2><13><101><49>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02e651b7bd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0022", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><56><34>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03138aebc4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0025", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><30><100><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0373bd8d6c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0027", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><23><101><65>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02dd21181c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0028", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<42><0><63><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04a5bb16d7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0029", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<16><76><82><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0414cc3198.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0030", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><85><100><97>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/24ab6d3ded.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0031", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<37><0><101><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03ab71b9d7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0032", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<1><43><92><97>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b8d74fcb3.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0033", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><70><38>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c51e2a97b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0034", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<64><0><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/041b1900de.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0035", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><40><101><50>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/031709c0fa.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0036", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<35><0><96><11>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0416ba85bb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0037", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><41><42><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04710d36cf.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0038", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><12><101><22>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/006d9df08a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0039", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><75><23>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04d3cd2444.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0040", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<47><0><87><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04b029690c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0041", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><98><35>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0432c28b41.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0042", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<7><0><101><57>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04f48c4646.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0043", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<14><95><71><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03969a67e1.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0045", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><34><8>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/244d2a8082.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0046", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><14>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/050bf9ca30.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0047", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><50><101><60>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04e5ecfbde.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0048", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<32><1><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03422321bb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0049", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><62><100><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/041bda3b04.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0050", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><26><101><93>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04e1d8f7ca.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0051", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<16><0><30><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/032177aab1.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0052", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><85><13>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/03f991ef8f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0053", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><33><101><65>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0568930a95.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0054", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><6><48><65>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05572c229f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0055", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<21><0><51><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/00323f1910.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0056", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<22><56><101><80>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/04f7141ff7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0057", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><30>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05a54ab210.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0058", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><61><100><94>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05cdc83902.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0059", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<33><0><68><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0614cf0b6c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0060", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><36>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06cf6a9e15.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0061", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<59><72><87><98>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/070ab527b1.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0062", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><56><101><66>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2907c5cca5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0063", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><17><99><68>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07424fb781.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0064", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><11><101><28>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/05e47b3be5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0065", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<5><46><101><76>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07b344fbb5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0066", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><22><33>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/08274e82fb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0067", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><48><100><56>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/062ff07243.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0068", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<5><0><24><26>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/085ef8448c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0069", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><8><24>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09ce3f15ee.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0070", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><96><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0823abbc29.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0071", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><26><101><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09e83b7ec9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0072", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><83><101><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/050da9c564.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0073", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><21>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/075c99bcfc.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0074", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><55><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0962d90501.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0075", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<40><0><101><41>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b1c21a106.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0076", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><22><12>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06ef1122ec.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0077", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<28><0><58><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a1ea2ce4f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0078", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><6><75><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a66231f08.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0079", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<63><13><96><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b45162089.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0080", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<70><0><100><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d091ab909.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0081", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><85><82>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0de8ecce67.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0082", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<56><79><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ed6516b91.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0083", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><9><101><61>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/101f683ee6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0084", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<70><0><101><72>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/11b8214fae.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0085", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><57><42><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a5b5df54b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0086", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><60><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a13effcb6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0087", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><25><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06fe4d8223.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0088", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><46><93><79>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/075c30e2f5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0089", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><18><73>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/095b44b0ce.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0090", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><16><44>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a4d368a58.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0091", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<20><88><99><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c43ec36f9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0092", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<35><0><71><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f04ad5127.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0094", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<32><0><101><30>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0adb8d3c2c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0095", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><49><101><68>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09ef36d784.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0096", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><59><74>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ab43360f6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0098", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<29><0><101><21>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d6db8f166.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0100", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<29><0><101><48>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b584a37c8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0102", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><62><100><68>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/074a4a918a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0103", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<25><0><45><2>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/02658f5ae3.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0104", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<74><0><101><13>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0475626c02.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0105", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<12><28><26><33>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/06b111b02d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0106", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<84><0><100><83>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07adb8811b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0107", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<65><0><101><26>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/07e0ac7743.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0108", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<88><0><101><22>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/093f8b1d6e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0109", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<89><52><101><64>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0adcdbf194.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0110", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><100><6>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c187c0ec0.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0111", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<17><69><43><84>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d2f16deee.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0112", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<35><0><42><17>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0dc05f65a2.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0113", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><81><52><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0eed90b7de.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0114", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<27><1><50><14>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f5b2d9561.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0115", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<76><1><94><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1001eb37e5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0116", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<50><84><65><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/10b41b221b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0117", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><93><9><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/11985f826d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0118", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><84><100><91>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12e44aaf72.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0119", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><47><28>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1471b3bf7e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0120", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><68><101><75>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15498a92ad.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0121", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<48><3><55><8>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15a76bc90c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0122", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><11><29>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17815a50e0.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0123", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><73><13>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/25cc21facb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0124", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><22>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d0a173bfe.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0125", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><39>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d9250fea0.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0126", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<8><0><100><36>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c8d55a780.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0127", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<20><0><74><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0db6588bf9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0128", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><36><101><66>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ec3cfbcc5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0129", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<18><49><101><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f337683b4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0130", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><29><100><43>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f776d1a05.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0132", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<7><0><77><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/069c7fbb03.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0133", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><42><100><51>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0702b8700f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0134", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<14><0><57><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09e2c7bfa3.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0136", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><61><23><72>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ccee86f32.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0137", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><32><101><40>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e69714d68.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0138", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<37><27><59><45>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f1c46ba13.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0139", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<77><0><93><21>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12b6c7311a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0140", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><57><101><66>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/143238e252.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0141", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<58><0><74><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/164de10f56.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0142", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<5><15><101><80>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1813a61a7c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0143", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<1><0><40><90>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18f73b05ae.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0144", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><19><21>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b203471b7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0145", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<32><44><91><83>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cc45d2a1f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0146", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<36><13><101><55>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e66c09f24.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0147", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<34><0><51><62>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f68e3a538.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0148", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<1><0><15><52>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fd17872d4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0149", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><28><94>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2056c97a10.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0150", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<89><91><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20c2ec94c6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0151", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><15><101><24>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/102a73cb82.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0152", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><22><101><32>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/113ff7f87d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0153", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<7><0><43><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0a1b6ae0d5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0154", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><56><101><63>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c3cdc4486.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0155", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<9><0><40><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/143196b1e8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0156", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<40><0><100><62>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/170a1cb9c7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0158", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<67><72><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cbb39d623.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0159", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><23>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c53156b05.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0160", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<12><48><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e2266401d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0161", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><33><84><93>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0f074f459b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0162", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><17><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1045d28892.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0163", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><9><33>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1290e11543.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0164", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<37><76><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14b1c33a62.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0165", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><39><101><54>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15c58c3f7c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0166", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><74><101><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/16e0dd1047.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0167", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><42><84>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a948a1a2d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0168", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<44><0><83><4>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bcab21a24.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0169", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><41><98>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d1e3f95d3.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0170", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><13><101><18>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09dbb503a8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0171", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><3><101><52>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d9e65099f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0172", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><9><27>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fd22e2882.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0173", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><14><100><25>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/151099de84.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0174", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><76><101><85>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18ef5f86ab.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0175", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><83><101><90>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0aada349b6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0176", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><85><101><94>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bfba17615.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0177", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><15><100><22>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f24885947.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0178", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><14><101><22>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2071f9850b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0179", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><93><101><98>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/059f99344f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0180", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><49><101><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/09020d5904.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0181", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<44><0><101><49>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0ab8828eb5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0182", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><98><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0c44f43875.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0183", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><16><94><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e471a54c7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0184", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<30><0><94><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/103035b94b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0185", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><88><77>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12a50502da.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0186", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><20><101><33>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14e3d2f19d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0187", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><10><101><62>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/189f543aa7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0188", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><23><60>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a279da1f9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0189", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<36><55><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cc76fe868.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0190", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><34><101><42>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f75d0bd30.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0191", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><59><101><70>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20676ad11f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0192", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<74><96><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20bde697e6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0193", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><100><23>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/213ac06da3.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0194", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><33><101><76>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/21ba72ed47.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0195", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<12><30><101><87>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2116631809.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0196", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><60><79><86>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/214bb6c663.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0197", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<45><63><52><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20f0e2dfdd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0198", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<46><0><85><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ed64d38cd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0199", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><63><100><77>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/276be2d7ab.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0201", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><66><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/203a330c4a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0202", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><54><101><75>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fe408de00.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0203", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><3><101><46>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0b118ea7b7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0204", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<66><33><101><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0d247ee571.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0205", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><20><101><81>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0e6f54a44e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0207", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<3><0><97><73>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/101926ea19.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0209", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><6><42><34>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0be8956e00.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0210", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><21><97><79>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0227b5b765.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0211", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><36><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0feeb1040c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0213", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><32><57>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1093e4f138.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0214", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><27><84><85>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/10dc83d62f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0215", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><55><101><61>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fa2535b77.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0217", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><46><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1202914cf2.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0218", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<38><0><84><13>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/13da82c8ae.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0219", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><31><101><45>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/158372da81.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0220", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<1><0><74><63>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/165ec50967.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0221", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<36><10><66><39>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/185ff08d47.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0222", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><20><35>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/193a5e4c04.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0223", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><88><5>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19c8c5aa98.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0224", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<12><0><79><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1aa5baa761.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0225", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><62><51>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/13351e9bc6.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0228", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><29><74><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/155070a394.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0229", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><33><99><67>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15c2b6e55e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0230", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><60><33><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1602c8b05b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0231", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><50><101><97>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1717b6750a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0232", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><84><100><93>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/174bd4ed02.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0233", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><2><26><29>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1874b0614a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0234", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><54><42>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1963a9e03a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0235", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><65>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15b7f06ba0.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0236", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<75><0><99><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17f3075bd2.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0237", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<73><41><101><87>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19d2303888.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0238", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><38><41>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b44199942.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0239", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><62><58>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d2bf3cc94.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0240", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><16><30>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ef7e65f42.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0241", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<8><0><39><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fdb251261.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0242", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><25>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/203c13a28b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0243", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><4><101><44>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20fcf160f4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0244", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<74><0><101><82>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/22a2288e0f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0245", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<12><44><100><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/22caaba7fa.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0246", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><39><101><57>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fd49d28d8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0247", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><23><101><55>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/228c4daacd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0248", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><30><55>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20792970f8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0249", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<40><15><69><63>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2097e63334.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0250", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><57><101><67>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20bdf88bee.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0251", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<58><24><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a407db63b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0253", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<2><69><25><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bca27f98f.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0254", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><35><35><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d8164b941.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0255", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<20><11><84><84>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ebd1031cd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0256", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><41><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/133b5ee507.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0257", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<42><0><100><81>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/154e585cc4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0259", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<9><15><80><52>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/18902bd56d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0260", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><5>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19c666a371.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0261", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<65><0><101><75>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1af68faa92.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0262", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<64><0><101><72>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c3df8172c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0263", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><63><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e933dc6cb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0264", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<49><85><87><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1fdb7fe384.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0265", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><100><73>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20b67a6c1d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0266", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><40>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f7d2d2769.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0267", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<7><0><40><48>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1e7e6a7b31.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0268", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<66><32><86><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1351d43f41.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0269", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><11><101><44>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1637d12136.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0270", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<59><0><65><11>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1892c3d197.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0271", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><64><33><88>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1a80491edd.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0272", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<5><0><101><45>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1bde429ee9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0273", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><15><67>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1cfc959ec2.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0274", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><97><15>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ee20d41ce.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0275", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<2><34><9><40>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1f78b0cece.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0276", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><76><20><96>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1ffaab4396.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0277", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><4><101><37>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1156737ae5.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0278", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><90><51><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17ea34c5d9.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0279", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><1><101><32>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17e8052ff2.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0281", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><9><101><34>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/17df5aa486.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0282", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><9><101><90>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/19fbc4280d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0284", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><30>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1b46f6af5c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0285", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><39><101><53>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c51a79860.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0287", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><65><101><94>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c298a2807.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0288", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><46>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1c4012bff4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0289", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<21><0><56><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0de9dd9520.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0290", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<19><0><48><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/12eb26825d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0291", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><51><101><87>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/14d5d41e14.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0292", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><83><101><96>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/15da8f19c8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0293", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<50><0><95><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1811afb8fb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0295", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><61><101><86>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/1d241376fb.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0298", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<62><0><92><79>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/20d0d1f973.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0299", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><55><101><59>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2480b2ea50.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0300", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><67><24>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/29e9c79a7e.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0301", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><100><33>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a4a5d2b71.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0302", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><7><100><54>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b0d71a390.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0303", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><100><12>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c8a7e025d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0304", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><79><67>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2cfa33fde4.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0305", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><27><101><38>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2cc9b18030.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0306", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><26><42><44>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c84e49a39.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0307", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><69><101><74>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c5fd36516.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0308", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<47><86><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b157ab430.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0309", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><9><101><48>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a0ae73183.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0310", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<61><69><101><100>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a5db8e4f7.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0311", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<72><0><81><21>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2abe2d917b.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0312", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><90><101><96>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2ca6256249.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0313", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<47><0><101><14>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c0da8535c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0314", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<35><63><101><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bd5791def.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0315", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><82><100><92>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2af94f9c4c.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0316", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><94><101><98>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2c4b9599df.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0317", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><6><101><12>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2f4cdfb568.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0318", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<23><25><39><35>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bec33a46d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0319", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><0><101><23>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b4049f833.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0320", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><42><101><51>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2ebc20ce2a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0321", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<19><0><27><15>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2baa4cda28.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0322", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<55><0><101><29>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2bbe5967d8.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0323", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<8><0><24><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a2dd02617.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0324", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<32><0><54><62>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a48ce5e78.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0325", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<67><0><81><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2a7d747db0.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0326", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<0><45><56><99>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b0e163a9d.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0327", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<17><0><31><101>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/2b23c2e75a.png" + ] + }, + { + "Question_id": "Salt Body Segmentation/0328", + "Question Type": "Visual Grounding", + "Text": "Please examine this seismic image and locate the salt dome byspecifying its bounding box coordinates. A salt dome is a geological structurewhere a large mass of salt has pushed up through the surrounding rock layers ,creating a dome-shaped structure. In seismic images, salt domes typically appear as distinct, bright features with clear boundaries due to the strong acoustic impedance contrast between salt and surrounding rocks. The imageresolution is 101 x 101 pixels. Please provide the coordinates in the format [x1, y1, x2, y2], where (x1,y1) is the top-left corner and (x2,y2) is the bottom-right corner of the bounding box.", + "L2-task": "geophysics imaging", + "L3-task": "Perception", + "L4-task": "salt body location", + "Dataset": "Salt-Body-Dataset", + "L1-task": "Lithosphere", + "Ground Truth": "{<18><32><101><51>}", + "Images": [ + "raw/Lithosphere/geophysics_imaging/Salt-Image/0fdbfa2f0d.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Extreme_Events/Perception/ENSO_Identification.json b/jsons/Oceansphere/Extreme_Events/Perception/ENSO_Identification.json new file mode 100644 index 0000000000000000000000000000000000000000..b82df218f542bb803bef73080ea865ff932e12ac --- /dev/null +++ b/jsons/Oceansphere/Extreme_Events/Perception/ENSO_Identification.json @@ -0,0 +1,3214 @@ +[ + { + "Question_id": "ENSO Identification/0000", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1854.png" + ] + }, + { + "Question_id": "ENSO Identification/0001", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1856.png" + ] + }, + { + "Question_id": "ENSO Identification/0002", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1857.png" + ] + }, + { + "Question_id": "ENSO Identification/0003", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1858.png" + ] + }, + { + "Question_id": "ENSO Identification/0004", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1859.png" + ] + }, + { + "Question_id": "ENSO Identification/0005", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1860.png" + ] + }, + { + "Question_id": "ENSO Identification/0006", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1861.png" + ] + }, + { + "Question_id": "ENSO Identification/0007", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1862.png" + ] + }, + { + "Question_id": "ENSO Identification/0008", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1863.png" + ] + }, + { + "Question_id": "ENSO Identification/0009", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1864.png" + ] + }, + { + "Question_id": "ENSO Identification/0010", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1865.png" + ] + }, + { + "Question_id": "ENSO Identification/0011", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1866.png" + ] + }, + { + "Question_id": "ENSO Identification/0012", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1867.png" + ] + }, + { + "Question_id": "ENSO Identification/0013", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1868.png" + ] + }, + { + "Question_id": "ENSO Identification/0014", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1869.png" + ] + }, + { + "Question_id": "ENSO Identification/0015", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1871.png" + ] + }, + { + "Question_id": "ENSO Identification/0016", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1872.png" + ] + }, + { + "Question_id": "ENSO Identification/0017", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1873.png" + ] + }, + { + "Question_id": "ENSO Identification/0018", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1875.png" + ] + }, + { + "Question_id": "ENSO Identification/0019", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1876.png" + ] + }, + { + "Question_id": "ENSO Identification/0020", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1877.png" + ] + }, + { + "Question_id": "ENSO Identification/0021", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1879.png" + ] + }, + { + "Question_id": "ENSO Identification/0022", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1880.png" + ] + }, + { + "Question_id": "ENSO Identification/0023", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1881.png" + ] + }, + { + "Question_id": "ENSO Identification/0024", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1882.png" + ] + }, + { + "Question_id": "ENSO Identification/0025", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1884.png" + ] + }, + { + "Question_id": "ENSO Identification/0026", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1885.png" + ] + }, + { + "Question_id": "ENSO Identification/0027", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1886.png" + ] + }, + { + "Question_id": "ENSO Identification/0028", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1888.png" + ] + }, + { + "Question_id": "ENSO Identification/0029", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1889.png" + ] + }, + { + "Question_id": "ENSO Identification/0030", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1890.png" + ] + }, + { + "Question_id": "ENSO Identification/0031", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1891.png" + ] + }, + { + "Question_id": "ENSO Identification/0032", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1892.png" + ] + }, + { + "Question_id": "ENSO Identification/0033", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1893.png" + ] + }, + { + "Question_id": "ENSO Identification/0034", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1894.png" + ] + }, + { + "Question_id": "ENSO Identification/0035", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1896.png" + ] + }, + { + "Question_id": "ENSO Identification/0036", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1897.png" + ] + }, + { + "Question_id": "ENSO Identification/0037", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1898.png" + ] + }, + { + "Question_id": "ENSO Identification/0038", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1899.png" + ] + }, + { + "Question_id": "ENSO Identification/0039", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1900.png" + ] + }, + { + "Question_id": "ENSO Identification/0040", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1901.png" + ] + }, + { + "Question_id": "ENSO Identification/0041", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1902.png" + ] + }, + { + "Question_id": "ENSO Identification/0042", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1903.png" + ] + }, + { + "Question_id": "ENSO Identification/0043", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1904.png" + ] + }, + { + "Question_id": "ENSO Identification/0044", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1905.png" + ] + }, + { + "Question_id": "ENSO Identification/0045", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1906.png" + ] + }, + { + "Question_id": "ENSO Identification/0046", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1907.png" + ] + }, + { + "Question_id": "ENSO Identification/0047", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1908.png" + ] + }, + { + "Question_id": "ENSO Identification/0048", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1910.png" + ] + }, + { + "Question_id": "ENSO Identification/0049", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1911.png" + ] + }, + { + "Question_id": "ENSO Identification/0050", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1913.png" + ] + }, + { + "Question_id": "ENSO Identification/0051", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1915.png" + ] + }, + { + "Question_id": "ENSO Identification/0052", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1916.png" + ] + }, + { + "Question_id": "ENSO Identification/0053", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1917.png" + ] + }, + { + "Question_id": "ENSO Identification/0054", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1918.png" + ] + }, + { + "Question_id": "ENSO Identification/0055", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1919.png" + ] + }, + { + "Question_id": "ENSO Identification/0056", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1920.png" + ] + }, + { + "Question_id": "ENSO Identification/0057", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1921.png" + ] + }, + { + "Question_id": "ENSO Identification/0058", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1922.png" + ] + }, + { + "Question_id": "ENSO Identification/0059", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1923.png" + ] + }, + { + "Question_id": "ENSO Identification/0060", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1924.png" + ] + }, + { + "Question_id": "ENSO Identification/0061", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1925.png" + ] + }, + { + "Question_id": "ENSO Identification/0062", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1927.png" + ] + }, + { + "Question_id": "ENSO Identification/0063", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1928.png" + ] + }, + { + "Question_id": "ENSO Identification/0064", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1931.png" + ] + }, + { + "Question_id": "ENSO Identification/0065", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1932.png" + ] + }, + { + "Question_id": "ENSO Identification/0066", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1933.png" + ] + }, + { + "Question_id": "ENSO Identification/0067", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1934.png" + ] + }, + { + "Question_id": "ENSO Identification/0068", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1935.png" + ] + }, + { + "Question_id": "ENSO Identification/0069", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1937.png" + ] + }, + { + "Question_id": "ENSO Identification/0070", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1938.png" + ] + }, + { + "Question_id": "ENSO Identification/0071", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1939.png" + ] + }, + { + "Question_id": "ENSO Identification/0072", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1940.png" + ] + }, + { + "Question_id": "ENSO Identification/0073", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1941.png" + ] + }, + { + "Question_id": "ENSO Identification/0074", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1942.png" + ] + }, + { + "Question_id": "ENSO Identification/0075", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1943.png" + ] + }, + { + "Question_id": "ENSO Identification/0076", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1945.png" + ] + }, + { + "Question_id": "ENSO Identification/0077", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1947.png" + ] + }, + { + "Question_id": "ENSO Identification/0078", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1948.png" + ] + }, + { + "Question_id": "ENSO Identification/0079", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1950.png" + ] + }, + { + "Question_id": "ENSO Identification/0080", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1951.png" + ] + }, + { + "Question_id": "ENSO Identification/0081", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1952.png" + ] + }, + { + "Question_id": "ENSO Identification/0082", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1953.png" + ] + }, + { + "Question_id": "ENSO Identification/0083", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1954.png" + ] + }, + { + "Question_id": "ENSO Identification/0084", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1955.png" + ] + }, + { + "Question_id": "ENSO Identification/0085", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1956.png" + ] + }, + { + "Question_id": "ENSO Identification/0086", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1957.png" + ] + }, + { + "Question_id": "ENSO Identification/0087", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1958.png" + ] + }, + { + "Question_id": "ENSO Identification/0088", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1959.png" + ] + }, + { + "Question_id": "ENSO Identification/0089", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1960.png" + ] + }, + { + "Question_id": "ENSO Identification/0090", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1961.png" + ] + }, + { + "Question_id": "ENSO Identification/0091", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1963.png" + ] + }, + { + "Question_id": "ENSO Identification/0092", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1964.png" + ] + }, + { + "Question_id": "ENSO Identification/0093", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1967.png" + ] + }, + { + "Question_id": "ENSO Identification/0094", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1968.png" + ] + }, + { + "Question_id": "ENSO Identification/0095", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1970.png" + ] + }, + { + "Question_id": "ENSO Identification/0096", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1971.png" + ] + }, + { + "Question_id": "ENSO Identification/0097", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1972.png" + ] + }, + { + "Question_id": "ENSO Identification/0098", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1973.png" + ] + }, + { + "Question_id": "ENSO Identification/0099", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1974.png" + ] + }, + { + "Question_id": "ENSO Identification/0100", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1975.png" + ] + }, + { + "Question_id": "ENSO Identification/0101", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1976.png" + ] + }, + { + "Question_id": "ENSO Identification/0102", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1977.png" + ] + }, + { + "Question_id": "ENSO Identification/0103", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1978.png" + ] + }, + { + "Question_id": "ENSO Identification/0104", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1980.png" + ] + }, + { + "Question_id": "ENSO Identification/0105", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1981.png" + ] + }, + { + "Question_id": "ENSO Identification/0106", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1982.png" + ] + }, + { + "Question_id": "ENSO Identification/0107", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1983.png" + ] + }, + { + "Question_id": "ENSO Identification/0108", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1984.png" + ] + }, + { + "Question_id": "ENSO Identification/0109", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1985.png" + ] + }, + { + "Question_id": "ENSO Identification/0110", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1986.png" + ] + }, + { + "Question_id": "ENSO Identification/0111", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1987.png" + ] + }, + { + "Question_id": "ENSO Identification/0112", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1988.png" + ] + }, + { + "Question_id": "ENSO Identification/0113", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1989.png" + ] + }, + { + "Question_id": "ENSO Identification/0114", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1991.png" + ] + }, + { + "Question_id": "ENSO Identification/0115", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1992.png" + ] + }, + { + "Question_id": "ENSO Identification/0116", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1993.png" + ] + }, + { + "Question_id": "ENSO Identification/0117", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1994.png" + ] + }, + { + "Question_id": "ENSO Identification/0118", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1995.png" + ] + }, + { + "Question_id": "ENSO Identification/0119", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1997.png" + ] + }, + { + "Question_id": "ENSO Identification/0120", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/1999.png" + ] + }, + { + "Question_id": "ENSO Identification/0121", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2000.png" + ] + }, + { + "Question_id": "ENSO Identification/0122", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2001.png" + ] + }, + { + "Question_id": "ENSO Identification/0123", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2002.png" + ] + }, + { + "Question_id": "ENSO Identification/0124", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2003.png" + ] + }, + { + "Question_id": "ENSO Identification/0125", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2004.png" + ] + }, + { + "Question_id": "ENSO Identification/0126", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2005.png" + ] + }, + { + "Question_id": "ENSO Identification/0127", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2006.png" + ] + }, + { + "Question_id": "ENSO Identification/0128", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2007.png" + ] + }, + { + "Question_id": "ENSO Identification/0129", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2008.png" + ] + }, + { + "Question_id": "ENSO Identification/0130", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2009.png" + ] + }, + { + "Question_id": "ENSO Identification/0131", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2010.png" + ] + }, + { + "Question_id": "ENSO Identification/0132", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2011.png" + ] + }, + { + "Question_id": "ENSO Identification/0133", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2012.png" + ] + }, + { + "Question_id": "ENSO Identification/0134", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2013.png" + ] + }, + { + "Question_id": "ENSO Identification/0135", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2014.png" + ] + }, + { + "Question_id": "ENSO Identification/0136", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2015.png" + ] + }, + { + "Question_id": "ENSO Identification/0137", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2016.png" + ] + }, + { + "Question_id": "ENSO Identification/0138", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2017.png" + ] + }, + { + "Question_id": "ENSO Identification/0139", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2018.png" + ] + }, + { + "Question_id": "ENSO Identification/0140", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2019.png" + ] + }, + { + "Question_id": "ENSO Identification/0141", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2020.png" + ] + }, + { + "Question_id": "ENSO Identification/0142", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2021.png" + ] + }, + { + "Question_id": "ENSO Identification/0143", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2022.png" + ] + }, + { + "Question_id": "ENSO Identification/0144", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2023.png" + ] + }, + { + "Question_id": "ENSO Identification/0145", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Pacific Ocean sea surface temperature anomalies for DJF (December-January-February) season. Please judge the El Niño-Southern Oscillation (ENSO) event that occurred. If the Niño3.4 index is greater than 0.5 and less than 1.4, it is a weak/moderate El Niño; greater than 1.5 is a strong El Niño; greater than -1.4 and less than -0.5 is a weak/moderate La Niña; less than -1.5 is a strong La Niña.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate El Niño", + "(C) Strong El Niño", + "(D) Weak/Moderate La Niña", + "(E) Strong La Niña", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "ENSO Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/ENSO/sst_ano_fig/2024.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Extreme_Events/Perception/IOD_Identification.json b/jsons/Oceansphere/Extreme_Events/Perception/IOD_Identification.json new file mode 100644 index 0000000000000000000000000000000000000000..f51b806708fcdd491fbcf6273947e41a8fbf9cac --- /dev/null +++ b/jsons/Oceansphere/Extreme_Events/Perception/IOD_Identification.json @@ -0,0 +1,3082 @@ +[ + { + "Question_id": "IOD Identification/0000", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1854.png" + ] + }, + { + "Question_id": "IOD Identification/0001", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1855.png" + ] + }, + { + "Question_id": "IOD Identification/0002", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1856.png" + ] + }, + { + "Question_id": "IOD Identification/0003", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1857.png" + ] + }, + { + "Question_id": "IOD Identification/0004", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1858.png" + ] + }, + { + "Question_id": "IOD Identification/0005", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1859.png" + ] + }, + { + "Question_id": "IOD Identification/0006", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1860.png" + ] + }, + { + "Question_id": "IOD Identification/0007", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1861.png" + ] + }, + { + "Question_id": "IOD Identification/0008", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1862.png" + ] + }, + { + "Question_id": "IOD Identification/0009", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1863.png" + ] + }, + { + "Question_id": "IOD Identification/0010", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1864.png" + ] + }, + { + "Question_id": "IOD Identification/0011", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1865.png" + ] + }, + { + "Question_id": "IOD Identification/0012", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1866.png" + ] + }, + { + "Question_id": "IOD Identification/0013", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1867.png" + ] + }, + { + "Question_id": "IOD Identification/0014", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1868.png" + ] + }, + { + "Question_id": "IOD Identification/0015", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1869.png" + ] + }, + { + "Question_id": "IOD Identification/0016", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1870.png" + ] + }, + { + "Question_id": "IOD Identification/0017", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1872.png" + ] + }, + { + "Question_id": "IOD Identification/0018", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1873.png" + ] + }, + { + "Question_id": "IOD Identification/0019", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1874.png" + ] + }, + { + "Question_id": "IOD Identification/0020", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1875.png" + ] + }, + { + "Question_id": "IOD Identification/0021", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1876.png" + ] + }, + { + "Question_id": "IOD Identification/0022", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1877.png" + ] + }, + { + "Question_id": "IOD Identification/0023", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1878.png" + ] + }, + { + "Question_id": "IOD Identification/0024", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1879.png" + ] + }, + { + "Question_id": "IOD Identification/0025", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1880.png" + ] + }, + { + "Question_id": "IOD Identification/0026", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1881.png" + ] + }, + { + "Question_id": "IOD Identification/0027", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1882.png" + ] + }, + { + "Question_id": "IOD Identification/0028", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1883.png" + ] + }, + { + "Question_id": "IOD Identification/0029", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1886.png" + ] + }, + { + "Question_id": "IOD Identification/0030", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1888.png" + ] + }, + { + "Question_id": "IOD Identification/0031", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1889.png" + ] + }, + { + "Question_id": "IOD Identification/0032", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1890.png" + ] + }, + { + "Question_id": "IOD Identification/0033", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1891.png" + ] + }, + { + "Question_id": "IOD Identification/0034", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1892.png" + ] + }, + { + "Question_id": "IOD Identification/0035", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1893.png" + ] + }, + { + "Question_id": "IOD Identification/0036", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1894.png" + ] + }, + { + "Question_id": "IOD Identification/0037", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1895.png" + ] + }, + { + "Question_id": "IOD Identification/0038", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1896.png" + ] + }, + { + "Question_id": "IOD Identification/0039", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1897.png" + ] + }, + { + "Question_id": "IOD Identification/0040", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1899.png" + ] + }, + { + "Question_id": "IOD Identification/0041", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1900.png" + ] + }, + { + "Question_id": "IOD Identification/0042", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1901.png" + ] + }, + { + "Question_id": "IOD Identification/0043", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1902.png" + ] + }, + { + "Question_id": "IOD Identification/0044", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1903.png" + ] + }, + { + "Question_id": "IOD Identification/0045", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1904.png" + ] + }, + { + "Question_id": "IOD Identification/0046", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1905.png" + ] + }, + { + "Question_id": "IOD Identification/0047", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1906.png" + ] + }, + { + "Question_id": "IOD Identification/0048", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1907.png" + ] + }, + { + "Question_id": "IOD Identification/0049", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1908.png" + ] + }, + { + "Question_id": "IOD Identification/0050", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1910.png" + ] + }, + { + "Question_id": "IOD Identification/0051", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1911.png" + ] + }, + { + "Question_id": "IOD Identification/0052", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1912.png" + ] + }, + { + "Question_id": "IOD Identification/0053", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1913.png" + ] + }, + { + "Question_id": "IOD Identification/0054", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1914.png" + ] + }, + { + "Question_id": "IOD Identification/0055", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1916.png" + ] + }, + { + "Question_id": "IOD Identification/0056", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1917.png" + ] + }, + { + "Question_id": "IOD Identification/0057", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1919.png" + ] + }, + { + "Question_id": "IOD Identification/0058", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1920.png" + ] + }, + { + "Question_id": "IOD Identification/0059", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1921.png" + ] + }, + { + "Question_id": "IOD Identification/0060", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1922.png" + ] + }, + { + "Question_id": "IOD Identification/0061", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1923.png" + ] + }, + { + "Question_id": "IOD Identification/0062", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1927.png" + ] + }, + { + "Question_id": "IOD Identification/0063", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1928.png" + ] + }, + { + "Question_id": "IOD Identification/0064", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1929.png" + ] + }, + { + "Question_id": "IOD Identification/0065", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1930.png" + ] + }, + { + "Question_id": "IOD Identification/0066", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1931.png" + ] + }, + { + "Question_id": "IOD Identification/0067", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1932.png" + ] + }, + { + "Question_id": "IOD Identification/0068", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1933.png" + ] + }, + { + "Question_id": "IOD Identification/0069", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1934.png" + ] + }, + { + "Question_id": "IOD Identification/0070", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1935.png" + ] + }, + { + "Question_id": "IOD Identification/0071", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1936.png" + ] + }, + { + "Question_id": "IOD Identification/0072", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1937.png" + ] + }, + { + "Question_id": "IOD Identification/0073", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1938.png" + ] + }, + { + "Question_id": "IOD Identification/0074", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1939.png" + ] + }, + { + "Question_id": "IOD Identification/0075", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1940.png" + ] + }, + { + "Question_id": "IOD Identification/0076", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1942.png" + ] + }, + { + "Question_id": "IOD Identification/0077", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1943.png" + ] + }, + { + "Question_id": "IOD Identification/0078", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1944.png" + ] + }, + { + "Question_id": "IOD Identification/0079", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1945.png" + ] + }, + { + "Question_id": "IOD Identification/0080", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1946.png" + ] + }, + { + "Question_id": "IOD Identification/0081", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1947.png" + ] + }, + { + "Question_id": "IOD Identification/0082", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1948.png" + ] + }, + { + "Question_id": "IOD Identification/0083", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1950.png" + ] + }, + { + "Question_id": "IOD Identification/0084", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1951.png" + ] + }, + { + "Question_id": "IOD Identification/0085", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1952.png" + ] + }, + { + "Question_id": "IOD Identification/0086", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1953.png" + ] + }, + { + "Question_id": "IOD Identification/0087", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1955.png" + ] + }, + { + "Question_id": "IOD Identification/0088", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1956.png" + ] + }, + { + "Question_id": "IOD Identification/0089", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1957.png" + ] + }, + { + "Question_id": "IOD Identification/0090", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1958.png" + ] + }, + { + "Question_id": "IOD Identification/0091", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1960.png" + ] + }, + { + "Question_id": "IOD Identification/0092", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1961.png" + ] + }, + { + "Question_id": "IOD Identification/0093", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1962.png" + ] + }, + { + "Question_id": "IOD Identification/0094", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1964.png" + ] + }, + { + "Question_id": "IOD Identification/0095", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1966.png" + ] + }, + { + "Question_id": "IOD Identification/0096", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1968.png" + ] + }, + { + "Question_id": "IOD Identification/0097", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1969.png" + ] + }, + { + "Question_id": "IOD Identification/0098", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1970.png" + ] + }, + { + "Question_id": "IOD Identification/0099", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1971.png" + ] + }, + { + "Question_id": "IOD Identification/0100", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1972.png" + ] + }, + { + "Question_id": "IOD Identification/0101", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1973.png" + ] + }, + { + "Question_id": "IOD Identification/0102", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1975.png" + ] + }, + { + "Question_id": "IOD Identification/0103", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1976.png" + ] + }, + { + "Question_id": "IOD Identification/0104", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1977.png" + ] + }, + { + "Question_id": "IOD Identification/0105", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1978.png" + ] + }, + { + "Question_id": "IOD Identification/0106", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1979.png" + ] + }, + { + "Question_id": "IOD Identification/0107", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1980.png" + ] + }, + { + "Question_id": "IOD Identification/0108", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1982.png" + ] + }, + { + "Question_id": "IOD Identification/0109", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1983.png" + ] + }, + { + "Question_id": "IOD Identification/0110", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1984.png" + ] + }, + { + "Question_id": "IOD Identification/0111", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1985.png" + ] + }, + { + "Question_id": "IOD Identification/0112", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1986.png" + ] + }, + { + "Question_id": "IOD Identification/0113", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1990.png" + ] + }, + { + "Question_id": "IOD Identification/0114", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1993.png" + ] + }, + { + "Question_id": "IOD Identification/0115", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1994.png" + ] + }, + { + "Question_id": "IOD Identification/0116", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1997.png" + ] + }, + { + "Question_id": "IOD Identification/0117", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1998.png" + ] + }, + { + "Question_id": "IOD Identification/0118", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/1999.png" + ] + }, + { + "Question_id": "IOD Identification/0119", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2000.png" + ] + }, + { + "Question_id": "IOD Identification/0120", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2002.png" + ] + }, + { + "Question_id": "IOD Identification/0121", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2003.png" + ] + }, + { + "Question_id": "IOD Identification/0122", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2004.png" + ] + }, + { + "Question_id": "IOD Identification/0123", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "D", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2005.png" + ] + }, + { + "Question_id": "IOD Identification/0124", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2006.png" + ] + }, + { + "Question_id": "IOD Identification/0125", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2007.png" + ] + }, + { + "Question_id": "IOD Identification/0126", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2008.png" + ] + }, + { + "Question_id": "IOD Identification/0127", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2009.png" + ] + }, + { + "Question_id": "IOD Identification/0128", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "E", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2010.png" + ] + }, + { + "Question_id": "IOD Identification/0129", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2011.png" + ] + }, + { + "Question_id": "IOD Identification/0130", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2012.png" + ] + }, + { + "Question_id": "IOD Identification/0131", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2013.png" + ] + }, + { + "Question_id": "IOD Identification/0132", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2014.png" + ] + }, + { + "Question_id": "IOD Identification/0133", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2015.png" + ] + }, + { + "Question_id": "IOD Identification/0134", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2017.png" + ] + }, + { + "Question_id": "IOD Identification/0135", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2018.png" + ] + }, + { + "Question_id": "IOD Identification/0136", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2019.png" + ] + }, + { + "Question_id": "IOD Identification/0137", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2020.png" + ] + }, + { + "Question_id": "IOD Identification/0138", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2023.png" + ] + }, + { + "Question_id": "IOD Identification/0139", + "Question Type": "Single Choice", + "Text": "The following figure is a chart of Indian Ocean sea surface temperature anomalies for SON (September-October-November) season. Please judge the Indian Ocean Dipole (IOD) event that occurred. If the Dipole Mode Index (DMI) is greater than 0.4 and less than 0.7, it is a weak/moderate positive event; greater than 0.8 is a strong positive event; greater than -0.7 and less than -0.4 is a weak/moderate negative event; less than -0.8 is a strong negative event.", + "Answer Choices": [ + "(A) Not an obvious event", + "(B) Weak/Moderate positive event", + "(C) Strong positive event", + "(D) Weak/Moderate negative event", + "(E) Strong negative event", + "(F) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Perception", + "L4-task": "IOD Identification", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Identification/IOD/sst_ano_fig/2024.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Extreme_Events/Reasoning/ENSO_Forecast.json b/jsons/Oceansphere/Extreme_Events/Reasoning/ENSO_Forecast.json new file mode 100644 index 0000000000000000000000000000000000000000..f7a9b5ecd0cc5723a81d593df308d4fe39d4c1ab --- /dev/null +++ b/jsons/Oceansphere/Extreme_Events/Reasoning/ENSO_Forecast.json @@ -0,0 +1,3802 @@ +[ + { + "Question_id": "ENSO Forecast/0001", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0002", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0003", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0004", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0005", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0006", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0007", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0008", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0009", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0010", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0011", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0012", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0013", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0014", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0015", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0017", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1870-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0018", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0019", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0021", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0022", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0023", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0025", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0026", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0027", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0028", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0030", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1883-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0031", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1884-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0032", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0034", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0035", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0036", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0037", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0038", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0039", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0040", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0042", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0043", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0044", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1897-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0045", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0046", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0047", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0048", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0049", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0050", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0051", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0052", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0053", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0054", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0055", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1908-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0056", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0057", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0059", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0060", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0061", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1914-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0062", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0063", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0064", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1917-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0065", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0066", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0067", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0068", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0069", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0070", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1923-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0071", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0073", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0074", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0076", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0077", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0078", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0079", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0080", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0081", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0083", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0084", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0085", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0086", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0087", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1940-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0088", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0089", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0091", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0093", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0094", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0095", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1948-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0096", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0097", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0098", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0099", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0100", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1953-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0101", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0102", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0103", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0104", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0105", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1958-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0106", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0107", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0109", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0110", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0111", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1964-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0113", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0114", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0116", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0117", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0118", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0119", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0120", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1973-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0121", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0122", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0123", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0124", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0126", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0127", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1980-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0128", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0129", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0130", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0131", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0132", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0133", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1986-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0134", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1987-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0135", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1988-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0137", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1990-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0138", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1991-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0139", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0140", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0141", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1994-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0143", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0144", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0145", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0146", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0147", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2000-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0148", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0149", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0150", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0151", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0152", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0153", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0154", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0155", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0156", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0157", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0158", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0159", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0160", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0161", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0162", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0163", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0164", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0165", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0166", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0167", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2020-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0168", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0169", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-12.png" + ] + }, + { + "Question_id": "ENSO Forecast/0170", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from JAS (July-August-September) season to DJF (December-January-February) season. Please determine which El Niño-Southern Oscillation (ENSO) event will occur in the DJF (December-January-February) season 12 months later. If the Niño3.4 index is greater than 0.5, it is an El Niño event; if less than -0.5, it is a La Niña event.", + "Answer Choices": [ + "(A) No events", + "(B) El Niño", + "(C) La Niña", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "ENSO Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-09.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-10.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-11.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-12.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Extreme_Events/Reasoning/IOD_Forecast.json b/jsons/Oceansphere/Extreme_Events/Reasoning/IOD_Forecast.json new file mode 100644 index 0000000000000000000000000000000000000000..e6bf577f1ced1ed5c268ddd87943ee286f2b3121 --- /dev/null +++ b/jsons/Oceansphere/Extreme_Events/Reasoning/IOD_Forecast.json @@ -0,0 +1,3627 @@ +[ + { + "Question_id": "IOD Forecast/0001", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1854-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0002", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1855-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0003", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1856-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0004", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1857-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0005", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1858-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0006", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1859-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0007", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1860-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0008", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1861-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0009", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1862-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0010", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1863-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0011", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1864-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0012", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1865-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0013", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1866-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0014", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1867-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0015", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1868-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0016", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1869-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0018", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1871-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0019", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1872-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0020", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1873-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0021", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1874-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0022", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1875-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0023", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1876-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0024", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1877-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0025", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1878-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0026", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1879-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0027", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1880-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0028", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1881-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0029", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1882-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0032", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1885-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0034", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1887-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0035", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1888-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0036", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1889-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0037", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1890-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0038", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1891-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0039", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1892-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0040", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1893-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0041", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1894-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0042", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1895-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0043", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1896-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0045", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1898-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0046", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1899-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0047", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1900-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0048", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1901-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0049", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1902-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0050", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1903-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0051", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1904-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0052", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1905-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0053", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1906-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0054", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1907-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0056", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1909-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0057", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1910-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0058", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1911-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0059", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1912-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0060", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1913-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0062", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1915-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0063", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1916-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0065", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1918-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0066", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1919-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0067", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1920-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0068", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1921-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0069", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1922-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0071", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1924-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0073", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1926-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0074", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1927-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0075", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1928-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0076", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1929-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0077", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1930-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0078", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1931-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0079", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1932-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0080", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1933-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0081", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1934-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0082", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1935-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0083", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1936-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0084", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1937-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0085", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1938-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0086", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1939-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0088", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1941-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0089", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1942-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0090", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1943-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0091", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1944-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0092", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1945-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0093", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1946-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0094", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1947-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0096", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1949-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0097", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1950-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0098", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1951-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0099", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1952-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0101", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1954-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0102", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1955-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0103", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1956-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0104", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1957-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0106", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1959-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0107", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1960-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0108", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1961-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0109", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1962-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0110", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1963-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0112", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1965-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0113", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1966-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0114", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1967-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0115", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1968-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0116", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1969-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0117", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1970-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0118", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1971-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0119", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1972-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0121", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1974-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0122", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1975-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0123", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1976-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0124", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1977-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0125", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1978-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0126", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1979-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0128", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1981-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0129", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1982-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0130", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1983-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0131", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1984-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0132", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1985-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0136", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1989-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0139", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1992-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0140", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1993-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0142", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1995-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0143", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1996-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0144", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1997-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0145", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1998-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0146", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/1999-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0148", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2001-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0149", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2002-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0150", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2003-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0151", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2004-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0152", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2005-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0153", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2006-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0154", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2007-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0155", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2008-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0156", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2009-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0157", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2010-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0158", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2011-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0159", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2012-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0160", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2013-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0161", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2014-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0162", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2015-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0163", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2016-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0164", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2017-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0165", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2018-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0166", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2019-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0168", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "C", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2021-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0169", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2022-09.png" + ] + }, + { + "Question_id": "IOD Forecast/0170", + "Question Type": "Single Choice", + "Text": "Below are six consecutive global sea surface temperature anomaly graphs from AMJ (April-May-June) season to SON (September-October-November) season. Please determine which Indian Ocean Dipole (IOD) event will occur in the SON (September-October-November) season 12 months later. If the Dipole Mode Index (DMI) is greater than 0.4, it is a positive event; if less than -0.4, it is a negative event.", + "Answer Choices": [ + "(A) No events", + "(B) Positive IOD", + "(C) Negative IOD", + "(D) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Extreme Events", + "L3-task": "Reasoning", + "L4-task": "IOD Forecast", + "Dataset": "ERASSTv5", + "Images": [ + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-04.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-05.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-06.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-07.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-08.png", + "raw/Oceansphere/Extreme_Events/ENSO_IOD_Forecast/sst_ano_fig/2023-09.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Marine_Debris_and_Oil_Pollution/Perception/Marine_Pollution_Type_Classification.json b/jsons/Oceansphere/Marine_Debris_and_Oil_Pollution/Perception/Marine_Pollution_Type_Classification.json new file mode 100644 index 0000000000000000000000000000000000000000..83f48baebb95fd07cc5b075c3cccfe953ea1a482 --- /dev/null +++ b/jsons/Oceansphere/Marine_Debris_and_Oil_Pollution/Perception/Marine_Pollution_Type_Classification.json @@ -0,0 +1,2312 @@ +[ + { + "Question_id": "Marine Pollution Type Classification/0000", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_54.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0001", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_53.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0002", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Ship", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0003", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Turbid Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_36.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0004", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0005", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0006", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Foam", + "(D) Dense Sargassum", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_34.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0007", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0008", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_55.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0009", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0010", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Waves & Wakes", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_57.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0011", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0012", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Ship", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0013", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Shallow Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0014", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Turbid Water", + "(B) Waves & Wakes", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_7.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0015", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0016", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0017", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_7.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0018", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_27.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0019", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0020", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Ship", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_100_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0021", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_100_L2R_rgb_13.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0022", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_101_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0023", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Ship", + "(D) Oil Platform", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0024", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Ship", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0025", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_101_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0026", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Ship", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0027", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0028", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0029", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_105_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0030", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0031", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Shallow Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0032", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Shallow Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_106_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0033", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_101_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0034", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0035", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Ship", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_100_L2R_rgb_12.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0036", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_3.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0037", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0038", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0039", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_14.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0040", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_23.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0041", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0042", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Dense Sargassum", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_25.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0043", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_25.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0044", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Dense Sargassum", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_37.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0045", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0046", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0047", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_1_L2R_rgb_38.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0048", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_18.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0049", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_39.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0050", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0051", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Shallow Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_0_L2R_rgb_7.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0052", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0053", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_101_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0054", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0055", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_106_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0056", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Jellyfish", + "(B) Shallow Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_29.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0057", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_100_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0058", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_7.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0059", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_105_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0060", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_106_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0061", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0062", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_24.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0063", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Shallow Water", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0064", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Natural Organie Material", + "(C) Marine water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_106_L2R_rgb_7.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0065", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Natural Organie Material", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_115_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0066", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_24.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0067", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_118_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0068", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_8.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0069", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Sea snot", + "(B) Natural Organic Material", + "(C) Sparse Floating Algae", + "(D) Marine Debris", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0070", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Oil Platform", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0071", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_11_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0072", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_110_L2R_rgb_9.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0073", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_110_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0074", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Sediment-Laden Water", + "(C) Sparse Floating Algae", + "(D) Turbid Water", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0075", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Natural Organic Material", + "(B) Oil Spill", + "(C) Waves&Wakes", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_111_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0076", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_41.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0077", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_111_L2R_rgb_11.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0078", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Shallow Water", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_112_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0079", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Natural Organic Material", + "(D) Oil Platform", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_112_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0080", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_107_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0081", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_32.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0082", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_100_L2R_rgb_11.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0083", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0084", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Shallow Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_119_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0085", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Oil Platform", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_112_L2R_rgb_11.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0086", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0087", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_40.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0088", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Ship", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_105_L2R_rgb_10.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0089", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_112_L2R_rgb_16.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0090", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0091", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_12.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0092", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_11.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0093", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Ship", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_104_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0094", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Waves & Wakes", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_109_L2R_rgb_11.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0095", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0096", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_25.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0097", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Ship", + "(B) Oil Platform", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_111_L2R_rgb_1.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0098", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Oil Spill", + "(C) Dense Sargassum", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_38.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0099", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Water", + "(B) Shallow Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_10_L2R_rgb_2.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0100", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Turbid Water", + "(B) Oil Spill", + "(C) Foam", + "(D) Dense Sargassum", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_41.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0101", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Marine Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_113_L2R_rgb_5.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0102", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Marine Water", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_46.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0103", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Sediment-Laden Wate", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Turbid Water", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_32.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0104", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_57.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0105", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_108_L2R_rgb_4.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0106", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Natural Organic Material", + "(C) Sparse Floating Algae", + "(D) Turbid Water", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_58.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0107", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Natural Organic Material", + "(C) Sparse Floating Algae", + "(D) Turbid Water", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_6.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0108", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Marine Debris", + "(B) Oil Spill", + "(C) Sparse Floating Algae", + "(D) Marine Water", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_52.png" + ] + }, + { + "Question_id": "Marine Pollution Type Classification/0109", + "Question Type": "Multiple Choice", + "Text": "What are the marine pollution types in the entire image?", + "Dataset": "MADOS", + "L1-task": "Oceansphere", + "L2-task": "Marine Debris and Oil Pollution", + "L3-task": "Perception", + "L4-task": "Marine Pollution Type Classification", + "Answer Choices": [ + "(A) Turbid Water", + "(B) Sediment-Laden Water", + "(C) Sparse Floating Algae", + "(D) Sea snot", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Oceansphere/pollution/MADOS/Scene_12_L2R_rgb_38.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Identification.json b/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Identification.json new file mode 100644 index 0000000000000000000000000000000000000000..1fe529cd70e05080912c0169189df53ac6d01414 --- /dev/null +++ b/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Identification.json @@ -0,0 +1,4286 @@ +[ + { + "Question_id": "Eddy Identification/0000", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004020.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0001", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004030.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0002", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004031.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0003", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004050.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0004", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004060.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0005", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004061.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0006", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004062.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0007", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004063.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0008", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004064.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0009", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004070.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0010", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004080.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0011", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004090.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0012", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004091.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0013", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004092.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0014", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004100.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0015", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004101.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0016", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004102.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0017", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004120.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0018", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004121.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0019", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004130.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0020", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004131.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0021", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004140.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0022", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004141.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0023", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004142.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0024", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004150.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0025", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004160.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0026", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004161.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0027", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004162.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0028", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004163.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0029", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004164.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0030", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004165.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0031", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004166.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0032", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004170.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0033", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004171.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0034", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004180.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0035", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004181.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0036", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004200.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0037", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004220.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0038", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004230.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0039", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004231.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0040", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004232.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0041", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004240.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0042", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004250.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0043", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004251.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0044", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004252.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0045", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004270.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0046", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004280.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0047", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004281.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0048", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004290.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0049", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004291.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0050", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004292.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0051", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004293.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0052", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004294.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0053", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004295.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0054", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004300.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0055", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004301.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0056", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004302.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0057", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202004303.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0058", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005020.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0059", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005021.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0060", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005040.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0061", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005041.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0062", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005042.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0063", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005050.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0064", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005051.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0065", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005052.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0066", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005070.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0067", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005071.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0068", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005072.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0069", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005073.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0070", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005074.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0071", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005075.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0072", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005080.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0073", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005081.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0074", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005082.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0075", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005083.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0076", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005084.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0077", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005085.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0078", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005086.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0079", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005110.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0080", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005111.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0081", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005112.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0082", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005113.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0083", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005114.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0084", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005115.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0085", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005120.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0086", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005121.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0087", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005130.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0088", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005131.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0089", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005132.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0090", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005140.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0091", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005141.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0092", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005142.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0093", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005143.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0094", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005144.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0095", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005145.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0096", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005146.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0097", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005150.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0098", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005151.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0099", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005190.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0100", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005210.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0101", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005260.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0102", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005270.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0103", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005271.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0104", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005280.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0105", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005281.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0106", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005290.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0107", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005291.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0108", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005292.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0109", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005300.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0110", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005301.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0111", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005302.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0112", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005310.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0113", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005311.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0114", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005312.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0115", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202005313.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0116", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006010.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0117", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006011.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0118", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006020.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0119", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006030.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0120", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006040.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0121", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006041.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0122", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006070.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0123", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006080.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0124", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006081.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0125", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006082.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0126", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006100.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0127", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006130.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0128", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006170.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0129", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006210.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0130", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006220.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0131", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006221.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0132", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006230.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0133", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006231.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0134", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006250.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0135", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006260.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0136", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202006290.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0137", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007030.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0138", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007080.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0139", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007081.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0140", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007090.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0141", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007091.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0142", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007092.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0143", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007110.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0144", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007150.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0145", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007160.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0146", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007161.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0147", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007170.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0148", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007180.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0149", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007181.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0150", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007200.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0151", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007210.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0152", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007211.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0153", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007220.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0154", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007221.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0155", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007290.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0156", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007310.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0157", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007311.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0158", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202007312.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0159", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008010.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0160", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008011.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0161", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008012.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0162", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008013.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0163", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008060.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0164", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008061.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0165", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008070.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0166", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008080.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0167", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008100.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0168", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008110.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0169", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008120.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0170", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008121.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0171", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008122.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0172", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008130.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0173", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008131.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0174", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008132.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0175", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008133.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0176", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008134.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0177", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008140.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0178", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008150.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0179", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008151.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0180", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008152.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0181", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008160.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0182", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008170.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0183", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008171.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0184", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008172.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0185", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008180.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0186", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008181.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0187", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008190.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0188", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008191.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0189", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008200.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0190", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008210.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0191", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008211.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0192", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008240.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0193", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008241.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0194", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008250.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0195", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008260.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0196", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008261.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0197", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008270.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0198", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008271.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0199", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008272.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0200", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008290.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0201", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008291.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0202", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008292.jpg" + ] + }, + { + "Question_id": "Eddy Identification/0203", + "Question Type": "Single Choice", + "Text": "Given an enhanced chlorophyll grayscale satellite image, determine the type of eddies present. The number of eddies is greater than or equal to 0.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Identification", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Answer Choices": [ + "(A) No eddy", + "(B) Only cyclone eddy", + "(C) Only anticyclone eddy", + "(D) Cyclone eddy and anticyclone eddy", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_identification/identification_image/202008293.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Localization.json b/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Localization.json new file mode 100644 index 0000000000000000000000000000000000000000..99ee09924bcf3cac9b644839264686fbb473cf8d --- /dev/null +++ b/jsons/Oceansphere/Phenomenon_Detection/Perception/Eddy_Localization.json @@ -0,0 +1,2326 @@ +[ + { + "Question_id": "Eddy Localization/0000", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 186 x 205), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<132><1><187><58>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004020.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0001", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 227 x 241), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<27><133><111><204>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004031.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0002", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 140 x 134), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<85><93><113><122>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004050.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0003", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 205 x 226), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<21><109><58><139>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004060.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0004", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 162 x 172), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<106><111><154><142>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004061.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0005", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 216 x 228), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<132><139><185><189>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004062.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0006", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 214 x 236), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<173><144><220><198>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004063.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0007", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 151 x 185), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<9><69><70><125>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004064.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0008", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 87 x 96), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<44><13><62><32>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004070.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0009", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 168 x 170), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<9><112><44><149>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004080.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0010", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 266 x 317), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<229><196><281><242>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004090.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0011", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 187 x 231), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<159><9><210><57>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004091.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0012", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 197 x 226), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<22><138><63><172>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004092.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0013", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 428 x 443), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<33><21><243><201>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004100.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0014", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 219 x 240), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<179><10><226><62>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004102.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0015", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 195 x 199), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><80><112><175>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004121.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0016", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 186 x 219), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<172><8><209><45>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004142.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0017", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 152 x 167), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<120><10><152><39>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004162.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0018", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 216 x 257), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><14><97><89>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004163.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0019", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 263 x 336), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<13><127><166><250>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004165.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0020", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 250 x 317), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<13><72><74><119>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004166.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0021", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 171 x 196), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<12><119><50><148>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004170.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0022", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 300 x 345), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<290><199><327><245>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004180.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0023", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 246 x 275), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<197><13><250><68>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004181.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0024", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 426 x 480), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<32><168><273><379>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004200.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0025", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 196 x 210), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<113><15><191><68>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004220.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0026", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 178 x 191), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<63><14><171><149>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004230.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0027", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 175 x 210), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<12><15><87><86>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004231.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0028", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 161 x 183), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<8><8><35><31>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004232.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0029", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 109 x 132), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<42><53><53><65>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004240.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0030", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 222 x 250), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<182><159><229><205>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004250.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0031", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 228 x 239), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><150><67><202>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004251.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0032", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 294 x 361), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<47><179><117><244>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004252.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0033", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 356 x 395), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<70><101><243><265>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004270.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0034", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 300 x 349), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<32><79><220><265>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004280.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0035", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 156 x 165), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<132><7><157><30>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004290.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0036", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 219 x 263), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<83><20><134><64>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004291.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0037", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 169 x 184), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<60><41><131><114>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004292.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0038", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 319 x 360), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<28><10><140><126>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004293.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0039", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 153 x 185), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<33><19><71><53>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004294.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0040", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 139 x 156), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<122><101><148><129>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004295.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0041", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 233 x 234), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<13><96><130><217>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004300.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0042", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 253 x 290), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<28><36><96><102>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004301.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0043", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 142 x 137), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<7><89><53><134>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004302.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0044", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 182 x 177), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<123><141><157><169>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202004303.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0045", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 257 x 313), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<9><125><141><242>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005020.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0046", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 164 x 213), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<167><121><207><157>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005021.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0047", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 194 x 231), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<10><8><48><44>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005040.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0048", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 193 x 203), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<9><8><78><73>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005041.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0049", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 155 x 147), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<16><14><52><54>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005042.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0050", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 214 x 250), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><43><102><124>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005052.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0051", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 282 x 304), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<27><23><81><77>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005071.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0052", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 192 x 205), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<18><14><84><82>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005072.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0053", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 292 x 278), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><196><94><276>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005073.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0054", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 168 x 190), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<19><87><62><138>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005074.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0055", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 256 x 313), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<16><37><104><110>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005075.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0056", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 203 x 224), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<10><100><81><176>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005080.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0057", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 175 x 183), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<89><102><144><154>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005081.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0058", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 108 x 125), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<84><72><112><95>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005083.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0059", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 176 x 189), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<19><20><100><121>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005085.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0060", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 304 x 311), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<117><83><294><280>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005086.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0061", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 187 x 213), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<11><47><127><167>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005110.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0062", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 179 x 226), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<143><109><210><161>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005112.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0063", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 244 x 283), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><18><90><80>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005113.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0064", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 232 x 251), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<13><166><65><217>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005114.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0065", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 386 x 440), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<219><121><412><367>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005115.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0066", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 291 x 319), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><204><94><271>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005120.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0067", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 165 x 195), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<134><122><173><154>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005121.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0068", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 258 x 239), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<25><39><77><78>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005130.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0069", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 216 x 281), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<37><26><130><124>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005131.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0070", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 288 x 312), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<29><90><154><247>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005132.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0071", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 391 x 418), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<290><46><379><137>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005140.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0072", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 307 x 321), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<226><55><300><130>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005141.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0073", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 230 x 253), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<177><149><243><216>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005142.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0074", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 241 x 273), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<12><159><71><218>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005143.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0075", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 206 x 235), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<144><107><220><190>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005146.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0076", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 308 x 312), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<23><24><104><103>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005151.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0077", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 294 x 309), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<36><28><144><101>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005190.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0078", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 266 x 333), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<228><168><299><242>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005210.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0079", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 141 x 136), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<8><73><59><129>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005260.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0080", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 350 x 406), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<237><162><382><334>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005270.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0081", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 259 x 290), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<19><25><154><136>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005271.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0082", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 268 x 294), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<81><69><208><198>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005280.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0083", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 260 x 307), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<22><21><154><166>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005281.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0084", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 555 x 650), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<72><21><466><379>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005292.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0085", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 490 x 565), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<40><56><388><286>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005300.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0086", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 187 x 209), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<83><66><185><159>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005301.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0087", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 255 x 329), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<38><23><165><159>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005302.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0088", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 386 x 484), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<20><166><256><362>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005310.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0089", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 213 x 247), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<46><45><170><157>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005311.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0090", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 338 x 367), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<164><27><309><156>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005312.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0091", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 318 x 376), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<160><4><342><166>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202005313.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0092", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 282 x 307), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<19><128><167><261>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006011.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0093", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 338 x 391), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<233><33><297><94>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006030.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0094", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 335 x 340), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<154><121><304><298>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006040.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0095", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 281 x 291), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<129><81><268><257>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006041.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0096", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 245 x 290), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<17><17><177><155>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006070.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0097", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 248 x 251), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<19><23><106><113>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006080.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0098", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 335 x 386), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<226><170><356><314>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006081.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0099", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 291 x 355), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<230><171><338><278>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006082.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0100", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 342 x 384), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<184><158><339><320>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006130.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0101", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 186 x 216), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<13><108><67><163>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006170.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0102", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 274 x 308), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<21><136><138><255>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006210.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0103", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 349 x 409), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<30><204><146><316>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006220.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0104", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 338 x 369), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<247><206><342><320>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006221.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0105", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 183 x 213), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<6><65><159><176>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006230.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0106", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 314 x 337), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<25><165><151><280>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006231.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0107", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 649 x 634), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<99><41><436><460>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006250.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0108", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 713 x 796), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<81><53><525><566>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006260.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0109", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 267 x 289), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<21><139><142><249>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202006290.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0110", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 216 x 226), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<73><102><217><206>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007030.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0111", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 252 x 251), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<136><79><245><184>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007080.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0112", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 234 x 275), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<12><6><89><82>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007081.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0113", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 203 x 237), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<116><77><231><192>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007090.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0114", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 224 x 232), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<140><135><224><210>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007091.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0115", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 205 x 226), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<16><17><67><67>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007110.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0116", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 159 x 166), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<79><22><151><95>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007150.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0117", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 502 x 510), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<111><111><369><420>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007180.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0118", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 264 x 287), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<23><12><114><113>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007181.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0119", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 170 x 182), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<126><113><169><156>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007200.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0120", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 273 x 309), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<28><184><99><252>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007210.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0121", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 507 x 522), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<242><19><492><299>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007211.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0122", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 264 x 307), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<31><31><68><72>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007220.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0123", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 223 x 240), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<78><117><126><168>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007221.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0124", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 451 x 496), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<38><32><159><149>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007290.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0125", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 219 x 208), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<7><7><122><110>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007310.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0126", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 169 x 180), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<24><20><47><44>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007311.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0127", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 293 x 271), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<31><19><216><200>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202007312.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0128", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 303 x 314), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<41><22><124><111>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008010.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0129", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 491 x 496), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<38><12><281><330>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008012.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0130", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 153 x 149), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<12><12><51><51>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008013.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0131", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 111 x 137), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<2><6><34><39>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008061.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0132", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 181 x 185), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<23><60><68><105>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008070.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0133", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 321 x 356), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<27><23><171><131>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008100.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0134", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 156 x 199), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<94><10><180><99>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008110.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0135", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 357 x 365), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<221><29><332><98>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008120.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0136", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 205 x 216), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<93><61><137><103>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008121.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0137", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 221 x 242), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<168><162><218><208>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008122.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0138", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 106 x 108), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<9><17><36><43>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008130.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0139", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 210 x 249), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<18><144><62><179>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008132.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0140", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 175 x 182), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<88><88><156><159>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008133.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0141", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 112 x 141), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<4><4><23><26>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008134.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0142", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 129 x 139), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<3><83><53><123>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008140.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0143", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 332 x 376), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<175><178><361><317>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008151.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0144", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 149 x 149), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<10><100><42><135>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008152.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0145", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 209 x 228), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<18><132><53><185>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008160.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0146", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 526 x 581), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<27><313><296><473>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008170.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0147", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 335 x 308), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<8><5><101><91>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008171.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0148", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 188 x 202), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<10><5><55><59>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008172.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0149", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 372 x 397), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<18><10><185><171>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008180.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0150", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 344 x 451), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<196><98><384><303>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008190.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0151", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 206 x 223), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<126><45><177><96>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008191.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0152", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 230 x 263), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<21><148><71><206>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008200.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0153", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 246 x 255), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<24><24><78><79>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008210.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0154", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 319 x 343), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<223><4><333><136>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008211.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0155", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 365 x 430), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<189><85><414><341>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008240.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0156", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 247 x 248), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<191><204><225><235>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008241.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0157", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 325 x 376), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<70><131><192><264>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008250.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0158", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 238 x 271), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<216><183><267><232>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008260.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0159", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 255 x 291), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<38><52><88><95>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008270.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0160", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 338 x 349), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<260><14><324><74>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008271.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0161", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 415 x 493), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<198><88><437><336>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008272.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0162", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 260 x 294), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<217><182><269><243>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008290.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0163", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 268 x 314), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<18><24><205><172>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008291.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0164", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 279 x 299), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<10><151><118><269>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008292.jpg" + ] + }, + { + "Question_id": "Eddy Localization/0165", + "Question Type": "Visual Grounding", + "Text": "Given an enhanced chlorophyll grayscale satellite image (heigtht x width: 143 x 167), identify the location of the eddy and give its bounding box in the format of (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Each image has only one eddy and the type of eddy include cyclone eddy and anticyclone eddy.", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Eddy Localization", + "Dataset": "YOLOv7-Eddy-CHL-GOCI", + "L1-task": "Oceansphere", + "Ground Truth": "{<71><10><111><69>}", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/eddy_localization/localization_image/202008293.jpg" + ] + } +] \ No newline at end of file diff --git a/jsons/Oceansphere/Phenomenon_Detection/Perception/Marine_Fog_Detection.json b/jsons/Oceansphere/Phenomenon_Detection/Perception/Marine_Fog_Detection.json new file mode 100644 index 0000000000000000000000000000000000000000..940523151c869014a0c0a1f3933867adce3bf393 --- /dev/null +++ b/jsons/Oceansphere/Phenomenon_Detection/Perception/Marine_Fog_Detection.json @@ -0,0 +1,3802 @@ +[ + { + "Question_id": "Marine Fog Detection/0000", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210110_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0001", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210110_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0002", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210110_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0003", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210110_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0004", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210110_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0005", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210115_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0006", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210115_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0007", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210115_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0008", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210115_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0009", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210115_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0010", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210121_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0011", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210121_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0012", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210121_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0013", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210121_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0014", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210121_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0015", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210122_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0016", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210122_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0017", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210122_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0018", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210122_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0019", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210122_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0020", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210123_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0021", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210123_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0022", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210123_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0023", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210123_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0024", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210123_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0025", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210124_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0026", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210124_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0027", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210124_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0028", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210124_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0029", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210124_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0030", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210125_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0031", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210125_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0032", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210125_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0033", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210125_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0034", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210125_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0035", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210126_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0036", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210126_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0037", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210126_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0038", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210126_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0039", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210126_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0040", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210127_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0041", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210127_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0042", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210127_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0043", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210127_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0044", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210127_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0045", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210211_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0046", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210211_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0047", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210211_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0048", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210211_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0049", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210211_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0050", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210212_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0051", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210212_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0052", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210212_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0053", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210212_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0054", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210212_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0055", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210213_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0056", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210213_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0057", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210213_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0058", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210213_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0059", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210213_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0060", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210220_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0061", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210220_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0062", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210220_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0063", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210220_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0064", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210220_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0065", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210304_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0066", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210304_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0067", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210304_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0068", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210304_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0069", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210304_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0070", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210305_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0071", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210305_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0072", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210305_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0073", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210305_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0074", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210305_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0075", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210310_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0076", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210310_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0077", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210310_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0078", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210310_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0079", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210310_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0080", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210314_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0081", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210314_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0082", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210314_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0083", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210314_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0084", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210314_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0085", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210325_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0086", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210325_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0087", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210325_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0088", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210325_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0089", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210325_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0090", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210328_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0091", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210328_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0092", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210328_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0093", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210328_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0094", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210328_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0095", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210410_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0096", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210410_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0097", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210410_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0098", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210410_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0099", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210410_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0100", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210420_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0101", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210420_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0102", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210420_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0103", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210420_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0104", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210420_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0105", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210426_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0106", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210426_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0107", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210426_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0108", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210426_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0109", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210426_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0110", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210427_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0111", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210427_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0112", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210427_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0113", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210427_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0114", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210427_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0115", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210428_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0116", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210428_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0117", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210428_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0118", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210428_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0119", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210428_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0120", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210429_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0121", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210429_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0122", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210429_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0123", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210429_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0124", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210429_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0125", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210509_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0126", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210509_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0127", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210509_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0128", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210509_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0129", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210509_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0130", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210510_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0131", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210510_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0132", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210510_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0133", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210510_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0134", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210510_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0135", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210512_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0136", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210512_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0137", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210512_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0138", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210512_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0139", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210512_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0140", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210520_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0141", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210520_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0142", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210520_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0143", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210520_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0144", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210520_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0145", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210530_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0146", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210530_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0147", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210530_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0148", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210530_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0149", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210530_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0150", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210531_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0151", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210531_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0152", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210531_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0153", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210531_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0154", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210531_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0155", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210606_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0156", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210606_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0157", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210606_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0158", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210606_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0159", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210606_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0160", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210613_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0161", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210613_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0162", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210613_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0163", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210613_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0164", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210613_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0165", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210620_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0166", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210620_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0167", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210620_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0168", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210620_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0169", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210620_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0170", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210711_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0171", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210711_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0172", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210711_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0173", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210711_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0174", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210711_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0175", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210712_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0176", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210712_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0177", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210712_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0178", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210712_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0179", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210712_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0180", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210715_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0181", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210715_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0182", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210715_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0183", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210715_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0184", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210715_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0185", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210717_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0186", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210717_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0187", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "A", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210717_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0188", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210717_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0189", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210717_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0190", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210718_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0191", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210718_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0192", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210718_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0193", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210718_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0194", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210718_0800.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0195", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210810_0000.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0196", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210810_0200.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0197", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210810_0400.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0198", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210810_0600.png" + ] + }, + { + "Question_id": "Marine Fog Detection/0199", + "Question Type": "Single Choice", + "Text": "The following image is an RGB image derived using the visible bands of satellite data. Please determine whether there is marine fog in the area shown in the image.", + "Answer Choices": [ + "(A) Yes, there is marine fog", + "(B) No, there is no marine fog", + "(C) Unable to decide" + ], + "Ground Truth": "B", + "L1-task": "Oceansphere", + "L2-task": "Phenomenon Detection", + "L3-task": "Perception", + "L4-task": "Marine Fog Detection", + "Dataset": "M4Fog", + "Images": [ + "raw/Oceansphere/Phenomenon_Detection/Marine_Fog_Detection/fog_images/20210810_0800.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Land_Use/Perception/Fine-grained_land_type_classification.json b/jsons/Pedosphere/Land_Use/Perception/Fine-grained_land_type_classification.json new file mode 100644 index 0000000000000000000000000000000000000000..4b09818409cfb5e5da829d2348912e6a423eac57 --- /dev/null +++ b/jsons/Pedosphere/Land_Use/Perception/Fine-grained_land_type_classification.json @@ -0,0 +1,10691 @@ +[ + { + "Question_id": "Fine-grained land type classification/0000", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><259><117><312>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0001", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<107><198><182><273>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0087.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0002", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><259><117><312>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0003", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><259><117><312>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Sparse woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0004", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<437><394><512><484>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0033.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0005", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<367><23><442><93>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0045.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0006", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<403><61><495><166>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0059.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0007", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<2><129><100><232>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0008", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<162><0><275><40>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0067.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0009", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<493><179><512><243>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0022.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0010", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><371><77><453>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0011", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<140><0><210><40>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0087.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0012", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<85><391><196><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0114.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0013", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<193><400><242><449>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0073.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0014", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<329><454><400><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0022.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0015", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<285><266><340><325>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0016", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<235><48><512><505>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Ocean", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0017", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<119><31><274><146>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0018", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<12><10><193><210>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0033.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0019", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<184><0><253><38>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0020", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<298><199><335><259>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0077.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0021", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<286><3><512><395>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0081.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0022", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<102><176><247><216>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0052.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0023", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<383><276><438><340>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Farm", + "(B) Grassland", + "(C) Lake", + "(D) Pond", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0065.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0024", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><116><119>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0087.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0025", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<194><0><273><49>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0097.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0026", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<396><188><502><295>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0072.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0027", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<339><472><392><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Urban built-up", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0045.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0028", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<433><184><509><291>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0093.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0029", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<227><465><354><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0030", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><418><32><510>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0031", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<123><2><367><212>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0042.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0032", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<290><97><360><160>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0033", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<441><296><493><343>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0034.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0034", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<74><276><107><448>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0035", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<261><116><360><221>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0131.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0036", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<141><96><200><167>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0052.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0037", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><14><90><89>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0117.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0038", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<101><128><171><186>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0027.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0039", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<181><0><248><19>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0040", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<458><371><512><446>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0041", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<4><0><512><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0107.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0042", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<63><148><131><211>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0043", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<218><75><270><132>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Grassland", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0011.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0044", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><148><241>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0045", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<142><37><263><102>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0133.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0046", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<238><304><294><355>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement ", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0047", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<116><170><242><253>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0026.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0048", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<292><253><398><392>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0029.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0049", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><147><137><286>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0050", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<153><377><197><437>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0051", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<244><443><290><468>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0052", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<260><0><347><51>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0073.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0053", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<365><51><502><179>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0054", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<278><192><501><385>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0055", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<288><325><368><445>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0078.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0056", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><235><16><266>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0057", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><81><104><285>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Marshland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0100.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0058", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<16><289><149><383>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0132.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0059", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<337><253><381><293>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0032.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0060", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<237><262><291><319>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0093.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0061", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><237><82><304>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0046.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0062", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<279><343><314><379>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0116.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0063", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<327><38><370><108>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Shoal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0064", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<41><162><68><197>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Reservoir pond", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0065", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<37><0><160><85>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0066", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<412><386><448><411>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Shrubbery", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0067", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><132><20><207>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0042.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0068", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<420><0><511><76>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) High-covered grassland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0069", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<324><479><387><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Low-covered grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0070", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<270><85><373><165>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) High-covered grassland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0042.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0071", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><354><31><403>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0072", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><221><63><325>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0033.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0073", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<6><384><133><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0098.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0074", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<286><187><360><293>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0107.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0075", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<327><131><401><189>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0037.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0076", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<366><376><438><423>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0077", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<334><391><482><511>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Low-covered grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0078", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<441><326><472><364>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0078.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0079", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<172><60><198><114>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Bare land", + "(C) Lake", + "(D) Low-covered grassland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0010.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0080", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<174><407><224><446>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Reservoir pond", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0078.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0081", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<460><436><508><470>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0097.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0082", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<22><354><61><406>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0083", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<260><195><299><240>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0054.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0084", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<18><271><63><315>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0038.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0085", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<54><238><183><287>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0047.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0086", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<450><138><511><224>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0087", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<230><90><280><148>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0076.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0088", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<139><34><235><128>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Reservoir pond", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0074.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0089", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<28><145><153><289>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0072.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0090", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<149><421><239><500>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0091", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><487><79><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0092", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><0><512><401>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0094.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0093", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<277><271><412><456>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0094", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<38><329><120><390>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0069.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0095", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<121><0><200><203>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0107.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0096", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<25><263><185><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0065.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0097", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<138><38><218><243>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0057.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0098", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<212><0><344><86>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0062.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0099", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<184><312><228><371>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0069.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0100", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><294><64><402>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0139.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0101", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<14><212><64><243>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0108.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0102", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<45><332><135><454>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0103", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<131><0><311><50>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Marshland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0104", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<144><139><212><284>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0061.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0105", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><142><16><174>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0090.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0106", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><36><264><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0046.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0107", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<210><209><270><306>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0108", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<252><343><356><457>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0109", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<172><157><228><224>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0086.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0110", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<383><136><493><266>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0100.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0111", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<323><156><383><208>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0112", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<116><277><284><408>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0113", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<347><371><428><447>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0105.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0114", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<226><272><302><334>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0115", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<321><308><374><346>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Rual settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0090.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0116", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<120><123><249><219>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0103.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0117", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<226><198><288><238>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0054.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0118", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<269><282><368><361>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0119", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<281><250><412><366>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0106.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0120", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<257><290><301><361>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land ", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0040.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0121", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<463><209><483><223>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0126.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0122", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<448><174><512><340>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0123", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<349><161><422><248>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0056.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0124", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<298><152><336><195>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0077.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0125", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<168><7><249><140>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0126", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<150><54><271><136>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0048.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0127", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<311><153><367><188>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0128", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><41><138><135>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0013.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0129", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<82><461><111><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0130", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<167><470><226><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Paddy field", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0131", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<65><270><133><383>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0116.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0132", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<146><0><314><46>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0067.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0133", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<275><121><348><199>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0101.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0134", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><449><61><492>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0034.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0135", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><438><30><479>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0024.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0136", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<267><493><339><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0072.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0137", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><15><52>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0138", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><92><20><143>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Urban built-up", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0090.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0139", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<291><261><328><301>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0010.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0140", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<168><162><228><234>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0033.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0141", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<407><239><512><343>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0142", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<17><384><77><496>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0102.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0143", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<69><448><188><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0041.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0144", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<295><54><372><118>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other construction land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0040.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0145", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><272><62><380>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0146", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<3><184><512><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0022.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0147", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<230><38><264><76>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other forest land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0108.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0148", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<440><372><512><481>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0014.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0149", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<477><355><512><493>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0150", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<291><385><348><472>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0076.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0151", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<35><55><305><400>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0049.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0152", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<191><397><275><467>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0153", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<201><14><259><97>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0154", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<338><132><446><246>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0045.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0155", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<101><205><172><234>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0064.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0156", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><198><204><298>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0088.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0157", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<326><425><367><487>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0102.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0158", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<153><285><186><340>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0069.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0159", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<15><51><64><87>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0160", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<151><279><207><349>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0016.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0161", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<170><23><208><76>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0063.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0162", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<211><442><343><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0056.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0163", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<118><22><159><66>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0164", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<115><354><197><436>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0004.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0165", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<344><458><397><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0135.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0166", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<324><416><383><457>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0167", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<369><192><403><226>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0121.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0168", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<367><34><389><42>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0169", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<115><312><146><338>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0009.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0170", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<222><298><234><311>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0171", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<377><288><409><315>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0172", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<411><127><445><152>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0020.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0173", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<94><116><128><166>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0058.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0174", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><228><114><397>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0175", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<301><425><389><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0176", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><25><58><85>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other construction land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0036.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0177", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><264><26><406>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0178", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<134><217><167><267>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Urban built-up", + "(B) Grassland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0179", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<279><479><369><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0039.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0180", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<64><150><136><216>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0089.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0181", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<146><53><182><84>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other construction land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0040.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0182", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<389><6><487><83>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0054.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0183", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<332><0><449><86>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0038.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0184", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><425><31><511>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0038.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0185", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<315><61><341><83>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0128.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0186", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<361><2><463><164>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0124.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0187", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<374><53><512><262>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0188", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<361><60><413><144>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0061.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0189", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<129><171><166><223>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0036.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0190", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<110><156><187><241>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0081.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0191", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<59><170><271><464>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Medium-covered grasslang", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0088.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0192", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<140><191><201><263>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0193", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<166><443><331><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0112.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0194", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<130><46><180><114>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0080.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0195", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<438><46><512><135>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0020.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0196", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<187><300><243><363>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0047.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0197", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<25><424><53><452>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0063.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0198", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<136><135><237><313>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0199", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<274><0><387><159>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0200", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<310><306><416><383>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0201", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<356><98><405><160>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0080.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0202", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<378><5><413><74>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0203", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<326><100><430><153>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0204", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<376><214><446><289>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0128.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0205", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<109><192><167><213>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0054.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0206", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<486><379><512><401>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0207", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<90><59><158><121>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Marshland", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0112.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0208", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><182><76><231>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0026.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0209", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<316><286><421><339>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0086.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0210", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<280><194><383><323>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0211", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<405><38><456><97>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0112.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0212", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<145><353><202><411>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0098.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0213", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><48><65><96>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0027.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0214", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<273><192><339><257>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0086.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0215", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<156><402><263><472>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0049.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0216", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<267><214><316><248>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0007.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0217", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<53><323><101><378>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0132.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0218", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<38><198><81><241>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0103.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0219", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<319><384><356><414>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Sparse woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0037.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0220", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<328><219><384><288>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Reservoir pond", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0024.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0221", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<294><251><342><308>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0020.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0222", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<48><164><134><251>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Bare rock", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0054.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0223", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<346><354><418><410>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0224", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<142><483><181><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0015.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0225", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><59><32><166>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0226", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<195><69><235><120>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other construction land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0108.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0227", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<407><501><431><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0053.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0228", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<22><474><49><499>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0059.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0229", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<326><321><351><336>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0230", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<203><6><223><18>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0061.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0231", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<208><164><237><191>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0103.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0232", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<56><0><392><397>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0133.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0233", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<225><168><512><314>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0234", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<151><129><182><159>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0041.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0235", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<320><469><390><507>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0236", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><101><173><229>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0237", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<276><186><305><292>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0238", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<276><270><344><342>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0239", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><464><41><510>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0065.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0240", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<269><337><340><378>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0241", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<257><231><320><268>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0037.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0242", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<227><123><302><220>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0046.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0243", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><285><70><434>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0244", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<285><190><314><224>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0105.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0245", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<460><406><507><442>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0246", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<172><285><224><331>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0073.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0247", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<294><340><345><369>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0102.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0248", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<134><10><216><77>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0249", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<403><29><447><77>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0250", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<143><179><213><221>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0251", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<393><261><412><311>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0101.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0252", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<413><440><454><494>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0253", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<72><289><107><330>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0254", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<49><21><109><62>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0072.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0255", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<72><372><96><402>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0256", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<2><5><79><86>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0135.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0257", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<165><149><215><231>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0125.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0258", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<63><412><171><441>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0108.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0259", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<7><2><111><98>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0260", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><234><60><287>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0023.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0261", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<265><187><329><241>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0262", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<152><446><198><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0010.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0263", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<78><183><163><220>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0020.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0264", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><71><11><126>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0067.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0265", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<74><0><126><143>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0266", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><58><47>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0080.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0267", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><44><49>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Gobi", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0105.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0268", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<189><311><216><339>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0048.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0269", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<84><237><128><287>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0115.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0270", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<425><263><452><291>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0271", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<160><407><208><448>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0081.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0272", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<5><476><43><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0128.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0273", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<3><233><46><298>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0274", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><0><50><38>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0275", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<3><467><38><511>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0026.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0276", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><205><30><245>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0032.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0277", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><349><41><426>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0010.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0278", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<38><119><64><138>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0104.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0279", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<434><0><489><38>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0061.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0280", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<94><389><122><417>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0110.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0281", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><0><54><63>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0282", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<386><291><444><367>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0053.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0283", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<339><448><394><488>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Other", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0284", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<426><323><463><379>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0051.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0285", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<120><21><147><57>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Urban built-up", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0121.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0286", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><299><31><349>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) rural settlement", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0287", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><463><31><483>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0083.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0288", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<370><464><408><501>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) rural settlement", + "(C) Lake", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0064.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0289", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<352><389><384><414>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) rural settlement", + "(C) Lake", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0104.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0290", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<280><41><318><58>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0129.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0291", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<336><2><512><242>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0039.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0292", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<17><193><58><228>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0293", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<225><166><266><217>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Urban and rural", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0120.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0294", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution of satellite image is 600 x 600. Bounding box: -[<396><113><399><118>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0135.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0295", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<54><244><72><279>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0130.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0296", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<156><346><191><382>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0028.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0297", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<54><367><91><411>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0298", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution ofsatellite image is 600 x 600. Bounding box: -[<257><432><302><475>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0090.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0299", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<76><352><171><438>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Bare land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0014.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0300", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<122><351><158><383>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0063.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0301", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<91><187><143><218>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0073.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0302", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-left corner is (x_min, y_min) and the bottom-right corner is (x_max,y_max). The resolution of satellite image is 600 x 600. Bounding box: -[<118><0><195><106>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0052.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0303", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<199><394><239><441>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0117.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0304", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<89><377><117><428>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0050.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0305", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<52><30><63><48>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0061.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0306", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<93><0><119><18>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0038.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0307", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><255><69>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Urban built-up", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0120.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0308", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<133><212><222><249>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0309", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<102><196><202><257>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0091.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0310", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<214><6><231><25>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0103.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0311", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<352><220><387><252>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0003.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0312", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<382><0><394><14>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0034.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0313", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<77><8><92><39>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0132.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0314", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><168><30><219>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0315", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<50><0><92><12>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0036.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0316", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<332><370><349><387>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0317", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<438><252><473><273>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0318", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<275><425><311><446>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0049.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0319", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<212><305><249><329>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0120.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0320", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<112><313><165><348>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0050.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0321", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<319><453><342><481>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0085.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0322", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<384><337><419><367>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0051.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0323", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<61><235><72><265>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0324", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<312><33><407><89>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0077.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0325", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<54><19><92><48>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0326", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<300><393><360><453>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0080.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0327", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<183><31><218><78>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0328", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<316><162><334><188>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0120.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0329", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<95><158><166><211>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0330", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<371><73><468><131>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0077.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0331", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<456><377><488><413>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0101.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0332", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<438><465><486><509>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0064.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0333", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<156><433><182><469>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0334", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<487><405><512><431>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0008.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0335", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<30><333><106><371>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0109.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0336", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<73><374><93><393>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0121.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0337", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<414><376><484><419>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0084.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0338", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<241><293><332><334>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0115.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0339", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<460><275><506><322>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0340", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<34><11><84><43>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Paddy field", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0341", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<48><114><77><161>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0137.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0342", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<140><271><211><326>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0343", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<274><356><322><394>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0008.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0344", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<264><302><346><367>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0003.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0345", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<114><55><238><119>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0125.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0346", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<45><220><123><256>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0139.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0347", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<109><459><190><510>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0003.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0348", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<476><209><499><249>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0018.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0349", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<310><5><334><43>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0104.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0350", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<360><36><390><74>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0351", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<73><479><90><488>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0007.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0352", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<361><71><387><105>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0125.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0353", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<12><429><46><457>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0005.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0354", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<338><175><459><310>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0117.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0355", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<375><466><393><487>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0018.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0356", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<11><486><36><507>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0006.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0357", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<412><32><466><147>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0078.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0358", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<23><54><109><158>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0011.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0359", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<110><0><146><44>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0139.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0360", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<83><0><213><29>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0361", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<363><2><512><107>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Sand", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0074.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0362", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><110><173>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0363", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><35><69><114>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0058.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0364", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<157><70><284><169>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0131.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0365", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<178><0><326><31>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0009.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0366", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<284><395><383><483>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0014.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0367", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<50><4><65><93>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0368", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><64><12><88>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0038.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0369", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<42><41><67><84>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0056.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0370", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><24><39>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0093.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0371", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<419><493><429><500>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Low-covered grassland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0014.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0372", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<14><46><65><88>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0082.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0373", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><9><24><47>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0132.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0374", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<13><301><42><339>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0110.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0375", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<375><266><418><297>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Sparse woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0064.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0376", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<368><0><436><74>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0117.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0377", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><57><512><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0026.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0378", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<299><0><325><11>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0037.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0379", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<405><45><446><72>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0065.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0380", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<51><0><158><38>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) High-covered grassland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0123.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0381", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<54><0><92><15>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0382", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<479><191><512><247>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0015.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0383", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<63><154><98><179>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0087.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0384", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<386><495><438><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0076.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0385", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<44><280><87><306>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0016.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0386", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<468><0><512><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Urban built-up", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0046.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0387", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<3><64><18><117>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0107.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0388", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><301><20><360>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0017.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0389", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<4><0><512><508>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Ocean", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0104.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0390", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<323><496><360><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Marshland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0076.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0391", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<447><303><503><348>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Resevoir pand", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0019.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0392", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<129><92><156><126>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pand", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0057.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0393", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<9><0><286><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0071.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0394", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<31><75><53><98>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0395", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<68><0><89><16>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0011.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0396", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><194><27><280>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Low-covered grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0397", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><67><-486><97>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0398", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><87><-476><107>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0120.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0399", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><1><-5><49>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0115.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0400", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<126><119><192><176>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0013.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0401", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<343><450><378><494>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0092.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0402", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<428><0><473><48>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0403", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<49><364><83><394>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement ", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0009.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0404", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<179><28><216><60>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0067.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0405", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<192><30><207><48>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm ", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0049.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0406", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<4><178><36><219>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0035.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0407", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<111><438><148><469>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0076.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0408", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<241><60><283><89>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0094.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0409", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<98><343><130><380>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0105.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0410", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<251><142><291><203>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0060.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0411", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<168><79><223><133>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0020.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0412", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<86><0><173><29>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0066.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0413", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<367><0><438><85>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0116.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0414", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<13><36><47><59>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0415", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<191><0><245><39>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0065.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0416", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><305><84><485>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Urban built-up ", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0124.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0417", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<17><391><62><440>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) High-covered grassland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0028.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0418", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<432><407><465><442>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0063.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0419", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><438><66><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0015.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0420", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<252><70><408><159>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0046.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0421", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<173><375><242><409>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0093.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0422", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<148><111><223><172>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0036.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0423", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<297><122><427><180>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0121.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0424", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<280><375><317><432>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0081.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0425", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<139><113><280><226>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0426", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<92><368><262><466>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservior pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0026.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0427", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<21><390><71><445>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0128.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0428", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<433><406><460><454>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0056.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0429", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><36><45><117>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0430", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<287><127><385><220>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Ocean", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0108.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0431", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<491><159><510><196>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0118.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0432", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<476><329><512><377>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Sand", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0021.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0433", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<122><50><208><105>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0434", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><47><46><87>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0099.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0435", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<449><470><475><500>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Sparse woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0001.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0436", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<397><386><454><440>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0064.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0437", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<26><349><82><424>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0122.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0438", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<417><465><455><489>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0007.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0439", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<502><460><512><481>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0041.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0440", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><107><82><224>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0030.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0441", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<465><0><512><107>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0069.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0442", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><383><96><452>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0094.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0443", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<150><69><194><95>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0052.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0444", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<124><236><438><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0002.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0445", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<98><0><166><63>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0031.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0446", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<458><353><489><384>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Bare land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0040.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0447", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<407><276><472><338>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0448", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<78><210><99><237>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0102.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0449", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<287><226><390><276>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0450", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<49><389><112><459>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0004.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0451", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<46><95><146><167>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0011.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0452", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<289><168><343><187>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0044.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0453", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<406><110><440><153>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0008.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0454", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<154><425><194><467>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Forest land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0070.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0455", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><400><-321><434>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0079.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0456", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><70><-242><94>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0127.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0457", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><251><-392><296>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Paddy field", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0091.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0458", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><23><-490><60>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0116.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0459", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><407><-262><428>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0016.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0460", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<134><88><146><100>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0461", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<171><221><194><243>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0049.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0462", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<359><273><388><305>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0116.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0463", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<448><219><472><234>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0039.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0464", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<232><86><255><109>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0016.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0465", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<440><163><450><170>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Reservoir pond", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0103.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0466", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<233><215><257><238>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0056.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0467", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<100><36><126><81>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0080.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0468", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<208><162><258><279>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0027.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0469", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<382><106><445><164>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0111.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0470", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<363><170><423><223>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0025.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0471", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<108><323><230><379>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0013.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0472", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<96><220><152><297>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0015.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0473", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><377><57><413>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0028.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0474", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><325><35><379>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0128.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0475", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<484><0><512><21>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0075.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0476", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<56><184><89><299>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0096.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0477", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<222><0><236><9>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0032.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0478", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><322><16><406>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Low-covered grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0100.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0479", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><14><9>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0121.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0480", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><34><16><61>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0043.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0481", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<227><91><280><146>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other forest land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0027.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0482", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><239><22><277>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0021.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0483", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><216><23><253>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Sparse woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0018.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0484", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><296><193><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Urban built-up", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0123.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0485", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><12><12>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0113.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0486", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><0><26><107>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0126.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0487", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<119><0><169><19>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0137.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0488", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<490><501><512><512>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0077.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0489", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><41><45><94>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Reservoir pand", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0013.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0490", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<76><244><108><291>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Other forest land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0090.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0491", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<36><163><76><200>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0105.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0492", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<44><224><109><249>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Other construction land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0062.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0493", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<248><56><269><82>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0091.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0494", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<36><251><66><273>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0045.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0495", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<122><448><240><508>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0089.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0496", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<487><0><512><31>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Low-cover grassland", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0012.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0497", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<96><361><131><392>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) other forest land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0055.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0498", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<354><264><385><292>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0016.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0499", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<0><104><10><141>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0036.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0500", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<251><0><297><31>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0095.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0501", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<393><400><435><442>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) rural settlement", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0001.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0502", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<1><243><28><293>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0014.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0503", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<258><270><375><356>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0017.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0504", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<141><434><175><483>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0018.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0505", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<488><227><511><249>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0142.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0506", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<386><393><462><436>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) rural settlement", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0002.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0507", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<15><368><60><411>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0133.png" + ] + }, + { + "Question_id": "Fine-grained land type classification/0508", + "Question Type": "Single Choice", + "Text": "Recognize the types of land use from satellite and aerial imagesgiven the bounding boxes forreferring objects. Bounding box in the format (xmin, ymin, xmax, ymax), wherethe top-leftcorner is (x_min, y_min) and the bottom-right corner is (x_max, y_max). Theresolution ofsatellite image is 600 x 600. Bounding box: -[<351><489><363><507>]", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Fine-grained land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0134.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Land_Use/Perception/Overall_land_type_classification.json b/jsons/Pedosphere/Land_Use/Perception/Overall_land_type_classification.json new file mode 100644 index 0000000000000000000000000000000000000000..9ebc7141a757091321b31c6af2f933cf22146122 --- /dev/null +++ b/jsons/Pedosphere/Land_Use/Perception/Overall_land_type_classification.json @@ -0,0 +1,10691 @@ +[ + { + "Question_id": "Overall land type classification/0000", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0001", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Rural settlement ", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0087.png" + ] + }, + { + "Question_id": "Overall land type classification/0002", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Sparse woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0003", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0037.png" + ] + }, + { + "Question_id": "Overall land type classification/0004", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Sparse woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0005", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0033.png" + ] + }, + { + "Question_id": "Overall land type classification/0006", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0045.png" + ] + }, + { + "Question_id": "Overall land type classification/0007", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0059.png" + ] + }, + { + "Question_id": "Overall land type classification/0008", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0009", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0067.png" + ] + }, + { + "Question_id": "Overall land type classification/0010", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0022.png" + ] + }, + { + "Question_id": "Overall land type classification/0011", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0012", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) High-covered grassland", + "(C) Lake", + "(D) Saline-alkali soil", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0087.png" + ] + }, + { + "Question_id": "Overall land type classification/0013", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0114.png" + ] + }, + { + "Question_id": "Overall land type classification/0014", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) Rural land", + "(D) Ocean", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0073.png" + ] + }, + { + "Question_id": "Overall land type classification/0015", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0022.png" + ] + }, + { + "Question_id": "Overall land type classification/0016", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) Shool", + "(D) rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0017", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Reservoir pand", + "(C) Beach land", + "(D) Ocean", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0018", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Ocean", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0019", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0033.png" + ] + }, + { + "Question_id": "Overall land type classification/0020", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0044.png" + ] + }, + { + "Question_id": "Overall land type classification/0021", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0077.png" + ] + }, + { + "Question_id": "Overall land type classification/0022", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Shoal", + "(D) Rive canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0081.png" + ] + }, + { + "Question_id": "Overall land type classification/0023", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0052.png" + ] + }, + { + "Question_id": "Overall land type classification/0024", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Farm", + "(B) Grassland", + "(C) Lake", + "(D) Pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0065.png" + ] + }, + { + "Question_id": "Overall land type classification/0025", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Ocean", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0087.png" + ] + }, + { + "Question_id": "Overall land type classification/0026", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Ocean", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0097.png" + ] + }, + { + "Question_id": "Overall land type classification/0027", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0072.png" + ] + }, + { + "Question_id": "Overall land type classification/0028", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0045.png" + ] + }, + { + "Question_id": "Overall land type classification/0029", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0093.png" + ] + }, + { + "Question_id": "Overall land type classification/0030", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) River canal", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0031", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0032", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0042.png" + ] + }, + { + "Question_id": "Overall land type classification/0033", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0034", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0034.png" + ] + }, + { + "Question_id": "Overall land type classification/0035", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Other forest land", + "(C) River canal", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0036", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0052.png" + ] + }, + { + "Question_id": "Overall land type classification/0037", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0131.png" + ] + }, + { + "Question_id": "Overall land type classification/0038", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Marshland", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0117.png" + ] + }, + { + "Question_id": "Overall land type classification/0039", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Dry farm", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0027.png" + ] + }, + { + "Question_id": "Overall land type classification/0040", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0041", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0042", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Paddy field", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0107.png" + ] + }, + { + "Question_id": "Overall land type classification/0043", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0044", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland ", + "(C) Grassland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0011.png" + ] + }, + { + "Question_id": "Overall land type classification/0045", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm ", + "(C) Reservoir pond ", + "(D) Rural settlement ", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0105.png" + ] + }, + { + "Question_id": "Overall land type classification/0046", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Urban built-up", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0047", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0133.png" + ] + }, + { + "Question_id": "Overall land type classification/0048", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Grassland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0044.png" + ] + }, + { + "Question_id": "Overall land type classification/0049", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0026.png" + ] + }, + { + "Question_id": "Overall land type classification/0050", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0029.png" + ] + }, + { + "Question_id": "Overall land type classification/0051", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0052", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0053", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0054", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0073.png" + ] + }, + { + "Question_id": "Overall land type classification/0055", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0056", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Shoal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0057", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) River canal ", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0078.png" + ] + }, + { + "Question_id": "Overall land type classification/0058", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Grassland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0059", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0100.png" + ] + }, + { + "Question_id": "Overall land type classification/0060", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0132.png" + ] + }, + { + "Question_id": "Overall land type classification/0061", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0032.png" + ] + }, + { + "Question_id": "Overall land type classification/0062", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Grassland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0093.png" + ] + }, + { + "Question_id": "Overall land type classification/0063", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Saline-alkali soil", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0046.png" + ] + }, + { + "Question_id": "Overall land type classification/0064", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0116.png" + ] + }, + { + "Question_id": "Overall land type classification/0065", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Lake", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0066", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Dry farm", + "(C) River canal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0067", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) River canal", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0068", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Shrubbery", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0069", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0042.png" + ] + }, + { + "Question_id": "Overall land type classification/0070", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) High-covered grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0071", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Rural settlement", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0072", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) High-covered grassland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0042.png" + ] + }, + { + "Question_id": "Overall land type classification/0073", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) paddy field", + "(B) other forest land", + "(C) Woodland", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0074", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0033.png" + ] + }, + { + "Question_id": "Overall land type classification/0075", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0098.png" + ] + }, + { + "Question_id": "Overall land type classification/0076", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0107.png" + ] + }, + { + "Question_id": "Overall land type classification/0077", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0037.png" + ] + }, + { + "Question_id": "Overall land type classification/0078", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0079", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0080", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0010.png" + ] + }, + { + "Question_id": "Overall land type classification/0081", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0078.png" + ] + }, + { + "Question_id": "Overall land type classification/0082", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Shoal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0097.png" + ] + }, + { + "Question_id": "Overall land type classification/0083", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0084", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0054.png" + ] + }, + { + "Question_id": "Overall land type classification/0085", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Paddy field ", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0038.png" + ] + }, + { + "Question_id": "Overall land type classification/0086", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0047.png" + ] + }, + { + "Question_id": "Overall land type classification/0087", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Shrubbery", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0088", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Sand", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0076.png" + ] + }, + { + "Question_id": "Overall land type classification/0089", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0074.png" + ] + }, + { + "Question_id": "Overall land type classification/0090", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0072.png" + ] + }, + { + "Question_id": "Overall land type classification/0091", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0092", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement ", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0093", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Gobi", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0094.png" + ] + }, + { + "Question_id": "Overall land type classification/0094", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0095", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0069.png" + ] + }, + { + "Question_id": "Overall land type classification/0096", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0107.png" + ] + }, + { + "Question_id": "Overall land type classification/0097", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0065.png" + ] + }, + { + "Question_id": "Overall land type classification/0098", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0057.png" + ] + }, + { + "Question_id": "Overall land type classification/0099", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Paddy field", + "(C) Dry farm", + "(D) Grassland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0062.png" + ] + }, + { + "Question_id": "Overall land type classification/0100", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0069.png" + ] + }, + { + "Question_id": "Overall land type classification/0101", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0139.png" + ] + }, + { + "Question_id": "Overall land type classification/0102", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0108.png" + ] + }, + { + "Question_id": "Overall land type classification/0103", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0104", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Rural settlement", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0105", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Paddy field", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0061.png" + ] + }, + { + "Question_id": "Overall land type classification/0106", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0090.png" + ] + }, + { + "Question_id": "Overall land type classification/0107", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0046.png" + ] + }, + { + "Question_id": "Overall land type classification/0108", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0109", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0110", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0086.png" + ] + }, + { + "Question_id": "Overall land type classification/0111", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0100.png" + ] + }, + { + "Question_id": "Overall land type classification/0112", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0113", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0114", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0105.png" + ] + }, + { + "Question_id": "Overall land type classification/0115", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0116", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0090.png" + ] + }, + { + "Question_id": "Overall land type classification/0117", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0103.png" + ] + }, + { + "Question_id": "Overall land type classification/0118", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0054.png" + ] + }, + { + "Question_id": "Overall land type classification/0119", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0120", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0106.png" + ] + }, + { + "Question_id": "Overall land type classification/0121", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Shoal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0122", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0126.png" + ] + }, + { + "Question_id": "Overall land type classification/0123", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0124", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0056.png" + ] + }, + { + "Question_id": "Overall land type classification/0125", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0077.png" + ] + }, + { + "Question_id": "Overall land type classification/0126", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0127", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry darm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0048.png" + ] + }, + { + "Question_id": "Overall land type classification/0128", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0129", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0013.png" + ] + }, + { + "Question_id": "Overall land type classification/0130", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0131", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0132", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) River canal", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0116.png" + ] + }, + { + "Question_id": "Overall land type classification/0133", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0067.png" + ] + }, + { + "Question_id": "Overall land type classification/0134", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) other construction land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0101.png" + ] + }, + { + "Question_id": "Overall land type classification/0135", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0034.png" + ] + }, + { + "Question_id": "Overall land type classification/0136", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0024.png" + ] + }, + { + "Question_id": "Overall land type classification/0137", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Other forest land", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0072.png" + ] + }, + { + "Question_id": "Overall land type classification/0138", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0139", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Urban built-up", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0090.png" + ] + }, + { + "Question_id": "Overall land type classification/0140", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Other forest land", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0010.png" + ] + }, + { + "Question_id": "Overall land type classification/0141", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0033.png" + ] + }, + { + "Question_id": "Overall land type classification/0142", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0143", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0102.png" + ] + }, + { + "Question_id": "Overall land type classification/0144", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Shoal", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0041.png" + ] + }, + { + "Question_id": "Overall land type classification/0145", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Paddy field", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0040.png" + ] + }, + { + "Question_id": "Overall land type classification/0146", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0147", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0022.png" + ] + }, + { + "Question_id": "Overall land type classification/0148", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) River canal", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0108.png" + ] + }, + { + "Question_id": "Overall land type classification/0149", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0014.png" + ] + }, + { + "Question_id": "Overall land type classification/0150", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0044.png" + ] + }, + { + "Question_id": "Overall land type classification/0151", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0076.png" + ] + }, + { + "Question_id": "Overall land type classification/0152", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Sand", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0049.png" + ] + }, + { + "Question_id": "Overall land type classification/0153", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0154", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Sand", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0155", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0045.png" + ] + }, + { + "Question_id": "Overall land type classification/0156", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0064.png" + ] + }, + { + "Question_id": "Overall land type classification/0157", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0088.png" + ] + }, + { + "Question_id": "Overall land type classification/0158", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0102.png" + ] + }, + { + "Question_id": "Overall land type classification/0159", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0069.png" + ] + }, + { + "Question_id": "Overall land type classification/0160", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0161", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0016.png" + ] + }, + { + "Question_id": "Overall land type classification/0162", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0063.png" + ] + }, + { + "Question_id": "Overall land type classification/0163", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0056.png" + ] + }, + { + "Question_id": "Overall land type classification/0164", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0165", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0004.png" + ] + }, + { + "Question_id": "Overall land type classification/0166", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0135.png" + ] + }, + { + "Question_id": "Overall land type classification/0167", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0168", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0121.png" + ] + }, + { + "Question_id": "Overall land type classification/0169", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) River canal", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0170", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0009.png" + ] + }, + { + "Question_id": "Overall land type classification/0171", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Sparse woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0172", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0173", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0020.png" + ] + }, + { + "Question_id": "Overall land type classification/0174", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0058.png" + ] + }, + { + "Question_id": "Overall land type classification/0175", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0176", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0177", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) River canal", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0036.png" + ] + }, + { + "Question_id": "Overall land type classification/0178", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0179", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) other forest land", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0180", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Gobi", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0039.png" + ] + }, + { + "Question_id": "Overall land type classification/0181", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Urban built-up", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0078.png" + ] + }, + { + "Question_id": "Overall land type classification/0182", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Sparse woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0089.png" + ] + }, + { + "Question_id": "Overall land type classification/0183", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shoal", + "(B) Grassland", + "(C) Gobi", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0040.png" + ] + }, + { + "Question_id": "Overall land type classification/0184", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0054.png" + ] + }, + { + "Question_id": "Overall land type classification/0185", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ACD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0038.png" + ] + }, + { + "Question_id": "Overall land type classification/0186", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0038.png" + ] + }, + { + "Question_id": "Overall land type classification/0187", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Other construction land", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0128.png" + ] + }, + { + "Question_id": "Overall land type classification/0188", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Other construction land", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0124.png" + ] + }, + { + "Question_id": "Overall land type classification/0189", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Medium-covered grasslang", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0190", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Reservoir pond", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0061.png" + ] + }, + { + "Question_id": "Overall land type classification/0191", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Reservoir pond", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0036.png" + ] + }, + { + "Question_id": "Overall land type classification/0192", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Paddy field", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0081.png" + ] + }, + { + "Question_id": "Overall land type classification/0193", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Medium-covered grasslang", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0088.png" + ] + }, + { + "Question_id": "Overall land type classification/0194", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0195", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Rural settlement", + "(B) Grassland", + "(C) Dry farm ", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0112.png" + ] + }, + { + "Question_id": "Overall land type classification/0196", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0080.png" + ] + }, + { + "Question_id": "Overall land type classification/0197", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field ", + "(B) Dry farm ", + "(C) Woodland ", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0020.png" + ] + }, + { + "Question_id": "Overall land type classification/0198", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0047.png" + ] + }, + { + "Question_id": "Overall land type classification/0199", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0063.png" + ] + }, + { + "Question_id": "Overall land type classification/0200", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) River canal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0201", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0202", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0203", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0080.png" + ] + }, + { + "Question_id": "Overall land type classification/0204", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Sparse woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0205", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0206", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Paddy field", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0128.png" + ] + }, + { + "Question_id": "Overall land type classification/0207", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0054.png" + ] + }, + { + "Question_id": "Overall land type classification/0208", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0209", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0112.png" + ] + }, + { + "Question_id": "Overall land type classification/0210", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0026.png" + ] + }, + { + "Question_id": "Overall land type classification/0211", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0086.png" + ] + }, + { + "Question_id": "Overall land type classification/0212", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0213", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0112.png" + ] + }, + { + "Question_id": "Overall land type classification/0214", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0098.png" + ] + }, + { + "Question_id": "Overall land type classification/0215", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0027.png" + ] + }, + { + "Question_id": "Overall land type classification/0216", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0086.png" + ] + }, + { + "Question_id": "Overall land type classification/0217", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0049.png" + ] + }, + { + "Question_id": "Overall land type classification/0218", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0007.png" + ] + }, + { + "Question_id": "Overall land type classification/0219", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0132.png" + ] + }, + { + "Question_id": "Overall land type classification/0220", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0103.png" + ] + }, + { + "Question_id": "Overall land type classification/0221", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Sparse woodland", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0037.png" + ] + }, + { + "Question_id": "Overall land type classification/0222", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Other construction land", + "(C) Other forest land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0024.png" + ] + }, + { + "Question_id": "Overall land type classification/0223", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0020.png" + ] + }, + { + "Question_id": "Overall land type classification/0224", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0054.png" + ] + }, + { + "Question_id": "Overall land type classification/0225", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0226", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Urban built-up", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0015.png" + ] + }, + { + "Question_id": "Overall land type classification/0227", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Other construction land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0228", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Other forest land", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0108.png" + ] + }, + { + "Question_id": "Overall land type classification/0229", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0053.png" + ] + }, + { + "Question_id": "Overall land type classification/0230", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0059.png" + ] + }, + { + "Question_id": "Overall land type classification/0231", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Paddy field", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0232", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0061.png" + ] + }, + { + "Question_id": "Overall land type classification/0233", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0103.png" + ] + }, + { + "Question_id": "Overall land type classification/0234", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0133.png" + ] + }, + { + "Question_id": "Overall land type classification/0235", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0236", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0041.png" + ] + }, + { + "Question_id": "Overall land type classification/0237", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0238", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0239", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0240", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0241", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0065.png" + ] + }, + { + "Question_id": "Overall land type classification/0242", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) River canal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0243", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0037.png" + ] + }, + { + "Question_id": "Overall land type classification/0244", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Reservoir pond", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0046.png" + ] + }, + { + "Question_id": "Overall land type classification/0245", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0246", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Other construction land", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0105.png" + ] + }, + { + "Question_id": "Overall land type classification/0247", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0248", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) River canal", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0073.png" + ] + }, + { + "Question_id": "Overall land type classification/0249", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0102.png" + ] + }, + { + "Question_id": "Overall land type classification/0250", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Urban built-up", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0251", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0252", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Other forest land", + "(C) Reservoir pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0253", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0101.png" + ] + }, + { + "Question_id": "Overall land type classification/0254", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) woodland", + "(B) dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0255", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0256", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0072.png" + ] + }, + { + "Question_id": "Overall land type classification/0257", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0258", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0135.png" + ] + }, + { + "Question_id": "Overall land type classification/0259", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0125.png" + ] + }, + { + "Question_id": "Overall land type classification/0260", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0108.png" + ] + }, + { + "Question_id": "Overall land type classification/0261", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0262", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Reservoir pond", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0023.png" + ] + }, + { + "Question_id": "Overall land type classification/0263", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0264", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Other construction land", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0010.png" + ] + }, + { + "Question_id": "Overall land type classification/0265", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0020.png" + ] + }, + { + "Question_id": "Overall land type classification/0266", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0067.png" + ] + }, + { + "Question_id": "Overall land type classification/0267", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0268", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Gobi", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0080.png" + ] + }, + { + "Question_id": "Overall land type classification/0269", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Gobi", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0105.png" + ] + }, + { + "Question_id": "Overall land type classification/0270", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0048.png" + ] + }, + { + "Question_id": "Overall land type classification/0271", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0115.png" + ] + }, + { + "Question_id": "Overall land type classification/0272", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0273", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0081.png" + ] + }, + { + "Question_id": "Overall land type classification/0274", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0128.png" + ] + }, + { + "Question_id": "Overall land type classification/0275", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0276", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0277", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0026.png" + ] + }, + { + "Question_id": "Overall land type classification/0278", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0032.png" + ] + }, + { + "Question_id": "Overall land type classification/0279", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0010.png" + ] + }, + { + "Question_id": "Overall land type classification/0280", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0104.png" + ] + }, + { + "Question_id": "Overall land type classification/0281", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Gobi", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0061.png" + ] + }, + { + "Question_id": "Overall land type classification/0282", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Sparse woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0110.png" + ] + }, + { + "Question_id": "Overall land type classification/0283", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0284", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0053.png" + ] + }, + { + "Question_id": "Overall land type classification/0285", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Other", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0286", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0051.png" + ] + }, + { + "Question_id": "Overall land type classification/0287", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Urban built-up", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0121.png" + ] + }, + { + "Question_id": "Overall land type classification/0288", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Rural settlement", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0289", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0083.png" + ] + }, + { + "Question_id": "Overall land type classification/0290", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0064.png" + ] + }, + { + "Question_id": "Overall land type classification/0291", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0104.png" + ] + }, + { + "Question_id": "Overall land type classification/0292", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0129.png" + ] + }, + { + "Question_id": "Overall land type classification/0293", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0039.png" + ] + }, + { + "Question_id": "Overall land type classification/0294", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0295", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Urban and rural", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0120.png" + ] + }, + { + "Question_id": "Overall land type classification/0296", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0135.png" + ] + }, + { + "Question_id": "Overall land type classification/0297", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0130.png" + ] + }, + { + "Question_id": "Overall land type classification/0298", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0028.png" + ] + }, + { + "Question_id": "Overall land type classification/0299", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0300", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Bare land", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0014.png" + ] + }, + { + "Question_id": "Overall land type classification/0301", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0063.png" + ] + }, + { + "Question_id": "Overall land type classification/0302", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0090.png" + ] + }, + { + "Question_id": "Overall land type classification/0303", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0073.png" + ] + }, + { + "Question_id": "Overall land type classification/0304", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0052.png" + ] + }, + { + "Question_id": "Overall land type classification/0305", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Sparse woodland", + "(C) River canal", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0050.png" + ] + }, + { + "Question_id": "Overall land type classification/0306", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0061.png" + ] + }, + { + "Question_id": "Overall land type classification/0307", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0038.png" + ] + }, + { + "Question_id": "Overall land type classification/0308", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Urban built-up", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0120.png" + ] + }, + { + "Question_id": "Overall land type classification/0309", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Urban built-up", + "(C) Rural settlement", + "(D) other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0310", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0091.png" + ] + }, + { + "Question_id": "Overall land type classification/0311", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Sparse woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0103.png" + ] + }, + { + "Question_id": "Overall land type classification/0312", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Reservoir pond", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0003.png" + ] + }, + { + "Question_id": "Overall land type classification/0313", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0034.png" + ] + }, + { + "Question_id": "Overall land type classification/0314", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Sparse woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0132.png" + ] + }, + { + "Question_id": "Overall land type classification/0315", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0316", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0036.png" + ] + }, + { + "Question_id": "Overall land type classification/0317", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0318", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0319", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Rural settlement", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0049.png" + ] + }, + { + "Question_id": "Overall land type classification/0320", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Other forest land", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0120.png" + ] + }, + { + "Question_id": "Overall land type classification/0321", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0050.png" + ] + }, + { + "Question_id": "Overall land type classification/0322", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0085.png" + ] + }, + { + "Question_id": "Overall land type classification/0323", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0051.png" + ] + }, + { + "Question_id": "Overall land type classification/0324", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0325", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Paddy field", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0077.png" + ] + }, + { + "Question_id": "Overall land type classification/0326", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0327", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0080.png" + ] + }, + { + "Question_id": "Overall land type classification/0328", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) River canal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0329", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0120.png" + ] + }, + { + "Question_id": "Overall land type classification/0330", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0331", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0077.png" + ] + }, + { + "Question_id": "Overall land type classification/0332", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Paddy field", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0101.png" + ] + }, + { + "Question_id": "Overall land type classification/0333", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0064.png" + ] + }, + { + "Question_id": "Overall land type classification/0334", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0335", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0008.png" + ] + }, + { + "Question_id": "Overall land type classification/0336", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0109.png" + ] + }, + { + "Question_id": "Overall land type classification/0337", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0121.png" + ] + }, + { + "Question_id": "Overall land type classification/0338", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0084.png" + ] + }, + { + "Question_id": "Overall land type classification/0339", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0115.png" + ] + }, + { + "Question_id": "Overall land type classification/0340", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0341", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0342", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0137.png" + ] + }, + { + "Question_id": "Overall land type classification/0343", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0344", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0008.png" + ] + }, + { + "Question_id": "Overall land type classification/0345", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0003.png" + ] + }, + { + "Question_id": "Overall land type classification/0346", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Ocean", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0125.png" + ] + }, + { + "Question_id": "Overall land type classification/0347", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0139.png" + ] + }, + { + "Question_id": "Overall land type classification/0348", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0003.png" + ] + }, + { + "Question_id": "Overall land type classification/0349", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0018.png" + ] + }, + { + "Question_id": "Overall land type classification/0350", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0104.png" + ] + }, + { + "Question_id": "Overall land type classification/0351", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0352", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0007.png" + ] + }, + { + "Question_id": "Overall land type classification/0353", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0125.png" + ] + }, + { + "Question_id": "Overall land type classification/0354", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Lake", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0005.png" + ] + }, + { + "Question_id": "Overall land type classification/0355", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0117.png" + ] + }, + { + "Question_id": "Overall land type classification/0356", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0018.png" + ] + }, + { + "Question_id": "Overall land type classification/0357", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0006.png" + ] + }, + { + "Question_id": "Overall land type classification/0358", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0078.png" + ] + }, + { + "Question_id": "Overall land type classification/0359", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0011.png" + ] + }, + { + "Question_id": "Overall land type classification/0360", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0139.png" + ] + }, + { + "Question_id": "Overall land type classification/0361", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0362", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0074.png" + ] + }, + { + "Question_id": "Overall land type classification/0363", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0364", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0058.png" + ] + }, + { + "Question_id": "Overall land type classification/0365", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0131.png" + ] + }, + { + "Question_id": "Overall land type classification/0366", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0009.png" + ] + }, + { + "Question_id": "Overall land type classification/0367", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0014.png" + ] + }, + { + "Question_id": "Overall land type classification/0368", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0369", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0038.png" + ] + }, + { + "Question_id": "Overall land type classification/0370", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0056.png" + ] + }, + { + "Question_id": "Overall land type classification/0371", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0093.png" + ] + }, + { + "Question_id": "Overall land type classification/0372", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Low-covered grassland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0014.png" + ] + }, + { + "Question_id": "Overall land type classification/0373", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0082.png" + ] + }, + { + "Question_id": "Overall land type classification/0374", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0132.png" + ] + }, + { + "Question_id": "Overall land type classification/0375", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Woodland", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0110.png" + ] + }, + { + "Question_id": "Overall land type classification/0376", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Sparse woodland", + "(C) Reservor pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0064.png" + ] + }, + { + "Question_id": "Overall land type classification/0377", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Gobi", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0117.png" + ] + }, + { + "Question_id": "Overall land type classification/0378", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Paddy field", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0026.png" + ] + }, + { + "Question_id": "Overall land type classification/0379", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Shoal", + "(D) Rutal settlement", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0065.png" + ] + }, + { + "Question_id": "Overall land type classification/0380", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) High-coverd grassland", + "(B) Grassland", + "(C) Marshland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0123.png" + ] + }, + { + "Question_id": "Overall land type classification/0381", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0382", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "AD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0015.png" + ] + }, + { + "Question_id": "Overall land type classification/0383", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) urban built-up", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0087.png" + ] + }, + { + "Question_id": "Overall land type classification/0384", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0076.png" + ] + }, + { + "Question_id": "Overall land type classification/0385", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0016.png" + ] + }, + { + "Question_id": "Overall land type classification/0386", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) High-covered grassland", + "(B) Urban built-up", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0046.png" + ] + }, + { + "Question_id": "Overall land type classification/0387", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0107.png" + ] + }, + { + "Question_id": "Overall land type classification/0388", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0017.png" + ] + }, + { + "Question_id": "Overall land type classification/0389", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Ocean", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0104.png" + ] + }, + { + "Question_id": "Overall land type classification/0390", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Gobi", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0076.png" + ] + }, + { + "Question_id": "Overall land type classification/0391", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Ocean", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0019.png" + ] + }, + { + "Question_id": "Overall land type classification/0392", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0057.png" + ] + }, + { + "Question_id": "Overall land type classification/0393", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0071.png" + ] + }, + { + "Question_id": "Overall land type classification/0394", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0395", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0011.png" + ] + }, + { + "Question_id": "Overall land type classification/0396", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) River canal", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0397", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0044.png" + ] + }, + { + "Question_id": "Overall land type classification/0398", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0120.png" + ] + }, + { + "Question_id": "Overall land type classification/0399", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Lake", + "(C) Grassland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0115.png" + ] + }, + { + "Question_id": "Overall land type classification/0400", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0013.png" + ] + }, + { + "Question_id": "Overall land type classification/0401", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0092.png" + ] + }, + { + "Question_id": "Overall land type classification/0402", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm ", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0403", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0009.png" + ] + }, + { + "Question_id": "Overall land type classification/0404", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Shrubbery ", + "(D) Grassland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0067.png" + ] + }, + { + "Question_id": "Overall land type classification/0405", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Medium-covered grasslang", + "(C) Lake", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0049.png" + ] + }, + { + "Question_id": "Overall land type classification/0406", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Urban built-up ", + "(D) Other forest land ", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0035.png" + ] + }, + { + "Question_id": "Overall land type classification/0407", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0076.png" + ] + }, + { + "Question_id": "Overall land type classification/0408", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland ", + "(B) Grassland", + "(C) Paddy field", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0094.png" + ] + }, + { + "Question_id": "Overall land type classification/0409", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Reservoir pond ", + "(B) Woodland", + "(C) Dry farm", + "(D) Paddy field", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0060.png" + ] + }, + { + "Question_id": "Overall land type classification/0410", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0020.png" + ] + }, + { + "Question_id": "Overall land type classification/0411", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0066.png" + ] + }, + { + "Question_id": "Overall land type classification/0412", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0116.png" + ] + }, + { + "Question_id": "Overall land type classification/0413", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Other forest land", + "(B) Reservoir pond", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0414", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field ", + "(B) Dry farm", + "(C) Reservoir pond", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0065.png" + ] + }, + { + "Question_id": "Overall land type classification/0415", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0124.png" + ] + }, + { + "Question_id": "Overall land type classification/0416", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) High-covered grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0028.png" + ] + }, + { + "Question_id": "Overall land type classification/0417", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0063.png" + ] + }, + { + "Question_id": "Overall land type classification/0418", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) River canal", + "(C) Urban built-up", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0015.png" + ] + }, + { + "Question_id": "Overall land type classification/0419", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0046.png" + ] + }, + { + "Question_id": "Overall land type classification/0420", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0093.png" + ] + }, + { + "Question_id": "Overall land type classification/0421", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0036.png" + ] + }, + { + "Question_id": "Overall land type classification/0422", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0121.png" + ] + }, + { + "Question_id": "Overall land type classification/0423", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry field", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0081.png" + ] + }, + { + "Question_id": "Overall land type classification/0424", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0425", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0026.png" + ] + }, + { + "Question_id": "Overall land type classification/0426", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0128.png" + ] + }, + { + "Question_id": "Overall land type classification/0427", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0056.png" + ] + }, + { + "Question_id": "Overall land type classification/0428", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0429", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Oceon", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0108.png" + ] + }, + { + "Question_id": "Overall land type classification/0430", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0118.png" + ] + }, + { + "Question_id": "Overall land type classification/0431", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Urban built-up", + "(B) Grassland", + "(C) Lake", + "(D) Sand", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0432", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0433", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0099.png" + ] + }, + { + "Question_id": "Overall land type classification/0434", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0001.png" + ] + }, + { + "Question_id": "Overall land type classification/0435", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0064.png" + ] + }, + { + "Question_id": "Overall land type classification/0436", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0122.png" + ] + }, + { + "Question_id": "Overall land type classification/0437", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0007.png" + ] + }, + { + "Question_id": "Overall land type classification/0438", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0041.png" + ] + }, + { + "Question_id": "Overall land type classification/0439", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0030.png" + ] + }, + { + "Question_id": "Overall land type classification/0440", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0069.png" + ] + }, + { + "Question_id": "Overall land type classification/0441", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0094.png" + ] + }, + { + "Question_id": "Overall land type classification/0442", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0443", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0002.png" + ] + }, + { + "Question_id": "Overall land type classification/0444", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0031.png" + ] + }, + { + "Question_id": "Overall land type classification/0445", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Bare land", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0040.png" + ] + }, + { + "Question_id": "Overall land type classification/0446", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0447", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Dry farm", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0102.png" + ] + }, + { + "Question_id": "Overall land type classification/0448", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0449", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0004.png" + ] + }, + { + "Question_id": "Overall land type classification/0450", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Sand", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0011.png" + ] + }, + { + "Question_id": "Overall land type classification/0451", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0044.png" + ] + }, + { + "Question_id": "Overall land type classification/0452", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0008.png" + ] + }, + { + "Question_id": "Overall land type classification/0453", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) forest land", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0070.png" + ] + }, + { + "Question_id": "Overall land type classification/0454", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) River canal", + "(D) Marshland", + "(E) Unable to decide" + ], + "Ground Truth": "BCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0079.png" + ] + }, + { + "Question_id": "Overall land type classification/0455", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Reservior pond", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0127.png" + ] + }, + { + "Question_id": "Overall land type classification/0456", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Paddy field", + "(D) Woodlan", + "(E) Unable to decide" + ], + "Ground Truth": "CD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0091.png" + ] + }, + { + "Question_id": "Overall land type classification/0457", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0116.png" + ] + }, + { + "Question_id": "Overall land type classification/0458", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) River canal", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0016.png" + ] + }, + { + "Question_id": "Overall land type classification/0459", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Urban built-up", + "(C) Rural settlement", + "(D) Other construction land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0460", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0049.png" + ] + }, + { + "Question_id": "Overall land type classification/0461", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Woodland", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0116.png" + ] + }, + { + "Question_id": "Overall land type classification/0462", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) River canal", + "(D) Other forest land", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0039.png" + ] + }, + { + "Question_id": "Overall land type classification/0463", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Rural settlement", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0016.png" + ] + }, + { + "Question_id": "Overall land type classification/0464", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Dry farm", + "(C) Woodland", + "(D) Reservoir pond", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0103.png" + ] + }, + { + "Question_id": "Overall land type classification/0465", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0056.png" + ] + }, + { + "Question_id": "Overall land type classification/0466", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Woodland", + "(D) Dry farm", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0080.png" + ] + }, + { + "Question_id": "Overall land type classification/0467", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Sand", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0027.png" + ] + }, + { + "Question_id": "Overall land type classification/0468", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0111.png" + ] + }, + { + "Question_id": "Overall land type classification/0469", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0025.png" + ] + }, + { + "Question_id": "Overall land type classification/0470", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Rural settlement", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0013.png" + ] + }, + { + "Question_id": "Overall land type classification/0471", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0015.png" + ] + }, + { + "Question_id": "Overall land type classification/0472", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Shrubbery", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0028.png" + ] + }, + { + "Question_id": "Overall land type classification/0473", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0128.png" + ] + }, + { + "Question_id": "Overall land type classification/0474", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0075.png" + ] + }, + { + "Question_id": "Overall land type classification/0475", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0096.png" + ] + }, + { + "Question_id": "Overall land type classification/0476", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0032.png" + ] + }, + { + "Question_id": "Overall land type classification/0477", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0100.png" + ] + }, + { + "Question_id": "Overall land type classification/0478", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Resevoir pand", + "(C) Rural settlement", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "ABC", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0121.png" + ] + }, + { + "Question_id": "Overall land type classification/0479", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0043.png" + ] + }, + { + "Question_id": "Overall land type classification/0480", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0027.png" + ] + }, + { + "Question_id": "Overall land type classification/0481", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0021.png" + ] + }, + { + "Question_id": "Overall land type classification/0482", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0018.png" + ] + }, + { + "Question_id": "Overall land type classification/0483", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0123.png" + ] + }, + { + "Question_id": "Overall land type classification/0484", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0113.png" + ] + }, + { + "Question_id": "Overall land type classification/0485", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Shoal", + "(C) Lake", + "(D) Barea rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0126.png" + ] + }, + { + "Question_id": "Overall land type classification/0486", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0137.png" + ] + }, + { + "Question_id": "Overall land type classification/0487", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0077.png" + ] + }, + { + "Question_id": "Overall land type classification/0488", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0013.png" + ] + }, + { + "Question_id": "Overall land type classification/0489", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0090.png" + ] + }, + { + "Question_id": "Overall land type classification/0490", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0105.png" + ] + }, + { + "Question_id": "Overall land type classification/0491", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) High-cover grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0062.png" + ] + }, + { + "Question_id": "Overall land type classification/0492", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0091.png" + ] + }, + { + "Question_id": "Overall land type classification/0493", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0045.png" + ] + }, + { + "Question_id": "Overall land type classification/0494", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0089.png" + ] + }, + { + "Question_id": "Overall land type classification/0495", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0012.png" + ] + }, + { + "Question_id": "Overall land type classification/0496", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) sparse woodland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0055.png" + ] + }, + { + "Question_id": "Overall land type classification/0497", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) paddy field", + "(B) Dry farm", + "(C) Lake", + "(D) woodland", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0016.png" + ] + }, + { + "Question_id": "Overall land type classification/0498", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "BD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0036.png" + ] + }, + { + "Question_id": "Overall land type classification/0499", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Marshland", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0095.png" + ] + }, + { + "Question_id": "Overall land type classification/0500", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Reservoir pond", + "(C) Rural settlement", + "(D) Other", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0001.png" + ] + }, + { + "Question_id": "Overall land type classification/0501", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0014.png" + ] + }, + { + "Question_id": "Overall land type classification/0502", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Woodland", + "(B) Grassland", + "(C) Dry farm", + "(D) Shoal", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0017.png" + ] + }, + { + "Question_id": "Overall land type classification/0503", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Shrubbery", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0018.png" + ] + }, + { + "Question_id": "Overall land type classification/0504", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Ocean", + "(B) Grassland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0142.png" + ] + }, + { + "Question_id": "Overall land type classification/0505", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) River canal", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0002.png" + ] + }, + { + "Question_id": "Overall land type classification/0506", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0133.png" + ] + }, + { + "Question_id": "Overall land type classification/0507", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Dry farm", + "(B) Woodland", + "(C) Lake", + "(D) Bare rock", + "(E) Unable to decide" + ], + "Ground Truth": "AB", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0134.png" + ] + }, + { + "Question_id": "Overall land type classification/0508", + "Question Type": "Multiple Choice", + "Text": "What are the types of land use in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Overall land type classification", + "Answer Choices": [ + "(A) Paddy field", + "(B) Grassland", + "(C) Dry farm", + "(D) Rural settlement", + "(E) Unable to decide" + ], + "Ground Truth": "ABCD", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0117.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Land_Use/Perception/Visual_groudning_of_land_types.json b/jsons/Pedosphere/Land_Use/Perception/Visual_groudning_of_land_types.json new file mode 100644 index 0000000000000000000000000000000000000000..4ed0d0211a4f239e0fae048d57c8f7d0e8159661 --- /dev/null +++ b/jsons/Pedosphere/Land_Use/Perception/Visual_groudning_of_land_types.json @@ -0,0 +1,7114 @@ +[ + { + "Question_id": "Visual groudning of land types/0000", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<452><0><512><20>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0001", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<452><0><512><20>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0002", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<452><0><512><20>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0003", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><34><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0033.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0004", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<463><9><503><52>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0045.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0005", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<414><318><476><393>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0059.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0006", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left part of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><18><46>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0007", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: This plot is located in the upper right corner of the picture, andthe land use type is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<343><0><512><148>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0067.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0008", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located The plot is located in the bottom right corner of thepicture first from the left, and the land use type is sand .", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<258><469><362><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0022.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0009", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<471><88><512><144>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0010", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<31><0><113><33>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0087.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0011", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<35><12><313><175>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0114.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0012", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom side of the picture, and the land use typeis other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<276><425><327><489>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0073.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0013", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located in the lower right corner of the image and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<351><393><512><487>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0014", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<64><276><116><369>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0015", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<343><336><391><413>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0016", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><467><62><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0033.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0017", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the left side of the picture, and the land use type ispaddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><226><116><372>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0018", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<67><440><119><508>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0077.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0019", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located on the right side of the image and has a land use typeof river canal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><256><489><313>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0081.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0020", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<431><326><480><396>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0052.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0021", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<56><105><107><186>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0065.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0022", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><123><27><168>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0087.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0023", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><317><34><395>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0097.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0024", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<8><413><133><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0072.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0025", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<20><152><84><235>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0045.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0026", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<454><469><501><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0093.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0027", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<407><406><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0028", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<401><0><473><48>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0029", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located in the lower left corner of the image and has a land use type of Dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><315><214><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0042.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0030", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located in the lower right corner of the image and has a land use type of dryfarm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<379><466><469><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0031", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located in the upper left corner of the image and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<123><23><175><68>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0034.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0032", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<484><28><512><66>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0033", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><60><120>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0131.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0034", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is located in the lower left corner of the image and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<140><383><190><442>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0052.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0035", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<2><322><57><405>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0117.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0036", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><120><234>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0027.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0037", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><2><51><65>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0038", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><5><30><62>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0039", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper bottom left of the picture, and the land usetype is Paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<34><487><105><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0107.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0040", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><117><87>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0041", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the left side of the picture, and theland use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<60><192><187><300>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0011.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0042", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<462><0><512><107>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0043", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This parcel is upper-center in the image and has a land use type of dryfarm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<178><103><228><179>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0133.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0044", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<281><0><476><68>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0045", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<49><475><131><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0026.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0046", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<486><371><512><424>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0029.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0047", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<397><0><512><80>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0048", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the picture and the land use type isPaddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<180><206><265><252>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0049", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is Dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><358><31><389>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0050", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<447><88><512><213>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0073.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0051", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the lower part of the picture, and theland use type is Marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<199><310><301><436>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0052", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><439><65><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0053", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<478><465><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0078.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0054", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><67><145><208>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0055", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<337><0><447><156>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0100.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0056", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<464><0><512><56>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0132.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0057", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<379><32><512><101>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0032.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0058", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<397><136><482><212>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0093.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0059", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<398><8><443><55>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0046.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0060", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<394><0><450><40>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0116.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0061", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<53><0><246><191>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0062", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<113><454><229><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0063", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<307><180><361><213>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0064", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><49><72><104>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0065", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<71><443><112><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0042.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0066", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<485><0><512><30>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0067", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><329><512><380>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0068", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<91><416><133><450>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0042.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0069", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is bare land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<20><53><65><102>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0070", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<434><49><512><285>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0033.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0071", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<356><38><412><90>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0098.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0072", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<121><0><233><112>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0107.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0073", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<49><463><76><499>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0037.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0074", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<42><348><137><482>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0075", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><36><93>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0076", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<66><0><145><144>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0078.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0077", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><452><45><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0010.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0078", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><504><44><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0078.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0079", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<62><384><106><468>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0097.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0080", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<429><0><459><17>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0081", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<407><374><512><498>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0054.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0082", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the lower part of the picture, and theland use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<158><390><256><486>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0038.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0083", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<69><427><99><480>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0047.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0084", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located on the left side of the picture and the land use type iswoodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><86><268><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0085", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<408><0><512><68>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0076.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0086", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<501><488><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0074.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0087", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><65><46><227>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0072.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0088", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<15><0><71><23>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0089", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><104><183>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0090", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<441><54><512><216>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0094.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0091", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<422><221><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0092", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<476><35><512><134>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0069.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0093", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<464><92><512><181>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0107.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0094", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<482><0><512><166>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0065.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0095", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<453><0><507><33>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0057.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0096", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the picture and the land use type isgrassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<260><197><311><340>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0062.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0097", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<20><474><100><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0069.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0098", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and its land usetype is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<93><450><142><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0139.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0099", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<350><456><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0108.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0100", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<115><26><289><208>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0101", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the left side of the picture and theland use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><166><57><241>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0102", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<434><0><512><61>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0061.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0103", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<377><33><410><72>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0090.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0104", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<369><21><400><72>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0046.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0105", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<487><348><512><430>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0106", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper middle corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<203><0><256><49>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0107", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<68><425><126><505>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0086.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0108", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rual settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<432><396><512><498>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0100.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0109", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of paddy dield.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<24><478><102><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0110", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower middle corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<240><453><283><497>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0111", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of rural settlement..", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<78><0><283><168>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0105.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0112", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of rural settlement..", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><341><492><377>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0113", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><419><21><476>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0090.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0114", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><488><30><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0103.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0115", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<414><0><490><31>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0054.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0116", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<495><399><512><461>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0117", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<422><345><492><412>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0106.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0118", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of shoal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<493><0><512><16>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0040.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0119", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<468><21><512><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0126.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0120", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<382><363><512><484>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0121", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of woodland..", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<475><464><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0056.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0122", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<490><40><512><81>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0077.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0123", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><34><9><57>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0124", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<452><0><512><20>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0125", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<400><0><447><51>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0126", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<360><39><397><91>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0127", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<464><1><512><96>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0013.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0128", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper side of the picture, and the land use typeis rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<244><23><312><77>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0129", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<93><402><126><437>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0130", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<226><307><281><344>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0116.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0131", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><75><48>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0067.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0132", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<337><0><485><38>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0101.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0133", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<39><347><98><384>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0034.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0134", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><121><58>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0024.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0135", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<45><10><127><106>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0072.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0136", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><76><72>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0090.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0137", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type isrural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<120><229><200><359>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0010.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0138", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located near the middle of the upper side of the picture, and theland use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<227><7><310><94>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0033.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0139", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the left side of the picture, and theland use type is sand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><224><58><293>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0140", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<460><461><512><494>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0102.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0141", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><263><380><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0041.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0142", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<304><441><367><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0040.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0143", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<418><438><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0144", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><70><70>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0022.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0145", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<401><74><490><146>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0108.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0146", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<459><22><512><66>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0014.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0147", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located near the middle on the right side of the picture, and theland use type is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<425><262><512><361>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0148", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><384><26><441>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0076.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0149", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is sand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<34><402><139><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0049.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0150", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<383><356><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0151", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<364><81><512><149>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0152", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><0><91><53>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0045.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0153", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<413><466><486><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0064.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0154", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><27><62><79>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0088.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0155", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<286><40><499><80>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0102.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0156", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><19><35>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0069.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0157", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located near the middle of the upper side of the picture, and theland use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<177><0><259><71>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0158", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the center of the picture and the land use type isrural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<252><251><301><284>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0016.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0159", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located near the middle on the left side of the picture, and theland use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<9><195><90><246>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0063.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0160", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<307><249><406><395>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0056.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0161", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<445><3><489><56>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0162", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the center of the picture and the land use type iswoodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<146><247><366><355>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0004.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0163", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<475><476><501><494>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0135.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0164", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper side of the picture, and the land use typeis dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<199><0><272><63>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0165", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<353><38><368><78>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0121.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0166", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><159><503><208>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0167", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><105><474><137>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0009.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0168", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom side of the picture, and the land use typeis paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<263><437><283><465>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0169", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<47><25><60><88>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0170", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<353><97><376><131>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0020.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0171", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type isrural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<224><201><285><244>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0058.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0172", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<428><0><461><83>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0173", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is lack.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><240><286><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0174", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><105><44><177>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0036.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0175", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><426><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0176", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<181><403><228><455>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0177", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is gobi.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<491><101><512><188>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0039.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0178", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<217><4><258><35>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0089.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0179", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is shoal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><0><64><50>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0040.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0180", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is low-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><134><192>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0054.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0181", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><184><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0038.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0182", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture , and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<286><414><350><467>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0038.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0183", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><181><44><231>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0128.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0184", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<34><140><229><331>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0124.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0185", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<360><464><408><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0186", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><487><65><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0061.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0187", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<46><493><76><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0036.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0188", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><409><55><511>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0081.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0189", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<83><0><178><125>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0088.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0190", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<311><69><396><238>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0191", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<371><106><502><260>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0112.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0192", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<268><200><403><279>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0080.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0193", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<326><349><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0020.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0194", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<352><390><441><462>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0047.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0195", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in middle position of the picture, and the land use typeis other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<189><221><261><324>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0063.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0196", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of otherconstruction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><114><158>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0197", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<460><86><512><121>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0198", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the image and has a land usetype of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<490><59><512><119>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0199", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<418><424><479><473>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0080.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0200", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<431><300><508><364>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0201", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture and the land use type isother construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<231><210><338><334>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0202", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the right side of the picture, and theland use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<498><230><512><259>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0128.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0203", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<413><427><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0054.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0204", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is saline-alkali soil.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><490><20><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0205", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<437><112><508><178>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0112.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0206", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<68><422><111><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0026.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0207", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<438><10><474><36>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0086.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0208", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<404><38><512><205>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0209", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the lower side of the picture, and theland use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<219><362><302><423>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0112.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0210", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><305><112><489>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0098.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0211", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<444><405><471><444>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0027.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0212", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><70><90>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0086.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0213", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<14><14><77><60>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0049.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0214", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<165><65><204><111>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0007.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0215", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><308><282>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0132.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0216", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><41><20><63>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0103.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0217", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<488><60><512><105>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0037.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0218", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><100><17><130>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0024.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0219", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><43><28>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0020.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0220", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is sand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><0><183><86>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0054.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0221", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<469><5><511><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0222", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><475><23><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0015.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0223", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<72><329><446><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0224", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><331><100><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0108.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0225", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<456><506><480><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0053.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0226", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<303><376><463><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0059.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0227", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<440><51><458><90>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0228", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type isreservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<202><290><278><350>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0061.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0229", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<103><471><134><496>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0103.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0230", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<335><0><510><433>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0133.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0231", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the map and the land usetype is rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<259><0><512><142>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0232", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the map, and the land usetype is shrub.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<3><356><60><416>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0041.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0233", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><97><49>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0234", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot of land is located in the upper right corner of the picture and itsland use type is a lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<455><39><512><101>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0235", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<423><0><512><64>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0236", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<468><0><512><69>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0237", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<443><0><510><23>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0065.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0238", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<409><0><512><92>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0239", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><61><507><105>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0037.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0240", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is medium-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<366><297><506><399>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0046.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0241", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<151><1><192><17>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0242", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><322><178><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0105.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0243", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<486><0><512><41>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0244", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><239><232><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0073.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0245", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<472><53><500><87>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0102.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0246", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<398><463><468><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0247", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<416><360><490><443>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0248", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<467><38><511><76>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0249", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<312><0><352><48>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0101.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0250", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<478><0><512><21>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0251", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<482><6><509><39>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0252", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<357><0><457><22>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0072.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0253", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<494><0><512><34>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0254", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<425><0><507><53>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0135.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0255", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located slightly lower in the middle of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<212><320><314><422>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0125.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0256", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<441><1><512><81>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0108.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0257", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<477><0><512><59>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0258", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is river and canal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<4><435><62><508>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0023.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0259", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<449><0><512><99>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0260", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot of land is located directly below the picture and its land use typeis Gobi.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<284><440><337><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0010.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0261", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is Rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><88><58><165>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0020.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0262", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<484><0><512><30>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0067.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0263", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<448><0><510><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0264", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<453><0><512><59>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0080.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0265", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Gobi.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><0><507><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0105.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0266", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<476><9><509><125>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0048.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0267", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<447><0><493><60>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0115.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0268", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<436><0><464><16>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0269", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<480><0><512><36>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0081.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0270", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<469><0><512><32>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0128.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0271", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<475><37><512><79>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0272", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<377><0><423><23>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0273", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<466><0><512><32>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0026.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0274", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<432><7><450><31>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0032.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0275", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<393><413><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0010.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0276", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><138><13><153>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0104.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0277", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<79><1><147><35>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0061.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0278", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><409><42><481>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0110.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0279", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The plot is located in the upper right corner of the picture and its land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<496><0><512><28>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0280", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located above the picture and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<199><27><229><39>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0053.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0281", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<405><0><512><27>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0282", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This map is located in the upper right corner of the picture. The land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<492><0><507><13>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0051.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0283", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><3><489><36>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0121.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0284", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<466><1><512><169>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0285", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><238><512><277>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0083.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0286", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This graph is located at the lower right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<391><414><426><460>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0064.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0287", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<440><60><468><95>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0104.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0288", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<447><8><510><83>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0129.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0289", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: This plot is located in the lower right corner of the picture andthe land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<246><357><512><510>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0039.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0290", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located on the right of the picture and the land use type iswoodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<431><412><512><510>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0291", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This picture is located in the upper left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<67><12><122><36>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0120.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0292", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<436><128><457><134>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0135.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0293", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<444><0><497><13>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0130.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0294", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper middle corner of the picture and the land use type is rural.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<243><0><256><24>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0028.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0295", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<285><74><321><127>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0296", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<441><209><505><293>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0014.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0297", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<453><109><505><173>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0063.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0298", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<257><0><512><242>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0090.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0299", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<329><33><347><43>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0073.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0300", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the bottom of the picture , and the land use type isrural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<98><479><166><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0052.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0301", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<459><0><477><20>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0117.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0302", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper side of the picture, and the land use typeis river canal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<264><0><288><31>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0050.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0303", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<461><140><491><186>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0061.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0304", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<39><494><80><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0038.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0305", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<447><0><464><15>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0120.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0306", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<28><48><72><78>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0307", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<288><30><320><79>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0091.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0308", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<58><76><68><91>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0103.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0309", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<61><457><92><498>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0003.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0310", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<363><12><378><25>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0034.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0311", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<40><24><63><49>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0132.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0312", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper side of the picture, and the land use typeis Reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<260><172><277><203>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0313", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<123><28><173><49>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0036.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0314", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<143><133><159><138>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0315", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the right side of the picture, and the land use typeis dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<397><260><427><298>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0316", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the right side of the picture, and the land use typeis rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<351><214><423><240>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0049.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0317", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<104><304><116><314>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0120.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0318", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<468><26><504><52>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0050.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0319", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<381><456><406><472>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0085.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0320", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<37><68><49><107>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0051.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0321", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lft side of the picture, and the land use type is.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<288><15><324><108>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0322", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<447><499><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0077.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0323", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the left side of the picture, and theland use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<7><271><45><319>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0324", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<453><0><512><114>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0080.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0325", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><168><220>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0326", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><71><38>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0120.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0327", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><66><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0328", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<310><0><341><41>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0077.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0329", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<475><455><512><506>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0101.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0330", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is shoal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<482><0><512><102>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0064.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0331", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<354><329><388><393>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0332", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is shoal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<475><61><512><107>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0008.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0333", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><484><21><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0109.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0334", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle on the left side of the picture, and theland use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><314><6><329>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0121.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0335", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle on the right side of the picture, and theland use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<397><260><467><320>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0084.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0336", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><439><41><483>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0115.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0337", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<483><0><512><18>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0338", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located slightly lower in the center of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<201><346><224><406>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0339", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><425><50><488>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0137.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0340", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<327><410><366><455>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0341", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<310><439><348><486>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0008.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0342", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><410><93><448>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0003.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0343", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located near the middle on the right side of the picture, and theland use type is bare land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<489><197><512><235>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0125.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0344", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture and the land usetype is shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><181><207>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0139.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0345", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower right of the picture and the land use typeis grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<370><247><512><443>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0003.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0346", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower right of the picture and the land use typeis river canal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<407><400><512><455>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0018.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0347", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower left of the picture and the land use type isother construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<101><250><190><340>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0104.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0348", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower right of the picture and the land use typeis other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<493><367><512><387>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0349", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower left of the picture and the land use type iswoodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<27><489><62><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0007.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0350", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<416><15><439><37>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0125.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0351", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle of the lower side of the picture, and theland use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<188><461><284><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0005.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0352", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<75><250><224><424>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0117.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0353", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<493><466><512><477>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0018.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0354", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<60><477><121><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0006.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0355", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-right corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<371><166><476><261>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0078.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0356", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<175><112><246><225>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0011.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0357", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<16><0><75><69>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0139.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0358", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<379><5><430><77>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0359", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<379><166><484><237>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0074.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0360", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<455><172><512><238>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0361", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<68><33><120><88>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0058.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0362", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<265><0><380><175>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0131.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0363", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><157><81><303>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0009.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0364", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><431><61><498>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0014.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0365", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<65><42><87><73>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0366", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<70><73><85><88>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0038.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0367", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><0><28><44>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0056.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0368", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<31><30><74><73>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0093.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0369", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<362><474><429><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0014.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0370", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the left of the picture, and the land use type is dryfarm .", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><209><150><378>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0082.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0371", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the central of the picture, and the land use type isrural settlement.This piece of land is the largest in area", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<103><146><215><370>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0132.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0372", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is Woodland .", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<2><0><89><223>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0110.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0373", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<446><0><512><91>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0064.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0374", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<477><0><512><45>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0117.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0375", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right of the picture, and the land use typeis dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<318><500><346><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0026.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0376", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom of the picture, and the land use type isdry farm .Its area is the largest in the picture.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<294><300><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0037.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0377", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the right of the picture, and the land use type isreservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<363><237><428><328>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0065.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0378", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper middle of the picture, and the land use typeis Sanline-alkali soil.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<212><0><326><14>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0123.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0379", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This L-shaped plot is located in the bottom left corner of the picture, andthe land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<21><289><135><433>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0380", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type ishigh-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><77><507><422>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0015.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0381", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is resevoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<76><0><121><22>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0087.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0382", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<256><372><289><421>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0076.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0383", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<135><419><155><494>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0016.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0384", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<158><0><217><42>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0046.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0385", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This square plot of land is located in the upper left corner of the picture,and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<48><0><83><28>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0107.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0386", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located below the center of the picture, and the land use type isrural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<177><364><186><374>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0017.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0387", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<211><469><238><500>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0104.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0388", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is gobi.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<373><35><512><231>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0076.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0389", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is ocean.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<394><471><502><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0019.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0390", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<286><19><309><83>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0057.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0391", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located on the left side of the river canal, and the land usetype is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<5><3><230><403>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0071.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0392", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><107><11><144>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0393", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This elliptical plot is located above the center of the picture, and the land use type is low-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<236><26><285><98>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0011.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0394", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is medium-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<399><0><469><126>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0395", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><2><0><19>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0396", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><466><0><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0120.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0397", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><420><0><509>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0115.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0398", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><453><55><498>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0013.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0399", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<435><11><465><91>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0092.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0400", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<486><388><512><436>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0401", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<323><477><365><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0009.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0402", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><477><23><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0067.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0403", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<127><0><189><72>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0049.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0404", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><350><17><382>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0035.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0405", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<155><0><251><119>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0076.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0406", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<465><317><512><483>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0094.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0407", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<113><127><167><165>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0105.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0408", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<59><392><79><407>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0060.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0409", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<83><385><200><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0020.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0410", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is medium-covered grasslang.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<41><264><97><320>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0066.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0411", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<440><419><469><453>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0116.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0412", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<85><0><127><61>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0413", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<25><143><77><188>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0065.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0414", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<6><0><75><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0087.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0415", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<197><421><283><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0124.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0416", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><200><360><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0028.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0417", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<495><484><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0063.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0418", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<119><477><205><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0015.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0419", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of Reservoir.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<25><426><94><445>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0046.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0420", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<375><430><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0093.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0421", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of dry darm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<13><0><59><81>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0036.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0422", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><28><17><95>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0121.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0423", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><104><58>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0081.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0424", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><492><34><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0425", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<53><470><93><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0026.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0426", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<33><496><60><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0128.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0427", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of shrubbery.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<471><442><512><470>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0056.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0428", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<366><0><487><22>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0429", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is ocean.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<432><0><512><54>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0108.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0430", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The plot is located in the upper right corner of the picture and its land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<372><0><512><53>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0118.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0431", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is sand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<351><406><428><436>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0432", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<354><52><403><107>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0433", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the image and has a land usetype of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<1><0><123><63>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0099.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0434", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<483><400><512><493>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0001.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0435", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture and has a land use type of paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><441><82><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0122.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0436", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of 的dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<440><503><495><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0007.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0437", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and has a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<460><435><493><475>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0064.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0438", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<502><432><512><457>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0041.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0439", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<45><242><115><373>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0030.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0440", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the left side of the picture, and the land use type isbare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><218><11><234>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0069.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0441", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is bare rock.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<474><0><512><45>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0094.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0442", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<454><25><509><95>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0052.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0443", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower corner of picture z and has a land use typeof 的dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><482><57><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0002.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0444", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is bare land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<380><23><466><142>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0031.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0445", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot of land is located in the upper right corner of the picture and itsland use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<482><0><512><32>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0040.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0446", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located at the lower right corner of the picture and its land usetype is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<342><412><406><449>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0447", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture and the land usetype is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<473><359><504><432>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0102.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0448", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot of land is located in the upper left corner of the picture and itsland use type is lake.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<58><0><108><26>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0449", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is saline-alkali soil.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<382><461><417><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0004.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0450", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle on the left side of the picture, and theland use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<51><257><137><315>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0011.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0451", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<490><14><512><77>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0044.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0452", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<494><7><512><72>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0008.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0453", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is reservior pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<123><464><154><488>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0070.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0454", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is Dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><22><0><37>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0079.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0455", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><2><26>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0127.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0456", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><3><0><47>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0091.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0457", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><45><0><67>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0116.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0458", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the right corner of the picture, and the land use typeis dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><422><0><440>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0016.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0459", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<44><287><83><326>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0460", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<160><367><181><396>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0049.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0461", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<79><420><95><433>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0116.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0462", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the right side of the picture, and the land use typeis other forest land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<487><301><507><332>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0039.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0463", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom side of the picture, and the land use typeis reservoir pond.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<222><408><291><460>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0016.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0464", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<356><3><402><83>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0103.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0465", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type isgrassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<280><319><303><348>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0056.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0466", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<64><0><78><5>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0080.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0467", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<79><65><165><105>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0027.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0468", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<153><74><205><129>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0111.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0469", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and is L-shaped,and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<423><21><512><147>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0025.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0470", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is rural settlement and this plot is the smallest rectangular plot.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<311><385><331><408>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0013.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0471", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This L-shaped plot of land is located in the bottom left corner of thepicture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><385><53><467>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0015.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0472", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><42><41><71>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0028.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0473", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upperlleft corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<182><57><241><140>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0128.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0474", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<366><104><376><120>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0075.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0475", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is high-covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<432><370><512><504>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0096.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0476", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><13><15><115>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0032.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0477", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bootm left corner of the picture, and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<77><500><95><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0100.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0478", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is resevoir pand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<86><29><156><100>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0121.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0479", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower left corner of the picture, and the land use type is rural settlement. The plot has an L-shaped shape.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<14><360><99><433>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0043.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0480", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is dry farm and this plot is the largest L-shaped plot.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<85><53><201><190>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0027.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0481", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is the largest plot in the entire picture, located in the center of the pictureand the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<216><227><454><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0021.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0482", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is sparse woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<344><329><377><480>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0018.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0483", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<318><497><346><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0123.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0484", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is low--covered grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<109><97><238><262>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0113.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0485", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is dry farm and it is the smallest plot in the entire picture.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<494><234><512><263>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0126.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0486", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><120><129><141>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0137.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0487", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<479><491><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0077.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0488", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottomr left corner of the picture, and the land use type is urban built-up.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><294><76><340>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0013.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0489", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is other construction land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><342><109><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0090.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0490", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture and is thelongest L-shaped plot, and the land use type is Rural settlement .", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<151><229><208><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0105.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0491", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the center of the picture, and the land use type isriver canal.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><148><408><326>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0062.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0492", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: This circular plot is located in the upper left corner of thepicture, with a land use type of rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><0><11><17>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0091.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0493", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture and is thesmallest triangular plot,the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><78><7><126>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0045.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0494", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom right corner of the picture and is thesmallest triangular plot. The land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<399><461><409><473>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0089.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0495", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture and is thesmallest triangular plot. The land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><497><33><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0012.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0496", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<0><464><54><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0055.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0497", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the lower right corner of the picture, and the land use type is paddy field.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<473><464><512><512>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0016.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0498", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<441><32><512><89>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0036.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0499", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is Marshland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<466><0><512><35>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0095.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0500", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture and the land usetype is rural settlement.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<421><88><460><150>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0001.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0501", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<23><59><78><102>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0014.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0502", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is woodland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<46><311><76><330>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0017.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0503", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is grassland.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<77><307><139><376>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0018.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0504", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the middle right corner of the picture, and the land use type is dry farm.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<483><207><512><293>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0142.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0505", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the bottom left corner of the picture, and the land use type is resevoir pand.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<93><396><116><437>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0002.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0506", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper right corner of the picture, and the land use type is beach land.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<378><0><488><123>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0133.png" + ] + }, + { + "Question_id": "Visual groudning of land types/0507", + "Question Type": "Visual Grounding", + "Text": "Given a 600x600 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This plot is located in the upper left corner of the picture, and the land usetype is ocean.", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual groudning of land types", + "Ground Truth": "{<10><0><215><114>}", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0134.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Land_Use/Perception/Visual_localization_of_land_use_types.json b/jsons/Pedosphere/Land_Use/Perception/Visual_localization_of_land_use_types.json new file mode 100644 index 0000000000000000000000000000000000000000..082eb596922fc708f5c44a95550f11d6ee391267 --- /dev/null +++ b/jsons/Pedosphere/Land_Use/Perception/Visual_localization_of_land_use_types.json @@ -0,0 +1,10691 @@ +[ + { + "Question_id": "Visual localization of land use types/0000", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0001", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0087.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0002", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0003", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0004", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0033.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0005", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0045.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0006", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0059.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0007", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0008", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0067.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0009", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0022.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0010", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0011", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0087.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0012", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0114.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0013", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0073.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0014", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0022.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0015", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0016", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0017", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 12", + "(B) 13", + "(C) 14", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0018", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0033.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0019", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0020", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0077.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0021", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0081.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0022", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0052.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0023", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0065.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0024", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0087.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0025", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0097.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0026", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0072.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0027", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0045.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0028", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0093.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0029", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0030", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0031", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0042.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0032", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0033", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0034.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0034", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0035", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0131.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0036", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0052.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0037", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0117.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0038", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0027.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0039", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0040", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0041", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0107.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0042", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0043", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0011.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0044", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0045", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0133.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0046", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0047", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0026.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0048", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0029.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0049", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0050", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0051", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0052", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0073.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0053", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0054", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0055", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0078.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0056", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0057", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0100.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0058", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0132.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0059", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0032.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0060", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0093.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0061", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0046.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0062", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0116.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0063", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0064", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0065", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0066", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0067", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0042.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0068", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0069", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0070", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0042.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0071", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0072", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0033.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0073", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0098.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0074", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0107.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0075", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0037.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0076", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0077", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0078", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0078.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0079", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0010.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0080", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 10", + "(C) 11", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0078.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0081", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0097.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0082", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0083", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0054.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0084", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0038.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0085", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0047.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0086", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0087", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0076.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0088", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0074.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0089", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0072.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0090", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0091", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0092", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0094.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0093", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0094", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0069.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0095", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0107.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0096", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0065.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0097", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0057.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0098", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0062.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0099", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0069.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0100", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0139.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0101", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0108.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0102", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0103", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0104", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0061.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0105", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0090.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0106", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0046.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0107", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0108", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0109", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0086.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0110", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0100.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0111", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0112", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0113", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0105.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0114", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0115", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0090.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0116", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0103.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0117", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0054.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0118", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0119", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 10", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0106.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0120", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 11", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0040.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0121", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0126.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0122", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0123", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0056.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0124", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0077.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0125", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0126", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0048.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0127", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0128", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0129", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0013.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0130", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0131", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0132", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0116.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0133", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0067.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0134", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0101.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0135", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0034.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0136", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0024.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0137", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0072.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0138", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0090.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0139", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0010.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0140", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0033.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0141", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0142", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0102.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0143", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0041.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0144", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0040.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0145", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0146", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0022.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0147", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0108.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0148", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0014.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0149", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0150", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0076.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0151", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0049.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0152", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0153", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0154", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0045.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0155", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0064.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0156", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0088.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0157", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0102.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0158", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0069.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0159", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0160", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0016.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0161", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0063.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0162", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0056.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0163", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0164", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0004.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0165", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0135.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0166", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0167", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0121.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0168", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0169", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0009.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0170", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0171", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0172", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0020.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0173", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0058.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0174", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0175", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0176", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0036.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0177", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0178", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0179", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0039.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0180", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0089.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0181", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0040.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0182", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0054.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0183", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0038.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0184", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0038.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0185", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0128.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0186", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0124.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0187", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0188", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0061.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0189", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0036.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0190", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 36", + "(B) 26", + "(C) 16", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0081.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0191", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0088.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0192", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0193", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0112.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0194", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0080.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0195", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0020.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0196", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 18", + "(C) 27", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0047.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0197", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0063.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0198", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0199", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0200", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 10", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0201", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0080.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0202", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0203", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0204", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0128.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0205", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0054.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0206", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0207", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0112.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0208", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0026.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0209", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0086.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0210", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0211", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0112.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0212", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0098.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0213", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0027.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0214", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0086.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0215", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0049.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0216", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0007.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0217", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0132.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0218", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0103.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0219", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0037.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0220", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0024.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0221", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0020.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0222", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0054.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0223", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0224", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0015.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0225", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0226", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0108.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0227", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0053.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0228", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0059.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0229", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0230", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0061.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0231", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0103.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0232", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0133.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0233", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0234", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0041.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0235", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0236", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0237", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0238", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0239", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 8", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0065.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0240", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0241", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0037.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0242", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0046.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0243", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0244", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0105.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0245", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0246", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0073.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0247", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0102.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0248", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0249", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0250", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0251", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0101.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0252", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0253", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0254", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0072.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0255", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0256", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0135.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0257", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0125.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0258", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0108.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0259", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0260", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0023.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0261", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0262", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0010.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0263", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0020.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0264", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0067.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0265", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0266", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0080.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0267", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0105.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0268", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0048.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0269", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0115.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0270", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0271", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0081.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0272", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0128.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0273", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0274", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0275", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0026.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0276", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0032.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0277", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0010.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0278", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0104.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0279", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0061.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0280", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0110.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0281", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0282", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0053.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0283", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0284", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0051.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0285", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0121.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0286", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0287", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0083.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0288", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0064.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0289", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0104.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0290", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0129.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0291", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0039.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0292", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0293", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0120.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0294", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0135.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0295", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0130.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0296", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0028.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0297", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0298", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0014.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0299", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0063.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0300", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0090.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0301", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0073.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0302", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0052.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0303", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0117.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0304", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0050.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0305", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0061.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0306", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0038.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0307", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0120.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0308", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0309", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0091.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0310", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0103.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0311", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0003.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0312", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0034.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0313", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0132.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0314", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0315", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0036.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0316", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0317", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0318", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0049.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0319", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0120.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0320", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0050.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0321", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0085.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0322", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0051.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0323", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0324", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0077.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0325", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 8", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0326", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0080.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0327", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0328", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0120.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0329", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0330", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0077.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0331", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0101.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0332", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0064.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0333", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0334", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0008.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0335", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0109.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0336", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0121.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0337", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0084.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0338", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0115.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0339", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0340", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0341", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0137.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0342", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0343", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0008.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0344", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0003.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0345", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0125.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0346", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0139.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0347", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0003.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0348", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0018.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0349", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0104.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0350", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0351", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0007.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0352", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0125.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0353", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0005.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0354", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0117.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0355", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0018.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0356", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0006.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0357", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0078.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0358", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0011.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0359", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0139.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0360", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0361", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0074.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0362", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0363", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0058.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0364", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0131.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0365", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0009.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0366", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0014.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0367", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0368", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0038.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0369", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0056.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0370", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0093.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0371", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0014.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0372", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 4", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0082.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0373", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0132.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0374", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0110.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0375", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0064.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0376", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0117.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0377", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0026.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0378", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0037.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0379", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0065.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0380", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0123.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0381", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0382", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0015.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0383", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer 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localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0016.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0386", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0046.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0387", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0107.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0388", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0017.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0389", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0104.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0390", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0076.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0391", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0019.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0392", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0057.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0393", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0071.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0394", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0395", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0011.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0396", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0397", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0398", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 9", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0120.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0399", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0115.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0400", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0013.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0401", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0092.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0402", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0403", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0009.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0404", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0067.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0405", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 6", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0049.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0406", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 9", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0035.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0407", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 7", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0076.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0408", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 28", + "(C) 38", + "(D) 48", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0094.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0409", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0105.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0410", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 24", + "(B) 4", + "(C) 16", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0060.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0411", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0020.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0412", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0066.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0413", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0116.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0414", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0415", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0065.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0416", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 6", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0124.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0417", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0028.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0418", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0063.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0419", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0015.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0420", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0046.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0421", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0093.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0422", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 10", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0036.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0423", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0121.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0424", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0081.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0425", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0426", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0026.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0427", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 9", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0128.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0428", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 8", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0056.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0429", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0430", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0108.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0431", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0118.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0432", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0021.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0433", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0434", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0099.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0435", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0001.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0436", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0064.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0437", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0122.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0438", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0007.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0439", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0041.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0440", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0030.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0441", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0069.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0442", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0094.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0443", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0052.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0444", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 7", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0002.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0445", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0031.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0446", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0040.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0447", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0448", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0102.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0449", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0450", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0004.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0451", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0011.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0452", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 6", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0044.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0453", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 5", + "(C) 7", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0008.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0454", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0070.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0455", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 3", + "(B) 5", + "(C) 7", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0079.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0456", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0127.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0457", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0091.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0458", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 4", + "(C) 6", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0116.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0459", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 9", + "(C) 6", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0016.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0460", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0461", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0049.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0462", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0116.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0463", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0039.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0464", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0016.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0465", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0103.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0466", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0056.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0467", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0080.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0468", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0027.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0469", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0111.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0470", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0025.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0471", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0013.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0472", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0015.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0473", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0028.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0474", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0128.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0475", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0075.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0476", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0096.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0477", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0032.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0478", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0100.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0479", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0121.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0480", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0043.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0481", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0027.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0482", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0021.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0483", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0018.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0484", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0123.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0485", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0113.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0486", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0126.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0487", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0137.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0488", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0077.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0489", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0013.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0490", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0090.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0491", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0105.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0492", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0062.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0493", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0091.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0494", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0045.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0495", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0089.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0496", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0012.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0497", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0055.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0498", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0016.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0499", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0036.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0500", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0095.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0501", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0001.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0502", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0014.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0503", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0017.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0504", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0018.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0505", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0142.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0506", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 5", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0002.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0507", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0133.png" + ] + }, + { + "Question_id": "Visual localization of land use types/0508", + "Question Type": "Single Choice", + "Text": "How many types of land use are there in the entire image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Perception", + "L4-task": "Visual localization of land use types", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0134.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Land_Use/Reasoning/Counting_of_land_types_under_complex_conditions.json b/jsons/Pedosphere/Land_Use/Reasoning/Counting_of_land_types_under_complex_conditions.json new file mode 100644 index 0000000000000000000000000000000000000000..d7f85c8ec7ff7755b8aa21ebb1652ce67aaa88e1 --- /dev/null +++ b/jsons/Pedosphere/Land_Use/Reasoning/Counting_of_land_types_under_complex_conditions.json @@ -0,0 +1,9431 @@ +[ + { + "Question_id": "Counting of land types under complex conditions/0000", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0001", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0025.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0002", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0003", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0004", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0005", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sparsewoodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0001.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0006", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0007", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0008", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0011.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0009", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0010", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0033.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0011", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerack?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0045.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0012", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-coverdgrassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0059.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0013", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0060.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0014", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0067.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0015", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0022.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0016", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0087.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0017", + "Question Type": "Single Choice", + "Text": "The number of land parcels with land use type shrubbery in theimage?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0114.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0018", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a beach land use type oflake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0073.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0019", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0022.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0020", + "Question Type": "Single Choice", + "Text": "The number of land parcels with land use type shool in the image?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0060.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0021", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0075.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0022", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0023", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of coveredgrassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0024", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0033.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0025", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0044.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0026", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0077.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0027", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0028", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0052.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0029", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0065.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0030", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0087.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0031", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0097.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0032", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0072.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0033", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0045.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0034", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0093.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0035", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0036", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of high-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0025.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0037", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0042.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0038", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0039", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0034.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0042", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0052.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0043", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0117.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0044", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0027.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0045", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0047", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0107.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0048", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0025.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0049", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0011.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0050", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0051", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0133.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0052", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0044.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0053", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0026.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0054", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0029.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0055", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0082.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0056", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0095.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0057", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0058", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0073.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0059", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0023.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0060", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0055.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0061", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0078.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0062", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0063", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0100.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0064", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0132.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0065", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0032.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0066", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0093.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0067", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0046.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0068", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0116.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0070", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0074", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0023.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0075", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0076", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of high-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0042.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0077", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0071.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0078", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0033.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0079", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0098.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0080", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0107.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0082", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0066.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0085", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0010.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0088", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0089", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0054.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0090", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0038.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0092", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0093", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0076.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0094", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0074.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0095", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0072.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0096", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0095.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0097", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of gobi?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0082.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0098", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0094.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0099", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0100", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0069.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0101", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0107.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0102", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0065.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0103", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0057.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0104", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0062.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0105", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0069.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0106", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0139.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0107", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0108.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0108", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0082.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0109", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0071.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0110", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0061.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0111", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0090.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0112", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0046.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0113", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0084.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0114", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0086.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0115", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0100.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0116", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0117", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0095.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0118", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 5", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0105.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0119", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 15", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0120", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0090.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0121", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0103.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0123", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0066.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0124", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0106.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0125", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0040.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0126", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0126.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0127", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0130", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0048.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0131", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0066.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0132", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0133", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0013.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0135", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0136", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0116.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0137", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O1_0067.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0139", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0034.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0141", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0072.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0142", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0090.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0143", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0010.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0144", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0033.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0145", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0066.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0147", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of gobi?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0041.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0148", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0040.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0149", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0055.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0150", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0022.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0152", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0014.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0155", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0049.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0157", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0158", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0045.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0159", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0064.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0160", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0088.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0161", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0102.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0162", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0069.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0163", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0164", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0016.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0165", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0063.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0166", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0056.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0167", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0168", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0004.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0169", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0135.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0170", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0171", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0121.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0173", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0009.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0174", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0175", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0176", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0020.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0177", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0058.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0178", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0179", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0055.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0180", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0036.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0181", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0182", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0183", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0039.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0184", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0089.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0185", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0040.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0186", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0054.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0187", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0038.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0188", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0038.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0189", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0128.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0191", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0192", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0061.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0193", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0036.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0194", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0081.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0195", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of medium-covered grasslang?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 9", + "(C) 12", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0088.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0196", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0197", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0112.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0198", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0080.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0199", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0020.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0200", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0047.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0201", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0063.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0202", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0203", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservorpond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0060.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0204", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 8", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0205", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0080.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0206", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0075.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0208", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0128.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0209", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0054.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0210", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0071.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0211", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0112.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0212", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0026.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0213", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0086.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0218", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0086.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0219", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0049.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0220", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0007.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0221", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0132.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0222", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0103.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0223", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0037.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0224", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0024.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0225", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0020.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0226", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0054.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0227", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0231", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0053.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0232", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0059.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0233", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0082.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0234", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0061.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0236", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0133.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0237", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0238", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0041.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0239", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0240", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0241", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0025.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0242", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0243", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0065.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0244", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0095.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0245", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0037.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0247", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0084.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0248", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0105.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0249", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0250", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0073.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0251", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0102.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0252", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0253", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0084.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0256", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0257", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0258", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0072.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0259", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0019.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0260", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0135.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0261", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0125.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0262", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0108.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0263", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0264", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0023.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0265", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0266", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0010.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0267", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0020.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0268", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0067.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0269", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0270", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0080.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0271", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0105.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0272", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0048.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0273", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0115.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0274", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0275", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0081.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0276", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0128.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0277", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0278", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0019.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0279", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0026.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0280", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0032.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0281", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0010.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0282", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0104.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0283", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of gobi?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0061.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0284", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sparsewoodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0110.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0285", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0286", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0053.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0287", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0060.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0288", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0051.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0289", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0121.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0291", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0083.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0294", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0129.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0295", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0039.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0296", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0297", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0120.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0298", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0135.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0299", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0130.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0300", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0028.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0301", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0302", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0014.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0303", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0063.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0304", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0090.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0305", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0073.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0306", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0052.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0307", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0117.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0309", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0061.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0310", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0038.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0311", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0120.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0312", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0084.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0313", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0091.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0314", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0103.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0315", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0003.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0316", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0034.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0317", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0132.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0318", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0319", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0036.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0320", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0066.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0321", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 8", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0019.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0322", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0049.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0323", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0120.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0325", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0085.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0326", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0051.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0327", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0328", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S2_0077.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0329", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0075.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0330", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0080.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0331", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0055.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0332", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0120.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0333", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0334", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0077.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0335", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0101.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0336", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0064.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0337", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0338", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0008.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0339", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0109.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0340", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0121.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0341", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of saline-alkali soil?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0084.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0342", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0115.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0343", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0019.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0344", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0075.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0345", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0137.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0346", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0347", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0008.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0348", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0003.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0349", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0125.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0350", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0139.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0351", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0003.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0352", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0018.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0355", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0007.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0356", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S6_0125.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0357", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0005.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0358", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0117.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0359", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0018.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0360", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0006.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0361", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0078.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0362", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0011.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0363", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0139.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0364", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0365", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0074.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0366", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0367", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0058.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0368", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0131.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0369", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0009.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0370", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0014.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0371", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0082.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0372", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O7_0038.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0373", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0056.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0374", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0093.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0375", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0014.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0377", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 30", + "(B) 17", + "(C) 20", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0132.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0378", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0110.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0379", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0064.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0380", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of gobi?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0117.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0381", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0026.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0382", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0037.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0383", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0065.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0384", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0123.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0385", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of resevairpand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0386", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0015.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0387", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of resevoirpond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0087.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0388", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0076.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0389", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0016.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0390", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of high-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0046.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0391", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0107.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0392", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0017.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0393", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0104.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0394", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of gobi?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T5_0076.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0395", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0019.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0396", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0057.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0397", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0071.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0398", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0399", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0400", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0044.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0401", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O5_0120.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0402", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O14_0115.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0403", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0013.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0404", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0092.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0405", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0407", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0067.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0408", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0049.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0409", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0035.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0411", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 7", + "(B) 17", + "(C) 27", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T6_0094.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0412", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond ?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0105.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0413", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T1_0060.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0414", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0020.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0416", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0116.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0419", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of medium-covered grasslang?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0087.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0420", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0124.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0421", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of marshland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0028.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0422", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low-covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0063.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0423", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0015.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0426", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 7", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0081.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0428", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0026.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0429", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0128.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0431", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0432", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S8_0108.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0433", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0118.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0434", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0021.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0435", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0436", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O23_0099.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0437", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O22_0122.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0438", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0007.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0439", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 9", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O4_0064.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0440", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0041.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0441", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0030.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0442", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0069.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0443", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of barerock?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0094.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0444", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0052.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0445", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0002.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0446", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0031.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0447", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0040.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0448", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0449", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0102.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0450", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0451", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0004.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0452", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0011.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0453", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 1", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0044.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0454", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O10_0008.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0455", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of forestland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0070.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0456", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of urban built-up?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O19_0079.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0457", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0127.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0458", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O20_0091.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0459", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O17_0116.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0460", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of Reserviorpond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O18_0016.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0462", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O16_0049.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0463", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0116.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0465", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0016.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0466", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O2_0103.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0467", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of dry farm?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0056.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0469", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0027.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0470", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S5_0111.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0471", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0025.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0472", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0013.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0473", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O15_0015.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0474", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type ofshrubbery?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O6_0028.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0475", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O8_0128.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0476", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0075.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0477", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sparsewoodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O25_0096.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0478", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sparsewoodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0032.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0479", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S4_0100.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0480", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of resevoirpand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S7_0121.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0481", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of bareland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0043.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0482", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoirpand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T7_0027.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0484", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of resevoirland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O24_0018.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0485", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0123.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0486", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of low--covered grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O9_0113.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0487", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of shoal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0126.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0488", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T2_0137.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0489", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O3_0077.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0490", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T3_0013.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0491", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of woodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S3_0090.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0492", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoirpand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0105.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0493", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0062.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0494", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of sparsewoodland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O26_0091.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0495", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of paddyfield?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O21_0045.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0497", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of rural settlement?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T4_0012.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0498", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of resevoirpand?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/T8_0055.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0499", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/S1_0016.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0500", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0036.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0501", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O11_0095.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0502", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of reservoir pond?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0001.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0503", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of lake?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0014.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0504", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of grassland?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O13_0018.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0505", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0142.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0506", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of river canal?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0002.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0507", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0133.png" + ] + }, + { + "Question_id": "Counting of land types under complex conditions/0508", + "Question Type": "Single Choice", + "Text": "How many land parcels in the image have a land use type of ocean?", + "Dataset": "WHU-OHS", + "L1-task": "Pedosphere", + "L2-task": "Land Use", + "L3-task": "Reasoning", + "L4-task": "Counting of land types under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/WHU-OHS/images/O12_0134.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Change_detection_counting_of_post-disaster_completely_destroyedbuilding.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Change_detection_counting_of_post-disaster_completely_destroyedbuilding.json new file mode 100644 index 0000000000000000000000000000000000000000..8fe09b7217840f35b7913ba6f08f1cbb8c9956f7 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Change_detection_counting_of_post-disaster_completely_destroyedbuilding.json @@ -0,0 +1,11051 @@ +[ + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0000", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0001", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0002", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0003", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0004", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0005", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0006", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0007", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0008", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0009", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0010", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0011", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0012", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0013", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0014", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0015", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0016", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0017", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0018", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0019", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0020", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0021", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0022", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0023", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0024", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0025", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0026", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0027", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0028", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0029", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0030", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0031", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0032", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0033", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0034", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0035", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0036", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0037", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0038", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0039", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0040", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0041", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0042", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0043", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0044", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0045", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0046", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0047", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0048", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0049", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0050", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0051", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0052", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0053", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0054", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0055", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0056", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0057", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0058", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0059", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0060", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0061", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0062", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0063", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0064", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0065", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0066", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0067", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0068", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0069", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0070", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0071", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0072", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0073", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0074", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0075", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 7", + "(B) 5", + "(C) 9", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0076", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0077", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0078", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0079", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0080", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 5", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0081", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0082", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0083", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0084", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0085", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0086", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0087", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0088", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0089", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0090", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0091", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0092", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0093", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0094", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0095", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000433_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000433_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0096", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0097", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0098", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0099", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0100", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0101", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0102", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0103", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0104", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0105", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0106", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0107", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0108", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0109", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0110", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0111", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0112", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0113", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0114", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0115", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0116", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0117", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0118", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0119", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0120", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0121", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0122", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0123", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0124", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0125", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0126", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0127", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0128", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0129", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0130", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0131", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0132", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0133", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0134", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0135", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0136", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0137", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0138", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0139", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0140", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0141", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0142", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0143", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0144", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0145", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0146", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0147", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0148", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0149", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0150", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0151", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0152", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0153", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0154", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0155", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0156", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0157", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0158", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0159", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0160", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0161", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0162", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0163", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0164", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0165", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0166", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0167", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0168", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0169", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0170", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0171", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0172", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0173", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0174", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0175", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0176", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0177", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0178", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0179", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0180", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0181", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0182", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0183", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0184", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0185", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0186", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0187", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0188", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0189", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0190", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0191", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0192", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0193", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0194", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0195", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0196", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0197", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0198", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0199", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0200", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0201", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0202", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0203", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0204", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000333_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0205", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0206", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0207", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0208", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0209", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0210", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0211", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0212", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0213", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0214", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0215", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0216", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0217", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0218", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0219", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0220", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0221", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0222", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0223", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0224", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0225", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0226", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 17", + "(B) 18", + "(C) 19", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0227", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0228", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0229", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0230", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0231", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0232", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0233", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0234", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0235", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0236", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0237", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0238", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0239", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0240", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0241", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0242", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0243", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0244", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0245", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0246", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0247", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0248", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0249", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0250", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0251", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0252", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0253", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0254", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0255", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0256", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0257", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0258", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0259", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0260", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0261", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0262", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0263", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0264", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0265", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0266", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0267", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0268", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0269", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0270", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0271", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0272", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0273", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0274", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0275", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0276", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0277", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0278", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0279", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0280", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0281", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0282", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0283", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0284", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0285", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0286", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0287", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0288", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0289", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0290", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0291", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0292", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0293", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0294", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0295", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0296", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0297", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000493_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000493_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0298", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0299", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0300", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0301", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0302", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0303", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0304", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0305", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0306", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0307", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0308", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0309", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0310", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0311", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0312", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0313", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0314", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0315", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0316", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0317", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0318", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0319", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0320", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0321", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0322", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0323", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0324", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0325", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0326", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0327", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0328", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0329", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0330", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0331", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0332", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0333", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0334", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0335", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0336", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0337", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0338", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0339", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0340", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 18", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0341", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0342", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0343", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 23", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0344", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 61", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0345", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0346", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0347", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0348", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0349", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0350", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0351", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0352", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0353", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0354", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0355", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0356", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0357", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0358", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0359", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0360", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0361", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0362", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0363", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0364", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0365", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0366", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0367", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0368", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0369", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000264_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0370", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0371", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0372", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0373", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0374", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0375", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0376", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0377", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0378", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0379", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0380", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0381", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0382", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0383", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0384", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0385", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0386", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0387", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0388", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 27", + "(B) 28", + "(C) 29", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0389", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0390", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0391", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0392", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0393", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0394", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0395", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0396", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0397", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0398", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0399", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0400", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0401", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0402", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0403", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0404", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0405", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0406", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0407", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0408", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0409", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0410", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0411", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0412", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0413", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0414", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0415", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0416", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0417", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0418", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0419", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0420", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0421", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0422", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0423", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0424", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0425", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0426", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0427", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0428", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0429", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0430", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0431", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0432", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0433", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0434", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0435", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0436", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0437", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0438", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0439", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0440", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0441", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0442", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0443", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0444", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0445", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0446", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0447", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0448", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0449", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0450", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0451", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0452", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0453", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0454", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0455", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0456", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0457", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0458", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0459", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0460", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0461", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0462", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0463", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0464", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0465", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0466", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 12", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0467", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0468", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 2", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0469", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0470", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0471", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0472", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0473", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0474", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0475", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0476", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0477", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0478", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0479", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0480", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0481", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0482", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 7", + "(B) 13", + "(C) 0", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0483", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0484", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0485", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 18", + "(B) 19", + "(C) 20", + "(D) 21", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0486", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0487", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0488", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0489", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0490", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0491", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0492", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0493", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0494", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0495", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many destroyed buildings are there in the whole picture based on two pre disasterand post disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 3", + "(B) 2", + "(C) 1", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0496", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_post_disaster.png" + ] + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0497", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000528_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000528_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0498", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000535_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000535_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0499", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000536_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000536_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0500", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000538_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000538_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Change detection counting of post-disaster completelydestroyed building/0501", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo. How many destroyed buildings are there in the whole picture based on two pre-disasterand post-disaster images? Only require fully destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Change detection counting of post-disaster completely destroyedbuilding", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000539_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000539_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Counting_of_Post-disaster_partially_damaged_building.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Counting_of_Post-disaster_partially_damaged_building.json new file mode 100644 index 0000000000000000000000000000000000000000..953cf01c1ebad99047fffe0e3f645803f3ff8248 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Perception/Counting_of_Post-disaster_partially_damaged_building.json @@ -0,0 +1,10955 @@ +[ + { + "Question_id": "Counting of Post-disaster partially damaged building/0000", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0001", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0002", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0003", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0004", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0005", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0006", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0007", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)1", + "(B)2", + "(C)3", + "(D)4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0008", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0009", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0010", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0011", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0012", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0013", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 36", + "(B) 37", + "(C) 38", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0014", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0015", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 27", + "(B) 28", + "(C) 29", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0016", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0017", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0018", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0019", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0020", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0021", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0022", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0023", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0024", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0025", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0026", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0027", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0028", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0029", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0030", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0031", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 16", + "(B) 17", + "(C) 18", + "(D) 19", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0032", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0033", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0034", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0035", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 103", + "(B) 104", + "(C) 105", + "(D) 106", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0036", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0037", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0038", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0039", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0040", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0041", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0042", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0043", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0044", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0045", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0046", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0047", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0048", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0049", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0050", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0051", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0052", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 42", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0053", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0054", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0055", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0056", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0057", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0058", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 8", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0059", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 34", + "(B) 13", + "(C) 24", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0060", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 30", + "(B) 19", + "(C) 27", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0061", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0062", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0063", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0064", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 200", + "(B) 198", + "(C) 256", + "(D) 311", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0065", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0066", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 200", + "(B) 231", + "(C) 215", + "(D) 334", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0067", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 70", + "(B) 71", + "(C) 72", + "(D) 73", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0068", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 64", + "(B) 56", + "(C) 29", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0069", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0070", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0071", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0072", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0073", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0074", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0075", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0076", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0077", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0078", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 6", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0079", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0080", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0081", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0082", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0083", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0084", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0085", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0086", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0087", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0088", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 14", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0089", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0090", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0091", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0092", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0093", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0094", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0095", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0096", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 60", + "(B) 61", + "(C) 62", + "(D) 63", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000433_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000433_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0097", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0098", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0099", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0100", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0101", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 41", + "(B) 42", + "(C) 43", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0102", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0103", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0104", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0105", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0106", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 250", + "(B) 251", + "(C) 252", + "(D) 253", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0107", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0108", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 31", + "(B) 32", + "(C) 33", + "(D) 34", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0109", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0110", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0111", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0112", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0113", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0114", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0115", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0116", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0117", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0118", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0119", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0120", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0121", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0122", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0123", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0124", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0125", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0126", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0127", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0128", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0129", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0130", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0131", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0132", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0133", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0134", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0135", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 27", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0136", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0137", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 24", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0138", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0139", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0140", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 165", + "(B) 166", + "(C) 164", + "(D) 163", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0141", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0142", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0143", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 188", + "(B) 187", + "(C) 189", + "(D) 186", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0144", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0145", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 84", + "(B) 85", + "(C) 82", + "(D) 83", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0146", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 28", + "(B) 29", + "(C) 27", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0147", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 12", + "(C) 14", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0148", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0149", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0150", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0151", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0152", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0153", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0154", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0155", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0156", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0157", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0158", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0159", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0160", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0161", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0162", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0163", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0164", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0165", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0166", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0167", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0168", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0169", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0170", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0171", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0172", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0173", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 60", + "(B) 69", + "(C) 68", + "(D) 67", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0174", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 14", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0175", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0176", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0177", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0178", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0179", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0180", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0181", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0182", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0183", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0184", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0185", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0186", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0187", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 16", + "(B) 15", + "(C) 14", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0188", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0189", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0190", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0191", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0192", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0193", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0194", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0195", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0196", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0197", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0198", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0199", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0200", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 30", + "(B) 10", + "(C) 20", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0201", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 80", + "(B) 81", + "(C) 82", + "(D) 83", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0202", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0203", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0204", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 60", + "(B) 61", + "(C) 62", + "(D) 63", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0205", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0206", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 57", + "(B) 56", + "(C) 55", + "(D) 54", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0207", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0208", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0209", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0210", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0211", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0212", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0213", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0214", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0215", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0216", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0217", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0218", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0219", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0220", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0221", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0222", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0223", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0224", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0225", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0226", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 184", + "(B) 185", + "(C) 186", + "(D) 187", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0227", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0228", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0229", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0230", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0231", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0232", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0233", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0234", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 9", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0235", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0236", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0237", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0238", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0239", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0240", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0241", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0242", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0243", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0244", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0245", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 82", + "(B) 83", + "(C) 84", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0246", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0247", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 100", + "(B) 101", + "(C) 102", + "(D) 103", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0248", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 33", + "(B) 34", + "(C) 35", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0249", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0250", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0251", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0252", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0253", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 100", + "(B) 101", + "(C) 102", + "(D) 103", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0254", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0255", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0256", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0257", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0258", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 17", + "(B) 18", + "(C) 19", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0259", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0260", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0261", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0262", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0263", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0264", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0265", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 14", + "(B) 13", + "(C) 12", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0266", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0267", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0268", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0269", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0270", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0271", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0272", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0273", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0274", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0275", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0276", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0277", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0278", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0279", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 172", + "(B) 173", + "(C) 174", + "(D) 175", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0280", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 302", + "(B) 303", + "(C) 304", + "(D) 305", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0281", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 113", + "(B) 114", + "(C) 115", + "(D) 116", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0282", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 71", + "(B) 72", + "(C) 73", + "(D) 74", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_pre_disaster.png", + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0283", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0284", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0285", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0286", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0287", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 73", + "(B) 74", + "(C) 75", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0288", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0289", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0290", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0291", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0292", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0293", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0294", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0295", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0296", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0297", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000493_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000493_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0298", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0299", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0300", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0301", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0302", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0303", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0304", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0305", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0306", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0307", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0308", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 0", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0309", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0310", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0311", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0312", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 19", + "(C) 20", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0313", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0314", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 18", + "(B) 19", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0315", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 42", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0316", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0317", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0318", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 30", + "(B) 16", + "(C) 20", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0319", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0320", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0321", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0322", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0323", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0324", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0325", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0326", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 20", + "(C) 30", + "(D) 40", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0327", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0328", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0329", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0330", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0331", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0332", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0333", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 66", + "(B) 67", + "(C) 68", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0334", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0335", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0336", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0337", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0338", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0339", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0340", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0341", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0342", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0343", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0344", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0345", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0346", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0347", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0348", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0349", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0350", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0351", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0352", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0353", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0354", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0355", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0356", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0357", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0358", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0359", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0360", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0361", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0362", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0363", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0364", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 17", + "(C) 19", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0365", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0366", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0367", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0368", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0369", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000264_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0370", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0371", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0372", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0373", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0374", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0375", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0376", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0377", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0378", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0379", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0380", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0381", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0382", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0383", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0384", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0385", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0386", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0387", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 52", + "(B) 53", + "(C) 54", + "(D) 55", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0388", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0389", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 12", + "(B) 13", + "(C) 14", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0390", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0391", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0392", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0393", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0394", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0395", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0396", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0397", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0398", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0399", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0400", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0401", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0402", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0403", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0404", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0405", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0406", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0407", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0408", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0409", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0410", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0411", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0412", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0413", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0414", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0415", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0416", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0417", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0418", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0419", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0420", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0421", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0422", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 22", + "(B) 23", + "(C) 24", + "(D) 25", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0423", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0424", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0425", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0426", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0427", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0428", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0429", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0430", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 0", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0431", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0432", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0433", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0434", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0435", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0436", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0437", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0438", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0439", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0440", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0441", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0442", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0443", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0444", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 8", + "(B) 0", + "(C) 5", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0445", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0446", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0447", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0448", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0449", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0450", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0451", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0452", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0453", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0454", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0455", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0456", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0457", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0458", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged,moderate damaged buildings and major damaged are there in thepicture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0459", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0460", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0461", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0462", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0463", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0464", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0465", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0466", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0467", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0468", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0469", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0470", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0471", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0472", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0473", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged,moderate damaged buildings and major damaged are there in thepicture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0474", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0475", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0476", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0477", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0478", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0479", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0480", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0481", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0482", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0483", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0484", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0485", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0486", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0487", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 17", + "(B) 18", + "(C) 19", + "(D) 20", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0488", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 5", + "(B) 0", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0489", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0490", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0491", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0492", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0493", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0494", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0495", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0496", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and moderate damaged buildings are there in the picture?not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_post_disaster.png" + ] + }, + { + "Question_id": "Counting of Post-disaster partially damaged building/0497", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.How many minor damaged and major damaged buildings are there in the picture? not include no-demagedbuildings or destroyed buildings.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Perception", + "L4-task": "Counting of Post-disaster partially damaged building", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_post_disaster.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Building_damage_prediction.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Building_damage_prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..46b196f3ff309913e3b89302f722641b99c1427c --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Building_damage_prediction.json @@ -0,0 +1,10486 @@ +[ + { + "Question_id": "Building damage prediction/0000", + "Question Type": "Single Choice", + "Text": "Given pre disaster images,predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0001", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0002", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0003", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0004", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0005", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0006", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0007", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0008", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0009", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0010", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0011", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0012", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0013", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0014", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0015", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0016", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0017", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0018", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0019", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0020", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0021", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0022", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 36", + "(B) 37", + "(C) 38", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0023", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0024", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 26", + "(B) 27", + "(C) 28", + "(D) 29", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0025", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0026", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0027", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0028", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0029", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 12", + "(B) 13", + "(C) 14", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0030", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0031", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0032", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0033", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0034", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0035", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0036", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0037", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0038", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0039", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 16", + "(B) 17", + "(C) 18", + "(D) 19", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0040", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0041", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0042", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0043", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 104", + "(B) 105", + "(C) 106", + "(D) 107", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0044", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0045", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0046", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0047", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0048", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0049", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0050", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0051", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0052", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0053", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0054", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0055", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0056", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0057", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0058", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0059", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0060", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 44", + "(B) 45", + "(C) 46", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0061", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0062", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0063", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0064", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 39", + "(B) 40", + "(C) 41", + "(D) 42", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0065", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0066", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0067", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0068", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 40", + "(B) 18", + "(C) 22", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0069", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 20", + "(B) 18", + "(C) 27", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0070", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0071", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0072", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 12", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0073", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 345", + "(B) 199", + "(C) 256", + "(D) 257", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0074", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0075", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 120", + "(B) 231", + "(C) 218", + "(D) 243", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0076", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 200", + "(B) 128", + "(C) 212", + "(D) 312", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0077", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 67", + "(B) 57", + "(C) 76", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0078", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0079", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0080", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0081", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0082", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0083", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0084", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 9", + "(C)10", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0085", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0086", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0087", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 9", + "(B) 10", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0088", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 0", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0089", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0090", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0091", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0092", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0093", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0094", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0095", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0096", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 14", + "(B) 15", + "(C) 16", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0097", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 15", + "(B) 14", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0098", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0099", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0100", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0101", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0102", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0103", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0104", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0105", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0106", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0107", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0108", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 41", + "(B) 42", + "(C) 43", + "(D) 44", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0109", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0110", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0111", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0112", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0113", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 250", + "(B) 251", + "(C) 252", + "(D) 253", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0114", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0115", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 31", + "(B) 32", + "(C) 33", + "(D) 34", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0116", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0117", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0118", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0119", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0120", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0121", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0122", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0123", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0124", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0125", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0126", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0127", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0128", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0129", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0130", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0131", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0132", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0133", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0134", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0135", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0136", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0137", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0138", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0139", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0140", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0141", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0142", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0143", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0144", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0145", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0146", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0147", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 166", + "(B) 165", + "(C) 167", + "(D) 164", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0148", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0149", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0150", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 186", + "(B) 189", + "(C) 188", + "(D) 187", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0151", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0152", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 87", + "(B) 84", + "(C) 85", + "(D) 86", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0153", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0154", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 16", + "(B) 15", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0155", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0156", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0157", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0158", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0159", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0160", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0161", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0162", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0163", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0164", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0165", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0166", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0167", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0168", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0169", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0170", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0171", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0172", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0173", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0174", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0175", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0176", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0177", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0178", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 65", + "(B) 66", + "(C) 68", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0179", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 13", + "(B) 14", + "(C) 12", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0180", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A)0", + "(B)1", + "(C)2", + "(D)3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0181", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0182", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0183", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0184", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0185", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0186", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0187", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0188", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0189", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0190", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0191", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0192", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 23", + "(B) 21", + "(C) 22", + "(D) 31", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0193", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0194", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 12", + "(C) 14", + "(D) 16", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0195", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 6", + "(C) 5", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0196", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0197", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0198", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0199", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0200", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0201", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0202", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0203", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0204", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0205", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0206", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0207", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 27", + "(B) 28", + "(C) 29", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0208", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 57", + "(B) 56", + "(C) 55", + "(D) 54", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0209", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0210", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0211", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0212", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0213", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0214", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0215", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0216", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0217", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0218", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0219", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0220", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0221", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0222", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0223", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0224", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0225", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0226", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0227", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0228", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 200", + "(B) 201", + "(C) 202", + "(D) 203", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0229", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0230", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0231", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 36", + "(B) 37", + "(C) 38", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0232", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0233", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0234", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0235", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0236", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0237", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0238", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0239", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0240", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0241", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 14", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0242", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0243", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 263", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0244", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0245", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 16", + "(C) 18", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0246", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0247", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 82", + "(B) 83", + "(C) 84", + "(D) 85", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0248", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 35", + "(B) 36", + "(C) 37", + "(D) 38", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0249", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 100", + "(B) 101", + "(C) 102", + "(D) 103", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0250", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 33", + "(B) 34", + "(C) 35", + "(D) 36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0251", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0252", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0253", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0254", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0255", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000189_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0256", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 100", + "(B) 101", + "(C) 102", + "(D) 103", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0257", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0258", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0259", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0260", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0261", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0262", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0263", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0264", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0265", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0266", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0267", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0268", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0269", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0270", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0271", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0272", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0273", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 10", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0274", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0275", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0276", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0277", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000049_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0278", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0279", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0280", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 11", + "(B) 12", + "(C) 13", + "(D) 14", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0281", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 171", + "(B) 172", + "(C) 173", + "(D) 174", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0282", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 302", + "(B) 303", + "(C) 304", + "(D) 305", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0283", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 113", + "(B) 114", + "(C) 115", + "(D) 116", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0284", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 71", + "(B) 72", + "(C) 73", + "(D) 74", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0285", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 14", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0286", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0287", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0288", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0289", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 73", + "(B) 74", + "(C) 75", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0290", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0291", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0292", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0293", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0294", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0295", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0296", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0297", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0298", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0299", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000484_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0300", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0301", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0302", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0303", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0304", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0305", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0306", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0307", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0308", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0309", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0310", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0311", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0312", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0313", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0314", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 19", + "(B) 18", + "(C) 21", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0315", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0316", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 40", + "(B) 41", + "(C) 42", + "(D) 43", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0317", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 4", + "(C) 6", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0318", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 23", + "(B) 18", + "(C) 20", + "(D) 32", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0319", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0320", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0321", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 6", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0322", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0323", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0324", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0325", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0326", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 20", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0327", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0328", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0329", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0330", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0331", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0332", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0333", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0334", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 66", + "(B) 67", + "(C) 68", + "(D) 69", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0335", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0336", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0337", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0338", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0339", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0340", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0341", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 20", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0342", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 8", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0343", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0344", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0345", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0346", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0347", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0348", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0349", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0350", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0351", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0352", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0353", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0354", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0355", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0356", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0357", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0358", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0359", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0360", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0361", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0362", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0363", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0364", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0365", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0366", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_post_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0367", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0368", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0369", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0370", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0371", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0372", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0373", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0374", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0375", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0376", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0377", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0378", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0379", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0380", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0381", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0382", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0383", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0384", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0385", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 54", + "(B) 55", + "(C) 56", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0386", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 27", + "(B) 28", + "(C) 29", + "(D) 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0387", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 14", + "(B) 15", + "(C) 16", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0388", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0389", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0390", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0391", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0392", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0393", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0394", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0395", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0396", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0397", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0398", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0399", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0400", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0401", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0402", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0403", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0404", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0405", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0406", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0407", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0408", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0409", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0410", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0411", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0412", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0413", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0414", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0415", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0416", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 21", + "(B) 22", + "(C) 23", + "(D) 24", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0417", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0418", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0419", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0420", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 23", + "(B) 24", + "(C) 25", + "(D) 26", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0421", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0422", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0423", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0424", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0425", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0426", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0427", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0428", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0429", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0430", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0431", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0432", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0433", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0434", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0435", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0436", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0437", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0438", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0439", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 11", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0440", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0441", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0442", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0443", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0444", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 7", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0445", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0446", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0447", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0448", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0449", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0450", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0451", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0452", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Major damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0453", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 8", + "(B) 7", + "(C) 6", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0454", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0455", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0456", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0457", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0458", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0459", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0460", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0461", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0462", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0463", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0464", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0465", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 12", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0466", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0467", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0468", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0469", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 19", + "(B) 17", + "(C) 21", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0470", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 14", + "(C) 20", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0471", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0472", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0473", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0474", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0475", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0476", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0477", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0478", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0479", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0480", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0481", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0482", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0483", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0484", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 18", + "(B) 19", + "(C) 20", + "(D) 21", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0485", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0486", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0487", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0488", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0489", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0490", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0491", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0492", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0493", + "Question Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged,Moderate damaged,and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_pre_disaster.png" + ] + }, + { + "Question_id": "Building damage prediction/0494", + "Question_Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000528_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Building damage prediction/0495", + "Question_Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000535_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Building damage prediction/0496", + "Question_Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 5", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000536_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Building damage prediction/0497", + "Question_Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 5", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000538_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Building damage prediction/0498", + "Question_Type": "Single Choice", + "Text": "Given pre disaster images, predict how many buildings are likely tobe damaged in the event of a disaster? (including Minor damaged, Major damaged, and Fully destroyed)", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Building damage prediction", + "Answer Choices": [ + "(A) 1", + "(B) 3", + "(C) 5", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000539_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_prediction.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_prediction.json new file mode 100644 index 0000000000000000000000000000000000000000..d877e7c7d941910726a33d58726cd4d72146d935 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_prediction.json @@ -0,0 +1,10502 @@ +[ + { + "Question_id": "Dissaster prediction/0000", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0001", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcano", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0002", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0003", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0004", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0005", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0006", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0007", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0008", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0009", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0010", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0011", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0012", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0013", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcano", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0014", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0015", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0016", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0017", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0018", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0019", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0020", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0021", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0022", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0023", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0024", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0025", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0026", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0027", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0028", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0029", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0030", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0031", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0032", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0033", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0034", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0035", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0036", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0037", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0038", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0039", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0040", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0041", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0042", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0043", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0044", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0045", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0046", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0047", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0048", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0049", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0050", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0051", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0052", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0053", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0054", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0055", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0056", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0057", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0058", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0059", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0060", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0061", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0062", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0063", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0064", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0065", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0066", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0067", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0068", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0069", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0070", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0071", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0072", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0073", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0074", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0075", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0076", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0077", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0078", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0079", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0080", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0081", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0082", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0083", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0084", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0085", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0086", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0087", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0088", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0089", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0090", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0091", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0092", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) harvey", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0093", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0094", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0095", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0096", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0097", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000433_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0098", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0099", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0100", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0101", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0102", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0103", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0104", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0105", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D)hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0106", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0107", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0108", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0109", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0110", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0111", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0112", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0113", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0114", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0115", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0116", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0117", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0118", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0119", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0120", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0121", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0122", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0123", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0124", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0125", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0126", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0127", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0128", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0129", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0130", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0131", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0132", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0133", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0134", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0135", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0136", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0137", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0138", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0139", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0140", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0141", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0142", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0143", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0144", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0145", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) harvey", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0146", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0147", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0148", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0149", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0150", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0151", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0152", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0153", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0154", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0155", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000064_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0156", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0157", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0158", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0159", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0160", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0161", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0162", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0163", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0164", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0165", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0166", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0167", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0168", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0169", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0170", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0171", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0172", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0173", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0174", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0175", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0176", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0177", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0178", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0179", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0180", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0181", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0182", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0183", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0184", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0185", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0186", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0187", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0188", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0189", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0190", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0191", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0192", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0193", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0194", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0195", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0196", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0197", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0198", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0199", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0200", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0201", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0202", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0203", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0204", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0205", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000333_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0206", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0207", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0208", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0209", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0210", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0211", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0212", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0213", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0214", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0215", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0216", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0217", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0218", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0219", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0220", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0221", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0222", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0223", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0224", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0225", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0226", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0227", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0228", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0229", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0230", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0231", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0232", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0233", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0234", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0235", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0236", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0237", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0238", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0239", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0240", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0241", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0242", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0243", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0244", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0245", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0246", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0247", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0248", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0249", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0250", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0251", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0252", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0253", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000189_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0254", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0255", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0256", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0257", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0258", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0259", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0260", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0261", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0262", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0263", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0264", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0265", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0266", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0267", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0268", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0269", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0270", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0271", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0272", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0273", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0274", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0275", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0276", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0277", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000049_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0278", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0279", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0280", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0281", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0282", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane-", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0283", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0284", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0285", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0286", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0287", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0288", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0289", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0290", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0291", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0292", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0293", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0294", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0295", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0296", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0297", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0298", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0299", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000484_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0300", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0301", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0302", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0303", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0304", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0305", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0306", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0307", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0308", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0309", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0310", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0311", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0312", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0313", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0314", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0315", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0316", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0317", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0318", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0319", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0320", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0321", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0322", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0323", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0324", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0325", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0326", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0327", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0328", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0329", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0330", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0331", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0332", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0333", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0334", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0335", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0336", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) florence", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0337", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0338", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0339", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0340", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0341", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0342", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0343", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0344", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0345", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0346", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0347", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0348", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0349", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0350", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0351", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0352", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0353", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0354", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0355", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0356", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0357", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000390_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0358", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0359", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0360", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0361", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0362", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0363", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0364", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0365", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0366", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0367", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0368", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0369", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0370", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0371", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0372", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0373", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0374", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0375", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0376", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0377", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0378", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0379", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0380", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0381", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0382", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0383", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0384", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0385", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0386", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0387", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0388", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0389", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0390", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0391", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0392", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0393", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0394", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0395", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0396", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0397", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0398", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0399", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0400", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0401", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0402", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0403", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurrican", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0404", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0405", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0406", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0407", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0408", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0409", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0410", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0411", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0412", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0413", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0414", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0415", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricaner", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0416", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0417", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0418", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0419", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) florence", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0420", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0421", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0422", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0423", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0424", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0425", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0426", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0427", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0428", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0429", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0430", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0431", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0432", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0433", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0434", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0435", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0436", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0437", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0438", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0439", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0440", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0441", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0442", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0443", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurrican", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0444", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0445", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0446", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0447", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0448", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0449", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0450", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0451", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0452", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0453", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0454", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0455", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0456", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0457", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0458", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0459", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0460", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0461", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0462", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0463", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0464", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0465", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0466", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0467", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0468", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0469", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0470", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0471", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0472", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0473", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0474", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0475", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0476", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0477", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0478", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0479", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0480", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0481", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0482", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0483", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0484", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0485", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0486", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0487", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0488", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0489", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0490", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0491", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0492", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0493", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0494", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0495", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) volcanic eruption", + "(C) hurricane", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0496", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) hurricane", + "(B) volcanic eruption", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0497", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0498", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster prediction/0499", + "Question Type": "Single Choice", + "Text": "This is a picture before the disaster. Please predict what kind ofdisaster will happen?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster prediction", + "Answer Choices": [ + "(A) torrential flood", + "(B) hurricane", + "(C) Wildfire", + "(D) man-made disaster", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_pre_disaster.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_type_classification.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_type_classification.json new file mode 100644 index 0000000000000000000000000000000000000000..19da0fee8b249481b5e14ff31edcf9e38257e1da --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Dissaster_type_classification.json @@ -0,0 +1,10502 @@ +[ + { + "Question_id": "Dissaster type classification/0000", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0001", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0002", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0003", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0004", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0005", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0006", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0007", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0008", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0009", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0010", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcano", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0011", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0012", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0013", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0014", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0015", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0016", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0017", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0018", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0019", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0020", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0021", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0022", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0023", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0024", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0025", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0026", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0027", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0028", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0029", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0030", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0031", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0032", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0033", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0034", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0035", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0036", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0037", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0038", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0039", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0040", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0041", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0042", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0043", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0044", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0045", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0046", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0047", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0048", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0049", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0050", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0051", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0052", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0053", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0054", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0055", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0056", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0057", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0058", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0059", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0060", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0061", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0062", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0063", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0064", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) Harvey", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0065", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0066", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0067", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0068", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0069", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0070", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0071", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0072", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0073", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0074", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0075", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0076", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0077", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0078", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0079", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0080", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0081", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0082", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0083", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0084", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0085", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0086", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0087", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcano", + "(B)earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0088", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) earthquake", + "(B) volcano", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0089", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B)earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0090", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0091", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0092", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0093", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0094", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0095", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0096", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0097", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0098", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0099", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0100", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0101", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0102", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0103", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0104", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0105", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0106", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0107", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0108", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0109", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000065_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0110", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0111", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0112", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0113", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcano", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0114", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0115", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0116", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0117", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0118", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0119", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0120", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0121", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0122", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0123", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0124", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0125", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0126", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0127", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000371_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0128", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0129", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000407_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0130", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0131", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000490_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0132", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0133", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0134", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0135", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0136", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0137", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0138", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0139", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0140", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0141", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0142", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0143", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0144", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0145", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0146", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0147", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0148", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0149", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0150", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000083_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0151", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0152", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0153", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0154", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0155", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0156", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000178_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0157", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0158", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0159", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0160", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0161", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0162", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0163", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0164", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0165", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0166", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0167", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0168", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0169", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0170", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0171", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0172", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0173", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0174", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0175", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0176", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0177", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0178", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0179", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0180", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0181", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0182", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0183", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0184", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0185", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0186", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0187", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0188", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0189", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0190", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0191", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0192", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0193", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0194", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0195", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0196", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0197", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0198", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0199", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0200", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0201", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000327_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0202", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0203", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0204", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0205", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0206", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0207", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0208", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0209", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0210", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0211", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0212", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0213", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0214", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0215", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0216", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0217", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0218", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0219", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0220", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0221", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0222", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0223", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0224", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0225", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0226", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0227", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0228", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0229", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0230", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000116_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0231", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0232", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0233", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0234", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000172_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0235", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0236", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000222_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0237", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0238", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0239", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0240", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0241", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0242", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0243", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0244", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0245", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0246", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0247", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0248", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0249", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0250", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0251", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0252", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0253", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0254", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0255", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0256", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0257", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0258", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0259", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0260", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000009_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0261", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0262", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0263", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0264", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0265", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0266", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0267", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0268", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0269", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0270", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0271", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0272", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0273", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0274", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0275", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0276", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0277", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0278", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0279", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0280", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0281", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0282", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0283", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0284", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0285", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0286", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0287", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0288", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0289", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0290", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0291", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0292", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0293", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0294", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0295", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000493_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0296", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0297", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0298", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0299", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0300", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0301", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0302", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0303", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0304", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurrican", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0305", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0306", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0307", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0308", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0309", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0310", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0311", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0312", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0313", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0314", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0315", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0316", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0317", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000504_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0318", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0319", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0320", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0321", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0322", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0323", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0324", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0325", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0326", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0327", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0328", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0329", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0330", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0331", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0332", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0333", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0334", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0335", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0336", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0337", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0338", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0339", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0340", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0341", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0342", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0343", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0344", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0345", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0346", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0347", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0348", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0349", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0350", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0351", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0352", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0353", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0354", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0355", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0356", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0357", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0358", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0359", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0360", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0361", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0362", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000410_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0363", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0364", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0365", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000313_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0366", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0367", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000264_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0368", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0369", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0370", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0371", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0372", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0373", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0374", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0375", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0376", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0377", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0378", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0379", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0380", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0381", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0382", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0383", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0384", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0385", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0386", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0387", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0388", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0389", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0390", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0391", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0392", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0393", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0394", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0395", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0396", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0397", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0398", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0399", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0400", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0401", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0402", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0403", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0404", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0405", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0406", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0407", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0408", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0409", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0410", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0411", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0412", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0413", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0414", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0415", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0416", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0417", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0418", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0419", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0420", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0421", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0422", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0423", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0424", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0425", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0426", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0427", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0428", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0429", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0430", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0431", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0432", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0433", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0434", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0435", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0436", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0437", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0438", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0439", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0440", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0441", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0442", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000153_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0443", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0444", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0445", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0446", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0447", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0448", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0449", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0450", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0451", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0452", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0453", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0454", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0455", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0456", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0457", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0458", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0459", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0460", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0461", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0462", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0463", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0464", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0465", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000106_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0466", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0467", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0468", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0469", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0470", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0471", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0472", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0473", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000094_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0474", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0475", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0476", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0477", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0478", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0479", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0480", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0481", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0482", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0483", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) flood", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0484", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0485", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0486", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0487", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0488", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0489", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0490", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0491", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0492", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite impact show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) hurricane", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0493", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) hurricane", + "(B) earthquake", + "(C) flood", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0494", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0495", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0496", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0497", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0498", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Dissaster type classification/0499", + "Question Type": "Single Choice", + "Text": "What natural disasters did this satellite image show in the area?", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Dissaster type classification", + "Answer Choices": [ + "(A) volcanic eruption", + "(B) earthquake", + "(C) hurricane", + "(D) wildfire", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_post_disaster.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Geolocation_estimation_of_disaster-affected_regions_from_imagery.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Geolocation_estimation_of_disaster-affected_regions_from_imagery.json new file mode 100644 index 0000000000000000000000000000000000000000..9f4894d2451f1a842160c01eb96f501ece3acfac --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Geolocation_estimation_of_disaster-affected_regions_from_imagery.json @@ -0,0 +1,10827 @@ +[ + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0000", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000010_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0001", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0002", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000020_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0003", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) hurricane-florece", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0004", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0005", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000036_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0006", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000055_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0007", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0008", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0009", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0010", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0011", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0012", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0013", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0014", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0015", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0016", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0017", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0018", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0019", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0020", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0021", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000018_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0022", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000019_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0023", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0024", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0025", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000255_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0026", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0027", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000271_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0028", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000284_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0029", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000235_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0030", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000258_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0031", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000270_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0032", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000278_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0033", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000316_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0034", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000332_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0035", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000329_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0036", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000030_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0037", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000300_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0038", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000404_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0039", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000409_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0040", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000315_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0041", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000319_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0042", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000022_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0043", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000047_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0044", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000061_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0045", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000076_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0046", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000085_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0047", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000101_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0048", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000111_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0049", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000119_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0050", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000129_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0051", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000141_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0052", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000180_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0053", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000194_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0054", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000200_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0055", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000212_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0056", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000220_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0057", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000231_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0058", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000216_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0059", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000221_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0060", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000228_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0061", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000233_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0062", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000237_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0063", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000241_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0064", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000248_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0065", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000257_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0066", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000266_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0067", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000277_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0068", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000289_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0069", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000312_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0070", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000325_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0071", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000006_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0072", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000029_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0073", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000051_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0074", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000070_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0075", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000077_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0076", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000089_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0077", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000100_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0078", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000146_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0079", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000159_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0080", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000177_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0081", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000195_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0082", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000204_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0083", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000213_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0084", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000218_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0085", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000226_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0086", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000232_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0087", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000244_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0088", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000267_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0089", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000275_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0090", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000288_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0091", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000309_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0092", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0093", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000015_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0094", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000323_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0095", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000245_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0096", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000249_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0097", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000261_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0098", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000264_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0099", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Hurricane", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000269_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0100", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000274_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0101", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000280_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0102", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000291_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0103", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0104", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000006_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0105", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0106", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000292_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0107", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000307_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0108", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0109", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000302_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0110", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000317_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0111", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000243_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0112", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000196_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0113", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000203_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0114", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000210_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0115", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000137_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0116", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0117", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0118", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000157_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0119", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0120", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0121", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000049_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0122", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000063_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0123", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0124", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0125", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000002_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0126", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0127", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000103_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0128", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000122_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0129", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0130", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000163_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0131", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000245_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0132", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000263_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0133", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000274_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0134", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000282_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0135", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000304_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0136", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000314_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0137", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000328_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0138", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0139", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0140", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000398_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0141", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0142", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000026_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0143", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000178_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0144", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000174_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0145", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000171_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0146", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000168_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0147", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000158_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0148", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000153_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0149", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000145_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0150", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000098_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0151", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000088_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0152", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000081_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0153", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000071_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0154", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000059_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0155", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000055_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0156", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000048_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0157", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000075_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0158", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0159", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000102_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0160", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0161", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000123_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0162", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0163", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000231_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0164", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000232_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0165", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000244_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0166", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000252_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0167", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000260_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0168", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000275_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0169", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000279_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0170", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000284_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0171", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000297_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0172", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000300_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0173", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000306_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0174", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000040_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0175", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000001_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0176", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000012_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0177", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000238_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0178", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000242_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0179", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000349_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0180", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000350_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0181", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000355_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0182", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000388_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0183", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000394_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0184", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000399_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0185", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000406_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0186", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000414_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0187", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000436_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0188", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000438_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0189", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000443_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0190", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000449_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0191", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000460_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0192", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000467_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0193", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000472_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0194", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000510_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0195", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000515_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0196", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000522_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0197", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000527_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0198", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000533_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0199", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000538_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0200", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000545_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0201", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0202", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000205_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0203", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000239_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0204", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000333_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0205", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000494_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0206", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000508_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0207", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000526_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0208", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000537_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0209", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000002_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0210", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000008_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0211", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000012_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0212", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000016_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0213", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000019_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0214", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000523_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0215", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000024_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0216", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000025_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0217", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0218", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0219", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0220", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0221", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000079_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0222", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0223", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0224", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000099_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0225", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000108_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0226", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000113_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0227", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000115_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0228", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000126_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0229", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0230", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0231", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000066_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0232", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0233", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0234", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0235", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000206_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0236", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0237", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000041_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0238", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000134_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0239", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000152_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0240", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000123_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0241", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) hurricane", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000138_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0242", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000147_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0243", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000154_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0244", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000160_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0245", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000170_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0246", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000176_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0247", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000187_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0248", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000197_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0249", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000207_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0250", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000393_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0251", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000416_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0252", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000446_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0253", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0254", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0255", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0256", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000531_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0257", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0258", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000057_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0259", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000107_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0260", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000136_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0261", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Harvey", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000169_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0262", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000054_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0263", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000080_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0264", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000128_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0265", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000156_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0266", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000268_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0267", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000285_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0268", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000299_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0269", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000039_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0270", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000060_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0271", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000075_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0272", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000082_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0273", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000092_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0274", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000104_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0275", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000109_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0276", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000114_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0277", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0278", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) harvey", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000042_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0279", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000529_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0280", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000540_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0281", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) hurricane", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000001_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0282", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000007_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0283", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000015_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0284", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) harvey", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000017_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0285", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) harvey", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000020_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0286", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000445_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0287", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000469_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0288", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000474_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0289", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000477_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0290", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0291", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000497_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0292", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000500_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0293", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000503_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0294", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000512_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0295", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000516_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0296", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000302_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0297", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000319_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0298", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000331_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0299", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000338_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0300", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000345_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0301", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000357_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0302", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florebce", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000361_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0303", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000372_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0304", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000379_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0305", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000382_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0306", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000401_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0307", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0308", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000411_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0309", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000464_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0310", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000478_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0311", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000498_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0312", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000514_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0313", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000536_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0314", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000506_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0315", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000513_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0316", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000517_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0317", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000392_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0318", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000395_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0319", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0320", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0321", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0322", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0323", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0324", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000476_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0325", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000482_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0326", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000485_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0327", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000496_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0328", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000424_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0329", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000426_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0330", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000437_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0331", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000441_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0332", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000457_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0333", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0334", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000453_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0335", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000451_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0336", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000450_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0337", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000442_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0338", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0339", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000431_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0340", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000341_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0341", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000353_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0342", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000359_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0343", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000362_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0344", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000368_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0345", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000370_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0346", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000376_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0347", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000380_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0348", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000387_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0349", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000397_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0350", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000405_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0351", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000408_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0352", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000419_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0353", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000425_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0354", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000423_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0355", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000185_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0356", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0357", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000356_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0358", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000329_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0359", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0360", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000272_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0361", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/guatemala-volcano_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0362", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000247_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0363", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000273_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0364", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000285_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0365", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000316_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0366", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000330_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0367", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000336_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0368", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000303_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0369", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000360_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0370", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000366_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0371", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000369_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0372", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000374_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0373", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000381_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0374", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000389_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0375", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000403_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0376", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000420_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0377", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000427_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0378", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000444_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0379", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000459_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0380", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000475_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0381", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000481_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0382", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000233_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0383", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000251_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0384", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0385", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0386", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000293_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0387", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000298_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0388", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000308_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0389", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000312_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0390", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000315_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0391", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000320_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0392", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000325_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0393", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000333_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0394", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000337_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0395", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000340_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0396", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0397", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000259_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0398", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000290_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0399", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0400", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0401", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0402", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000334_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0403", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000324_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0404", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000309_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0405", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000296_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0406", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000277_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0407", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000256_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0408", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000237_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0409", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000224_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0410", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000216_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0411", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000212_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0412", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000199_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0413", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000088_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0414", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000120_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0415", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000156_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0416", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000188_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0417", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000189_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0418", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000191_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0419", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000193_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0420", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000195_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0421", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000140_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0422", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0423", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000242_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0424", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000255_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0425", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000269_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0426", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000289_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0427", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000229_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0428", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000164_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0429", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0430", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000217_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0431", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000219_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0432", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000226_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0433", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0434", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000180_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0435", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000158_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0436", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000045_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0437", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0438", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000149_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0439", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000148_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0440", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0441", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000136_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0442", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000144_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0443", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000166_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0444", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0445", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000192_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0446", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000069_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0447", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000080_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0448", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000096_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0449", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000104_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0450", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000111_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0451", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000138_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0452", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0453", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000132_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0454", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000139_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0455", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000091_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0456", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000114_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0457", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000110_pre_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0458", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000101_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0459", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0460", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000070_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0461", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000085_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0462", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) hurricane", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000100_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0463", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000086_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0464", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0465", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000084_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0466", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000078_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0467", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000073_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0468", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000067_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0469", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000061_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0470", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000062_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0471", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000060_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0472", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) Switzerland", + "(C) florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000059_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0473", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000054_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0474", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000048_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0475", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) Florence", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0476", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000053_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0477", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000043_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0478", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala-volcano", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000022_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0479", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000027_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0480", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000028_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0481", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000030_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0482", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) Switzerland", + "(C) New Zealand", + "(D) Florence", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000023_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0483", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000032_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0484", + "Question Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) guatemala", + "(B) florence", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000031_post_disaster.png" + ] + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0485", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florence", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000486_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0486", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florida", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000540_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0487", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florida", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000540_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0488", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florida", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000541_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0489", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Florida", + "(B) Switzerland", + "(C) New Zealand", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000541_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0490", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000542_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0491", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000542_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0492", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000543_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0493", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000543_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0494", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000546_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0495", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Florida", + "(D) Bermuda Triangle", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000546_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0496", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000547_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0497", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000547_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0498", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000548_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0499", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000548_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0500", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000549_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Geolocation estimation of disaster-affected regions fromimagery/0501", + "Question_Type": "Single Choice", + "Text": "Please identify the location of the disaster based on the image.", + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Geolocation estimation of disaster-affected regions from imagery", + "Answer Choices": [ + "(A) Tokyo", + "(B) Switzerland", + "(C) Firenze", + "(D) Florida", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000549_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Individual_building_damage_assessment.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Individual_building_damage_assessment.json new file mode 100644 index 0000000000000000000000000000000000000000..9a734fa72d85057e7a576f6ee17747d47346f7e4 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Individual_building_damage_assessment.json @@ -0,0 +1,3212 @@ +[ + { + "Question_id": "Individual building damage assessment/0000", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located on theleft side of the river, in an L-shape", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 13undamaged buildings and 5 minor-damage buildings.", + "Step 2: There are 5 buildings located on the left side of the river.", + "Step 3: This is a building is an L-shaped structure on the left side of theriver.", + "Step 4: Bounding Box -[<369><138><432><228>] is the described building.", + "Step 5: Bounding Box -[<369><138><432><228>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<369><138><432><228>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000344_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0001", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. escription:This building is located in theupper left corner of the picture and has a triangular roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 88major-damage buildings and 7 destroyed buildings and 5 unclassifiedbuildings.", + "Step 2: This building is located in the upper left corner of the picture.", + "Step 3: This building has a triangular green roof", + "Step 4: Bounding Box -[<0><121><17><155>] is the described building.", + "Step 5: Bounding Box -[<0><121><17><155>] roof and walls have obvious cracks.", + "Step 6: Bounding Box -[<0><121><17><155>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000361_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0002", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located betweentwo roads, with a rectangular white roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 139major-damage buildings and 10 destroyed buildings.", + "Step 2: There are some buildings located in the bottom right corner of thepicture.", + "Step 3: There is a building has a rectangular white roof in the bottom rightcorner of the picture,above it is a road.", + "Step 4: Bounding Box -[<835><606><872><686>] is the described building.", + "Step 5: Bounding Box -[<835><606><872><686>] have obvious cracks on the walls and roof.", + "Step 6: Bounding Box -[<835><606><872><686>] is major-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000365_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0003", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located at the topright of the picture, with a green square shaped roof surrounded byvegetation.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 156undamaged buildings.", + "Step 2: There are some buildings located at the top right of the image.", + "Step 3: There is a building has a square green roof surrounded byvegetation", + "Step 4: Bounding Box -[<956><8><994><54>] is the described building.", + "Step 5: Bounding Box -[<956><8><994><54>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<956><8><994><54>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000366_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0004", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the highway and is L-shaped.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 79undamaged buildings.", + "Step 2: There are 6 buildings located in the upper right corner of theentire picture and is rectangular in shape.", + "Step 3: This building with an L-shaped green roof and green plants below.", + "Step 4: Bounding Box -[<938><0><1024><228>] is the described building.", + "Step 5: Bounding Box -[<938><0><1024><228>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<938><0><1024><228>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000367_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0005", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thecenter of the picture, the smallest white roofed building on the green beltbetween two roads.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 134undamaged buildings.", + "Step 2: There are some buildings located in the center of the picture,it have the smallest square white roofed building.", + "Step 3: There is a building is the smallest white roofed structure located onthe green belt between two roads.", + "Step 4: Bounding Box -[<402><400><412><418>] is the described building.", + "Step 5: Bounding Box -[<402><400><412><418>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<402><400><412><418>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000379_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0006", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located above theparking lot and has a conical shape. Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 63undamaged buildings.", + "Step 2:There are are some buildings located in the upper left corner of thepicture.", + "Step 3: There is a building located above the parking lot, it has a greenconical roof.", + "Step 4: Bounding Box -[<0><383><79><473>] is the described building.", + "Step 5: Bounding Box -[<0><383><79><473>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<0><383><79><473>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000396_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0007", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located beneaththe road and is rectangular in shape. It is the largest building in the entirepicture. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 41undamaged buildings.", + "Step 2: There are 15 buildings located in the upper right corner of thepicture.", + "Step 3: There is a building in this area located at the lower right corner ofthe crossroads, on a sparse meadow.", + "Step 4: Bounding Box -[<697><207><787><322>] is the described building.", + "Step 5: Bounding Box -[<697><207><787><322>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<697><207><787><322>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000374_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0008", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located above theroad, rectangular in shape, this building is the smallest building. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 104undamaged buildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: There is a building located above the road, it is the smallestrectangular building.", + "Step 4: Bounding Box -[<195><152><213><202>] is the described building.", + "Step 5: Bounding Box -[<195><152><213><202>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<195><152><213><202>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000413_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0009", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the image and is in the shape of an inverted U. The building isthe widest in the entire image, with a river adjacent to it below. Pleaseassess the damage to the building.", + "CoT": [ + "Step 1: An image is a photo taken after a disaster. There are 1 undamaged and1 unclassified and 186 severely damaged and 7 completely damaged.", + "Step 2:There's a river in the bottom left corner of the picture, and there'sa building above the river.", + "Step 3: There is a building in this area, located above the river channel,which is an inverted U-shaped building.", + "Step 4: Bounding Box -[<1><452><120><590>] is the described building.", + "Step 5: Bounding box -[<1><452><120><590>] does not have a full roof and upright walls, and hasmore gaps.", + "Step 6: Bounding Box -[<1><452><120><590>] is major-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000434_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0010", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower left corner of the road in a V-shape. The building is the most remote inthe whole map and is connected to the road by a small road. Please assess thedamage to this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 137major-damage and 21 minor-damage.", + "Step 2: There is a road on the left side of the picture, and there is aV-shaped building on the bottom of the left side of the road.", + "Step 3: There is a building in this area on the left side of the intersectionwith no other buildings around.", + "Step 4: Bounding Box -[<0><861><50><926>] is the described building.", + "Step 5: Bounding box -[<0><861><50><926>] has a less complete roof and less upright walls with alittle gap.", + "Step 6: Bounding Box -[<0><861><50><926>] is minor-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000435_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0011", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the entire picture. This building has a white roof andthere is a parking lot on its left.Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 87undamaged buildings and 2 minor damaged buildings.", + "Step 2: There are some buildings located in the upper right corner of theentire picture.", + "Step 3: There is a building with a white roof, and a parking lot to itsleft.", + "Step 4: Bounding Box -[<955><0><1024><88>] is the described building.", + "Step 5: Bounding Box -[<955><0><1024><88>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<955><0><1024><88>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000443_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0012", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper side of the image and is trapezoidal. The building is the smallest inthe whole picture, with a white roof. Please assess the damage to thebuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 99buildings that were badly damaged and 4 that were completely damaged.", + "Step 2: There is a river channel in the upper left corner of the picture, anda trapezoidal building on the right side of the river.", + "Step 3:There are several buildings in this area, located above the image,surrounded by buildings that are all larger than it and have white roofs.", + "Step 4: Bounding Box -[<390><191><418><219>] is the described building.", + "Step 5: Bounding box -[<390><191><418><219>] does not have a full roof and upright walls, and thegap between them is large.", + "Step 6: Bounding Box -[<390><191><418><219>] is major-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000463_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0013", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the picture. It stands alone and is surrounded by roadsin a circle, separated from other buildings.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 7 minordamage buildings and 87 major damage buildings.", + "Step 2: There is a picture in the upper right corner, surrounded by severalroads, and there are many buildings of various shapes around the roads.", + "Step 3:There is an area where a building is located in the upper right cornerof the picture, surrounded by a road. There are several roads around leadingto the building in all directions, and the surrounding buildings are allsmaller than it.", + "Step 4: Bounding Box -[<631><159><695><281>] is the described building.", + "Step 5: Bounding Box -[<631><159><695><281>] has a Incomplete roof and not vertical walls without alot of gaps gaps.", + "Step 6: Bounding Box -[<631><159><695><281>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000471_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0014", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper side of the road and is rectangular in shape. This building is thesmallest of the upper half of the picture. Please assess the damage to thebuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 33major-damage buildings,3 minor-damges buildings and 1 destroyed building.", + "Step 2: There is a road in the middle of the picture, and there arerectangular buildings above the road.", + "Step 3: There is a building in this area, located in the upper left corner ofthe road, and the surrounding buildings are all larger than it.", + "Step 4: Bounding Box -[<189><109><233><156>] is the described building.", + "Step 5: Bounding box -[<189><109><233><156>] has an incomplete roof and broken walls.", + "Step 6: Bounding Box -[<189><109><233><156>] is major-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000470_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0015", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the intersection, with a rectangular shape. This building is inthe middle position on the right side of the picture. There is no buildingdirectly above it. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged building, 5 minor damaged buildings, 9 major damaged buildings, 16fully destroyed buildings and 4 unclassified buildings.", + "Step 2: There are some buildings in the middle position on the right side ofthe picture.", + "Step 3: There is a building on the right side of the crossroads. There is nobuilding directly above it.", + "Step 4: Bounding Box -[<953><499><977><515>] is the described building.", + "Step 5: The building has completely collapsed with no remaining structuralintegrity, leaving only rubble and debris.", + "Step 6: Bounding Box -[<953><499><977><515>] is Fully destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000198_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0016", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the green belt and is rectangular in shape. This building is theone closest to the circular building. Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 29undamaged buildings, 11 major damaged buildings and 7 minor damagedbuildings.", + "Step 2: There are some buildings in the upper right corner of the picture.", + "Step 3: There is a building located on the right side of the green belt, theclosest to the circular building.", + "Step 4: Bounding Box -[<921><189><955><234>] is the described building.", + "Step 5: Bounding Box -[<921><189><955><234>] has severe structural collapse, extensive wallbreaches, and partial roof failure.", + "Step 6: Bounding Box -[<921><189><955><234>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000455_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0017", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom side of the picture, with a rectangular shape. This building is smallerthan most of buildings in the entire picture. Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 3destroyed buildings,5 unclassified buildings,6 minor damaged buildings and 179major damaged buildings.", + "Step 2: There is a location in the middle bottom of the picture, and thereare rectangluar buildings on the right side of the location.", + "Step 3: There is a building in this area located in the middle bottom of theintersection, connected by a path and road, and the surrounding buildings mostof which are bigger than it.", + "Step 4: Bounding Box -[<520><991><543><1013>] is the described building.", + "Step 5: Bounding Box -[<520><991><543><1013>] has not a complete roof and upright walls.", + "Step 6: Bounding Box -[<520><991><543><1013>] is destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000347_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0018", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper left side of the picture, with a rectangular shape. This building is thelarger than most of buildings in the entire picture. Please evaluate thedamage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the upper left corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<75><33><186><194>] is the described building.", + "Step 5: Bounding Box -[<75><33><186><194>] has a broken roof and walls with some gaps.", + "Step 6: Bounding Box -[<75><33><186><194>] is minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000375_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0019", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 48minor damaged buildings and 10 destroyed buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the upper right corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<875><717><925><740>] is the described building.", + "Step 5: Bounding Box -[<875><717><925><740>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<875><717><925><740>] is destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000462_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0020", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is triangular inshape and located on the lower side of the road, with four similar rectangularbuildings adjacent to it. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 9 fullydestroyed buildings.", + "Step 2: There are some buildings located in the lower left corner of thepicture.", + "Step 3: There is a triangular building located on the lower side of the road,adjacent to four similar rectangular structures.", + "Step 4: Bounding Box -[<0><759><16><789>] is the described building.", + "Step 5: Bounding Box -[<0><759><16><789>] has completely collapsed with no remaining structuralintegrity, leaving only rubble and debris.", + "Step 6: Bounding Box -[<0><759><16><789>] is Fully destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000310_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0021", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thelower side of the coast and is in an L shape. This building is on the upperside of all the buildings in the picture and is the one closest to the coast.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 279minor damaged buildings, 32 major damaged buildings, 18 fully destroyedbuildings and 6 unclassified buildings.", + "Step 2: There are some buildings in the middle of the left side of thepicture.", + "Step 3: There is a building positioned at the top of all structures in theimage that is also the closest to the coastline.", + "Step 4: Bounding Box -[<166><500><192><529>] is the described building.", + "Step 5: Bounding Box -[<166><500><192><529>] has completely collapsed with no remaining structuralintegrity, leaving only rubble and debris.", + "Step 6: Bounding Box -[<166><500><192><529>] is Fully destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000372_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0022", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower right corner of the road and is rectangular in shape. There is also apath above the building. Please assess the damage to this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings, 3 unclassified buildings, 4 minor—damage buildings and 1major-damage building.", + "Step 2: There is a highway on the right side of the picture, and there arerectangular buildings in the lower right corner of the road.", + "Step 3:There is a building in the lower right corner of the road, and thereis a path above the building that connects to the road.", + "Step 4: Bounding Box -[<967><909><1015><945>] is the described building.", + "Step 5: Bounding Box -[<967><909><1015><945>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<967><909><1015><945>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000009_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0023", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the picture, closest to the edge. Its shape isrectangular and there is a road on the right.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 79undamaged buildings, 21 minor-damage buildings, 3 major-damage buildings, 1destroyed buildings and 3 unclassified buildings.", + "Step 2: There is a vertical road in the upper right corner of the picture,and on the left side of the road, there is a rectangular building.", + "Step 3: There is a building in this area, there is a building located on theleft side of the road. It is not connected to the surrounding buildings. Onlybelow it is there a building of a similar shape to it.", + "Step 4: Bounding Box -[<793><9><823><72>] is the described building.", + "Step 5: Bounding Box -[<793><9><823><72>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<793><9><823><72>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000016_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0024", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road. Please evaluate thedamage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 35undamaged buildings, 10 minor damaged buildings, 5 major damaged buildings and3 destroyed buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the right side of theintersection, connected by a path and road, and the surrounding buildings aresmaller than it.", + "Step 4: Bounding Box -[<572><534><896><743>] is the described building.", + "Step 5: Bounding Box -[<572><534><896><743>] has no roof and upright walls with many gaps.", + "Step 6: Bounding Box -[<572><534><896><743>] is destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000035_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0025", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is the lowest of theseven buildings in the upper left corner of the crossroads and is in an Lshape. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings, 8 minor damaged buildings, 4 major damaged buildings and2 fully destroyed buildings.", + "Step 2: There are seven buildings in the upper left corner of thecrossroads.", + "Step 3: There is a building located at the bottom of the seven buildings inthe upper left corner of the crossroads.", + "Step 4: Bounding Box -[<2><758><27><803>] is the described building.", + "Step 5: Bounding Box -[<2><758><27><803>] has severe structural collapse, extensive wallbreaches, and partial roof failure.", + "Step 6: Bounding Box -[<2><758><27><803>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000044_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0026", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the image.This building is the topmost of the threebuildings on the left side of the road. Please evaluate the damage situationof this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged building and 7 minor damaged buildings.", + "Step 2: There are some buildings in the upper right corner of the picture.", + "Step 3: There is the topmost building among the three buildings on the leftside of a road.", + "Step 4: Bounding Box -[<882><144><935><210>] is the described building.", + "Step 5: Bounding Box -[<882><144><935><210>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 6: Bounding Box -[<882><144><935><210>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000130_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0027", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the junction of the arc road and the straight road on the rightside of the image, and is in an inverse Z-shape. Please assess the damage tothe building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 69undamaged buildings, 1 unclassified building, 11 slightly damaged buildings,and 1 severely damaged building.", + "Step 2:In the lower right corner of the picture there is a building on theleft side of the junction of the curved road and the straight road.", + "Step 3:There is an inverted Z-shaped building in this area, located to theleft of the junction.", + "Step 4: Bounding Box -[<281><772><349><825>] is the described building.", + "Step 5: Bounding Box -[<281><772><349><825>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<281><772><349><825>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000147_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0028", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:There is building located in thebottom right corner of the whole picture, in the shape of a square, with arectangular building above it and a rectangular building on the left. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 2: There building is located in the bottom right corner of the wholepicture.", + "Step 3: There is a building in this area located in the upper right corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<963><967><1024><1024>] is the described building.", + "Step 5: Bounding Box -[<963><967><1024><1024>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<963><967><1024><1024>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000418_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0029", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located on theleft side of the river on the left side of the picture and is irregularlyshaped, and on the left side of the picture, it connects a row of buildings inthe forest on the left side with a large river. Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 210buildings with major damage.", + "Step 2: There In the middle left of the picture there is a green forest, andthere are irregular buildings in the middle of the forest.", + "Step 3: There are 5 buildings side by side in this area, counting from leftto right, the building is last.", + "Step 4: Bounding Box -[<133><411><184><470>] is the described building.", + "Step 5: Bounding Box -[<133><411><184><470>] has a broken roof and the walls have slightcollapses.", + "Step 6: Bounding Box -[<133><411><184><470>] has major damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000502_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0030", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom middle of the image and is the only triangular figure in the picture.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings，2 minor-damaged buildings and 1 un-classified buildings.", + "Step 2:There is a triangular building at the very bottom of the image.", + "Step 3:There is only one building to the left of the building.", + "Step 4: Bounding Box -[<405><1011><434><1024>] is the described building.", + "Step 5: Bounding Box -[<405><1011><434><1024>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<405><1011><434><1024>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000365_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0031", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theleft center of the image, in a 7-sided shape, and it is surrounded by acircular path, and it is surrounded by a large open space.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 31minor-damaged buildings,3 major-damaged buildings and 1 fully destroyedbuilding.", + "Step 2: There is a 7-sided building on the left side of the picture.", + "Step 3: In the middle of this area, there is a polygonal building in thecircular path. It is at a distance from other buildings.", + "Step 4: Bounding Box -[<24><574><50><598>] is the described building.", + "Step 5: The roof of Bounding Box -[<24><574><50><598>] has completely collapsed, leaving only afew ruins on the walls.", + "Step 6: Bounding Box -[<24><574><50><598>] is fully damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000003_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0032", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is in the far rightcorner of the image, rectangular in shape, it is surrounded by a forest and tothe left is the road. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20minor-damaged buildings ，67 no-damaged buildings,4 major-damaged buildings,1fully destroyed building and 1 un-classified building.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the upper right corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<961><107><993><131>] is the described building.", + "Step 5: Bounding Box -[<961><107><993><131>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<961><107><993><131>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000072_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0033", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, in the bottom right conner of the entire picture witha rectangular shape. This building is the smallest in the entire picture, andit is connected to the road through a small path. Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 59undamaged buildings,15 minor damaged buildings, 3 destroyed buildings,15 minordamaged buildings and 1 unclassified buildings.", + "Step 2: There is a intersection in the bottom right corner of the picture,and there are rectangular buildings on the left side of the intersection.", + "Step 3: There is a building in this area located in the left side of theintersection, connected by a path and road, and the surrounding buildings arebigger than it.", + "Step 4: Bounding Box -[<698><836><704><844>] is the described building.", + "Step 5: Bounding Box -[<698><836><704><844>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<698><836><704><844>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000152_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0034", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper left of the picture and is rectangular in shape. The building is theclosest to the intersection. Please assess the damage to the building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 6minor-damage buildings,5 major-damage buildings,2 no-damage buildings and 2destroyed buildings.", + "Step 2: There is an X-shaped intersection above the picture, and there arerectangular buildings on the right side of the intersection.", + "Step 3: In this area there is a building, located in the lower right cornerof the intersection, connected by roads and paths, surrounded by largerbuildings.", + "Step 4: Bounding Box -[<302><232><354><303>] is the described building.", + "Step 5: Bounding box -[<302><232><354><303>] has an incomplete roof and gaped walls that are notupright.", + "Step 6: Bounding Box -[<302><232><354><303>] is destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000151_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0035", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thelower side of the road and is rectangular. This building is located at thelargest bottom of the entire picture and there are no other buildings aroundit. Please assess the damage of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 21undamaged buildings, 2 major-damage buildings and 2 minor-damage buildings.", + "Step 2: There is a horizontal road in the picture and there are buildingsbelow it. It is beneath the largest building.", + "Step 3: The building is located on the lower side of the road and isrectangular. This building is located at the largest bottom of the entirepicture and there are no other buildings around it. Please assess the damageof this building.", + "Step 4: Bounding Box -[<59><947><91><997>] is the described building.", + "Step 5: Bounding Box -[<59><947><91><997>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<59><947><91><997>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000183_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0036", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper left corner of the first intersection, with a rectangular shape and agray roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 50undamaged buildings ,23 minor-damaged buildings, 7 major damaged buildings,6fully destroyed buildings and un-classified buil dings ", + "Step 2: There building is located in the upper left corner of the firstintersection", + "Step 3: There building is surrounded by a forest, with two roads to its rightand below, located in the upper left corner of the first intersection.", + "Step 4: Bounding Box -[<0><0><52><96>] is the described building.", + "Step 5: The roof of the Bounding Box -[<0><0><52><96>] has large cracks and the walls haveslight collapses.", + "Step 6: Bounding Box -[<0><0><52><96>] is major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000253_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0037", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the main road on the far right of the picture and is rectangularin shape. This building is the one closest to the upper right corner in thepicture. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 65undamaged buildings, 42 minor damaged buildings and 6 major damagedbuildings.", + "Step 2: There are some buildings in the upper right corner of the picture.", + "Step 3: There is a building located on the right side of the main road at thefar right of the picture, which is the building closest to the upper rightcorner in the picture.", + "Step 4: Bounding Box -[<985><0><1024><24>] is the described building.", + "Step 5: Bounding Box -[<985><0><1024><24>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 6: Bounding Box -[<985><0><1024><24>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000181_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0038", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located below theriver and is rectangular in shape. This building is the smallest green roofedbuilding in the entire picture. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 4minor-damage buildings and 1 unclassified buildings and 5 destroyedbuildings.", + "Step 2: there are 3 buildings located in the bottom left corner of thepicture.", + "Step 3: There is a building here that is the smallest green rectangularbuilding.", + "Step 4: Bounding Box -[<130><987><145><998>] is the described building.", + "Step 5: The roof and walls of Bounding Box -[<130><987><145><998>] have slight cracks.", + "Step 6: Bounding Box -[<130><987><145><998>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000190_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0039", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located below theroad and is rectangular in shape. This building is the smallest in the entirepicture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 8major-damaged buildings and 1 unclassified buildings and 10 destroyedbuildings and 4minor-damage buildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: There is a building here with the smallest green rectangular roof.", + "Step 4: Bounding Box -[<37><422><52><448>] is the described building.", + "Step 5: Bounding Box -[<37><422><52><448>] walls and roof have obvious cracks.", + "Step 6: Bounding Box -[<37><422><52><448>] is Major-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000221_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0040", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the city and is triangular in shape. There is a green roof.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings and 9 unclassified buildings and 67 minor-damge buildingsand 12 major-damage buildings and 3 destryed buildings.", + "Step 2: there are some buildings located in the bottom left corner of theimage.", + "Step 3: There is a building with a green roof in the shape of a triangle.", + "Step 4: Bounding Box -[<266><1014><291><1024>] is the described building.", + "Step 5: Bounding Box -[<266><1014><291><1024>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<266><1014><291><1024>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000278_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0041", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on anopen space between two roads and is triangular in shape. This building is thelargest triangular green roof building in the entire picture. Please evaluatethe damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 43undamaged buildings and 1 unclassified buildings and10 minor-damagebuildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: There is a building located on an open space between two roads, witha green triangular roof.", + "Step 4: Bounding Box -[<0><442><18><486>] is the described building.", + "Step 5: Bounding Box -[<0><442><18><486>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<0><442><18><486>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0042", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the intersection in the lower left corner of the picture, in atriangular shape. This building is the smallest building in the entirepicture. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 77undamaged buildings and 1 unclassified buildings and 4 major-damage buildingsand 18 minor-damage buidlings and 2 destroyed buildings.", + "Step 2: There are some buildings located in the lower left corner of thepicture.", + "Step 3: There is a building that is the smallest triangular building in theentire picture.", + "Step 4: Bounding Box -[<1><994><9><1016>] is the described building.", + "Step 5: Bounding Box -[<1><994><9><1016>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<1><994><9><1016>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000014_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0043", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located below thetown, on a green belt, in a triangular shape. There is a green roof. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 12undamaged buildings and 1 unclassified buildings and 4 major-damage buildingsand 18 minor-damage buildings and 1 destroyed buildings.", + "Step 2: There are some buildings located in the bottom left corner of theimage.", + "Step 3: There is a building with a triangular green roof.", + "Step 4: Bounding Box -[<2><927><40><997>] is the described building.", + "Step 5: Bounding Box -[<2><927><40><997>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<2><927><40><997>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000034_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0044", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thegreen belt on the right side of the picture, forming a triangle. Thisbuilding is the smallest green roofed building in the entire picture. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 44undamaged buildings and 9 minor-damage buildings and 4 major-damagebuildings.", + "Step 2: There are some buildings located on the green belt on the right sideof the picture.", + "Step 3: There is a buildinge has the smallest green roof triangular buildingin the entire picture.", + "Step 4: Bounding Box -[<1010><42><1024><81>] is the described building.", + "Step 5: Bounding Box -[<1010><42><1024><81>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<1010><42><1024><81>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000056_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0045", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on a greenbelt and is rectangular in shape. This building is the smallest building inthe entire picture. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 54undamaged buildings and 14 minor-damage buildings and 6 major-damage buildingsand 1 destroyed buildings.", + "Step 2: There are some buildings located in the lower right corner.", + "Step 3: There is a building the smallest rectangular building with a greenroof is located in the city center.", + "Step 4: Bounding Box -[<402><625><408><638>] is the described building.", + "Step 5: Bounding Box -[<402><625><408><638>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<402><625><408><638>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000142_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0046", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located below theparking lot on the right side of the highway, in a triangular shape. Thisbuilding is the smallest building in the entire picture. Please evaluate thedamage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 70undamaged buildings and 10 major-damage buildings and 22 minor-damagebuildings.", + "Step 2: There are 4 buildings located in the bottom right corner of thepicture.", + "Step 3: There is a building located below the parking lot, which has atriangular roof.", + "Step 4: Bounding Box -[<997><997><1024><1024>] is the described building.", + "Step 5: Bounding Box -[<997><997><1024><1024>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<997><997><1024><1024>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000146_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0047", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the left road and is triangular in shape. There is a beige roof.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 1 unclassified buildings and 23 destroyed buildingsand 21 minor-damage buildings and 10 major-damage buildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: There is a building located on the right side of the left road, witha triangular shaped earth yellow roof.", + "Step 4: Bounding Box -[<362><0><436><23>] is the described building.", + "Step 5: Bounding Box -[<362><0><436><23>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<362><0><436><23>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000165_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0048", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the parking lot below the road and is L-shaped. There is a whiteroof. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 66undamaged buildings and 5 major-damage buildings and 69 minor-damagebuildings and 4 destroyed buildings.", + "Step 2: There are some buildings located in the bottom left corner of theimage.", + "Step 3: There is a building with an L-shaped white roof located on the leftside of the parking lot.", + "Step 4: Bounding Box -[<24><637><149><707>] is the described building.", + "Step 5: Bounding Box -[<24><637><149><707>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<24><637><149><707>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000266_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0049", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom left corner of the diagram and has the largest area.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings and 3 major damaged buildings and 4 minor damagedbuildings and 2 unclassified buildings.", + "Step 2: There are building in the bottom left corner of the picture.", + "Step 3: There is a building in the bottom left corner of the picture and itis the largest in area.", + "Step 4: Bounding Box -[<18><682><790><1024>] is the described building.", + "Step 5: Bounding Box -[<18><682><790><1024>] has obvious cracks on the roof and walls.", + "Step 6: Bounding Box -[<18><682><790><1024>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000261_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0050", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom left corner of the diagram and presents a triangular shape. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged buildings and 7 major damaged buildings and 14 minor damagedbuildingsand 4 destroyed buildings.", + "Step 2: There are building in the bottom left corner of the picture.", + "Step 3: There is a building in the lower left corner of the picture and itappears in a triangular shape.", + "Step 4: Bounding Box -[<38><1000><85><1024>] is the described building.", + "Step 5: Bounding Box -[<38><1000><85><1024>] has slight damage to the roof and walls.", + "Step 6: Bounding Box -[<38><1000><85><1024>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000200_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0051", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper left corner closest to the lake and presents the largest square shape.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 14major damaged buildings and 2 minor damaged buildings and 108 destroyedbuildings.", + "Step 2: There are building in the upper left corner of the picture.", + "Step 3: In the upper left corner of the picture, there is a building that isclosest to the largest lake and is the largest square.", + "Step 4: Bounding Box -[<3><84><54><144>] is the described building.", + "Step 5: Bounding Box -[<3><84><54><144>] has obvious cracks on the roof and walls.", + "Step 6: Bounding Box -[<3><84><54><144>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000385_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0052", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thebottom right side of the road in the picture and presents the longestrectangle. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 33minor damaged buildings and 10 major damaged buildings and 54 undamagedbuildings and 2 destroyed buildings.", + "Step 2: There are buildings at the bottom of the road near the right in thepicture.", + "Step 3: There is a building located at the bottom of the picture, close tothe right side of the road, and presenting the longest rectangle.", + "Step 4: Bounding Box -[<500><948><693><1024>] is the described building.", + "Step 5: Bounding Box -[<500><948><693><1024>] has has obvious cracks on the roof and walls.", + "Step 6: Bounding Box -[<500><948><693><1024>] is major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000051_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0053", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom right corner of the diagram and is the largest building in terms ofarea. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 37undamaged buildings and 15 minor damage buildings and 2 destroyed buildingsand 2 unclassified buildings.", + "Step 2: There are building in the bottom right corner of the picture, andthere are rectangular buildings on the right side of the intersection.", + "Step 3: There is a building in the bottom right corner of the picture and itis the largest building in terms of area.", + "Step 4: Bounding Box -[<897><958><989><1024>] is the described building.", + "Step 5: Bounding Box -[<897><958><989><1024>] has slight cracks on the roof and walls.", + "Step 6: Bounding Box -[<897><958><989><1024>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000335_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0054", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower right corner of the diagram, with the road on the right side and thelargest area . Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 2undamaged buildings and 4 minor damaged buildings and 6 major damagedbuildings and 1 destroyed building.", + "Step 2: There are building in the bottom right corner of the picture.", + "Step 3: in the bottom right corner of the picture, there is a building nearthe road on the right, and it is the largest building in terms of area.", + "Step 4: Bounding Box -[<490><555><671><773>] is the described building.", + "Step 5: Bounding Box -[<490><555><671><773>] has slight cracks on the roof and walls.", + "Step 6: Bounding Box -[<490><555><671><773>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000124_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0055", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom left corner of the diagram and appears as a square . Please evaluatethe damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 6 majordamaged buildings and 8 minor damaged buildings and 17 destroyed buildings and2 unclassified buildings.", + "Step 2: There are building in the bottom left corner of the picture.", + "Step 3: There is a building in the bottom left corner of the picture and itappears as a square.", + "Step 4: Bounding Box -[<45><1000><63><1016>] is the described building.", + "Step 5: Bounding Box -[<45><1000><63><1016>] has completely collapsed, leaving only a few ruins onthe walls.", + "Step 6: Bounding Box -[<45><1000><63><1016>] is Fully destroyed." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000231_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0056", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper left side of the image, closest to the narrow road, next to an open andlight colored area. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 34 no-damaged buildings and 14 major-damage buildings.", + "Step 2: In the upper left part of the picture, there is a building near anarrow road.", + "Step 3: In the upper left part of the picture, there is a building closest tothe narrow road, and the shape of the building is trapezoidal.", + "Step 4: Bounding Box -[<97><347><148><390>] is the described building.", + "Step 5: Bounding Box -[<97><347><148><390>] There are obvious cracks on the roof and walls.", + "Step 6: Bounding Box -[<97><347><148><390>] is Major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000338_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0057", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:There is a small island in thebottom left corner of the picture, and this building is arranged in theleftmost position from left to right on the island. Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 9 no-damaged buildings and 1 major damaged building and 132 minor damagedbuildings.", + "Step 2: There are buildings on the small island in the lower left part of thepicture.", + "Step 3: In the lower left part of the figure, there is a building on theisland, and this building is ranked first in the island in order from left toright.", + "Step 4: Bounding Box -[<140><978><216><1024>] is the described building.", + "Step 5: Bounding Box -[<140><978><216><1024>] has slight damage to the roof and walls.", + "Step 6: Bounding Box -[<140><978><216><1024>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000433_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0058", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 257undamaged buildings.", + "Step 2: There are building in the upper right corner of the picture.", + "Step 3: There is a building in the upper right corner of the picture, andthis building appears rectangular closest to the upper right corner.", + "Step 4: Bounding Box -[<1003><6><1018><78>] is the described building.", + "Step 5: Bounding Box -[<1003><6><1018><78>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<1003><6><1018><78>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000452_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0059", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom right corner and presents a triangular shape. Please evaluate thedamage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 114major damaged buildings and 60 minor damaged buildings and 2 unclassifiedbuildings and 1 destroyed building.", + "Step 2: There are building in the bottom right corner of the picture.", + "Step 3: In the bottom right corner of the figure, there is a building and theshape is the smallest triangle.", + "Step 4: Bounding Box -[<985><1006><1015><1024>] is the described building.", + "Step 5: Bounding Box -[<985><1006><1015><1024>] has slight cracks on the roof and walls.", + "Step 6: Bounding Box -[<985><1006><1015><1024>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000491_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0060", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in themiddle of the parking lot and is rectangular in shape. Above it is a highway.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 2: There are 8 buildings located in the bottom left corner of thepicture.", + "Step 3: There is a building located in the center of the parking lot, it isthe largest rectangular building.", + "Step 4: Bounding Box -[<0><638><99><868>] is the described building.", + "Step 5: Bounding Box -[<0><638><99><868>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<0><638><99><868>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000469_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0061", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located on theright side of the river. It is elliptical in shape and has a green roof.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 2undamaged buildings and 1 unclassified buildings and 33 minor-damagebuildings.", + "Step 2: There are 2 buildings located in the bottom right corner of theimage.", + "Step 3: There is a building has an oval shaped green roof.", + "Step 4: Bounding Box -[<967><624><989><652>] is the described building.", + "Step 5: Bounding Box -[<967><624><989><652>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<967><624><989><652>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000478_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0062", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper right side of the road, in an L-shape, with a reddish brown roof. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 86undamaged buildings and 18 major-damage buildings and 6 minor-damgebuildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: There is a building has a reddish brown roof and is L-shaped.", + "Step 4: Bounding Box -[<399><185><472><290>] is the described building.", + "Step 5: There are slight cracks on the walls and roof of Bounding Box -[<399><185><472><290>] ", + "Step 6: Bounding Box -[<399><185><472><290>] is Major-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000492_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0063", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the parking lot, rectangular in shape, and is the smallest whiteroofed building. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 35undamaged buildings.", + "Step 2: There are 6 buildings located in the bottom left corner of thepicture.", + "Step 3: There is a building is the smallest rectangular white roofedbuilding located on the left side of the parking lot.", + "Step 4: Bounding Box -[<73><387><100><409>] is the described building.", + "Step 5: Bounding Box -[<73><387><100><409>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<73><387><100><409>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000514_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0064", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower right corner of the picture and is rectangular in shape. To its left isa small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 93undamaged buildings.", + "Step 2: There are some buildings in the bottom right corner of the picture.", + "Step 3: There is a building on the right side of the road, and there is alarger rectangular building directly above it.", + "Step 4: Bounding Box -[<823><873><871><1024>] is the described building.", + "Step 5: Bounding Box -[<823><873><871><1024>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<823><873><871><1024>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000397_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0065", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 29destroyed buildings and 7 major buildings.", + "Step 2: There are some buildings in the bottom right corner of the picture.", + "Step 3: There is a building in the bottom left corner of the picture, whichis the largest rectangular shaped building with a white roof.", + "Step 4: Bounding Box -[<608><676><748><707>] is the described building.", + "Step 5: Bounding Box -[<608><676><748><707>] has a severely damaged door and window, and a hole hasbeen opened in the roof.", + "Step 6: Bounding Box -[<608><676><748><707>] is Major-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000493_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0066", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower left corner of the picture, rectangular in shape, surrounded by forests,and a road in front of it to the left. Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 40undamaged buildings 、4 unclassified buildings、31 minor damaged buildings、4major damaged buildings and 1 destroyed buildings.", + "Step 2: There are some buildings in the bottom left corner of the picture.", + "Step 3: There is a building located in the bottom left corner of the picture,surrounded by forests, and in front of it on the left is a rectangular road.", + "Step 4: Bounding Box -[<249><525><286><568>] is the described building.", + "Step 5: Bounding Box -[<249><525><286><568>] has one door and window slightly damaged, while theothers were not damaged.", + "Step 6: Bounding Box -[<249><525><286><568>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000129_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0067", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the picture, in an irregular rectangle, surrounded byforests. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 23undamaged buildings、3 major damaged buildings、6 minor damaged buildings and 2unclassified buildings.", + "Step 2: There is a building in the upper right corner of the picture.", + "Step 3: There is a building in the upper right corner of the picture. It isthe smallest building with a purple red roof.", + "Step 4: Bounding Box -[<989><341><1019><366>] is the described building.", + "Step 5: Bounding Box -[<989><341><1019><366>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<989><341><1019><366>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000364_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0068", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 22undamaged buildings and 6 minor damaged buildings.", + "Step 2: There are some buildings located in the upper right corner of thepicture, above the road.", + "Step 3: There are some buildings located in the upper right corner of thepicture, above the road. It is the largest rectangular shaped building in theentire picture.", + "Step 4: Bounding Box -[<706><167><767><244>] is the described building.", + "Step 5: Bounding Box -[<706><167><767><244>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<706><167><767><244>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000008_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0069", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located below thepicture and is the largest rectangular shaped building in the entire picture.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 48undamaged buildings、6 major damaged buildings、9 minor damaged buildings and 4unclassified buildings.", + "Step 2: There are some buildings located directly below the picture, at theintersection of two roads.", + "Step 3: There is a building located at the intersection of the secondhorizontal road and the third vertical road.", + "Step 4: Bounding Box -[<396><730><572><775>] is the described building.", + "Step 5: Bounding Box -[<396><730><572><775>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<396><730><572><775>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000058_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0070", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper right corner of the picture, above the first horizontal road from top tobottom, and has a rectangular shape. Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 62undamaged buildings、4 major damaged buildings、35 minor damaged buildings and 1unclassified buildings.", + "Step 2: There are some buildings located in the upper right corner of thepicture, with white roofs and rectangular shapes", + "Step 3: There is a building located above the first cross road from top tobottom, in the upper right corner of the picture, with a white roof and arectangular shape.", + "Step 4: Bounding Box -[<985><123><1024><226>] is the described building.", + "Step 5: Bounding Box -[<985><123><1024><226>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<985><123><1024><226>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000202_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0071", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom side of the road, with a rectangular shape. This building is in thebottom right conner entire picture, and it is connected to the road. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 44undamaged buildings, 12 major damaged buildings, 4 destroyed buildings, 22minor damaged buildings and 13 unclassified buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the left side of theintersection.", + "Step 3: There is a building in this area located in the left corner of theintersection, connected by a path and road, and the surrounding buildings aresmaller than it.", + "Step 4: Bounding Box -[<908><999><979><1023>] is the described building.", + "Step 5: Bounding Box -[<908><999><979><1023>] has a badly broken roof and upright walls with manygaps.", + "Step 6: Bounding Box -[<908><999><979><1023>] is major damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000184_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0072", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the road, in a triangular shape with a green roof. Pleaseevaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 35undamaged buildings and 18 major-damage buildings and 17 minor-damagebuildings.", + "Step 2: There are some buildings located in the upper right corner of theimage.", + "Step 3: There is a building with a triangular green roof located on the greenbelt on the right side of the road", + "Step 4: Bounding Box -[<999><353><1024><433>] is the described building.", + "Step 5: Bounding Box -[<999><353><1024><433>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<999><353><1024><433>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000405_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0073", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the middle of the picture, close to the path on the left side,and is the longest rectangle. Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 36undamaged buildings and 1 destroyed building and 11 minor damaged buildingsand 2 major damaged buidings.", + "Step 2: There are building on the left side in the middle.", + "Step 3: In the middle left side of the picture, there is a small path nearthe left side with buildings and it is the longest rectangle.", + "Step 4: Bounding Box -[<234><411><274><515>] is the described building.", + "Step 5: Bounding Box -[<234><411><274><515>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<234><411><274><515>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000454_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0074", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thelower side of the main road and is rectangular in shape. It is connected tothe road via a path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 185undamaged buildings.", + "Step 2: There are many buildings on the left side of the picture.", + "Step 3: There is a building located on the lower side of the main road, inthe shape of a rectangle. It is connected to the road via a narrow path.", + "Step 4: Bounding Box -[<16><587><36><616>] is the described building.", + "Step 5: Bounding Box -[<16><587><36><616>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<16><587><36><616>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000462_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0075", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thelower right corner of the intersection and is triangular in shape. Thisbuilding is the smallest in the entire picture. Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 71undamaged buildings and 5 unclassified buildings and 12 minor-damage buildingsand 4 major buildings and 1 destroyed buildings.", + "Step 2: There are some buildings located in the bottom right corner of theimage", + "Step 3: There is a building with the smallest triangular roof located in thelower right corner of the intersection.", + "Step 4: Bounding Box -[<1010><898><1024><925>] is the described building.", + "Step 5: Bounding Box -[<1010><898><1024><925>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<1010><898><1024><925>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000473_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0076", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on thebottom side of the road and takes the shape of a cross. The building isconnected to the road via a path.Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 127undamaged buildings.", + "Step 2: There are many buildings in the lower right corner of the picture.", + "Step 3: There is a building located on the lower side of the road, in theshape of a cross. This building is connected to the road via a path.", + "Step 4: Bounding Box -[<919><800><965><838>] is the described building.", + "Step 5: Bounding Box -[<919><800><965><838>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<919><800><965><838>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000474_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0077", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located at theupper right corner of the intersection, with a similar rectangular buildingpositioned upper it. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 14undamaged buildings, 2 minor damaged buildings and 1 major damaged building.", + "Step 2: There is a crossroads at the top-right corner of the image, with twobuildings at its upper right corner.", + "Step 3: There is a building located in the upper right corner of theintersection, and upper it there is a rectangular building similar to it.", + "Step 4: Bounding Box -[<966><34><1024><76>] is the described building.", + "Step 5: Bounding Box -[<966><34><1024><76>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 6: Bounding Box -[<966><34><1024><76>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000275_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0078", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper left corner of the crossroads at the lower right corner of the picture.This building is rectangular. It is on the right side of the longest buildingin the picture, and there is another building of the same area directlybeneath it. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 55undamaged buildings, 14 minor damaged buildings and 9 major damagedbuildings.", + "Step 2: There are three buildings located in the upper left corner of thecrossroads at the lower right corner of the picture. ", + "Step 3: There is a building on the right side of the picture's longeststructure, with another building of equal area positioned directly below it.", + "Step 4: Bounding Box -[<879><595><904><695>] is the described building.", + "Step 5: Bounding Box -[<879><595><904><695>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 6: Bounding Box -[<879><595><904><695>] is Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000461_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0079", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper side of the road and has an irregular shape. The building is the largestin the upper left corner of the entire picture. It is connected to the roadthrough a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 2: There are many buildings in the upper left corner of the picture.", + "Step 3: There is a building located on the upper side of the road, with anirregular shape. This building is the largest in the entire picture in theupper left corner. It is connected to the road via a narrow path.", + "Step 4: Bounding Box -[<60><190><249><318>] is the described building.", + "Step 5: Bounding Box -[<60><190><249><318>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<60><190><249><318>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000435_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0080", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theupper side of the road and has an irregular shape. This building is connectedto the road via a path.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings.", + "Step 2: There are many buildings in the lower left corner of the picture.", + "Step 3: There is a building located above the road, with an irregular shape.This building is connected to the road via a narrow path.", + "Step 4: Bounding Box -[<316><641><411><742>] is the described building.", + "Step 5: Bounding Box -[<316><641><411><742>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<316><641><411><742>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000265_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0081", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the road and is rectangular in shape.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 2: There are many buildings located at the center of the picture.", + "Step 3: There is a building located on the left side away from the road, atthe position slightly to the left of the center of the picture.", + "Step 4: Bounding Box -[<112><481><317><505>] is the described building.", + "Step 5: Bounding Box -[<112><481><317><505>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<112><481><317><505>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000167_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0082", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located beneaththe road and is rectangular in shape. It is connected to the road via apath.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 2: There are many buildings located beneath the picture.", + "Step 3: There is a building located on the left side of the crossroads, andthere are many buildings similar to it beside it.", + "Step 4: Bounding Box -[<504><860><528><913>] is the described building.", + "Step 5: Bounding Box -[<504><860><528><913>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<504><860><528><913>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000133_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0083", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theopposite side of the road and is rectangular in shape.Please evaluate thedamage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 16undamaged buildings.", + "Step 2: There are many buildings in the upper right corner of the picture.", + "Step 3: There is a rectangular building located on the right side of themiddle road, and the surrounding buildings are very similar to it.", + "Step 4: Bounding Box -[<588><62><732><125>] is the described building.", + "Step 5: Bounding Box -[<588><62><732><125>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<588><62><732><125>] is minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000039_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0084", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This rectangular building islocated right next to the road on the left side.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 42undamaged buildings.", + "Step 2: There are buildings are on the left side of the picture.", + "Step 3: There is a building located on the left side of the road, and thereare few surrounding buildings.", + "Step 4: Bounding Box -[<213><568><240><598>] is the described building.", + "Step 5: Bounding Box -[<213><568><240><598>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<213><568><240><598>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000373_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0085", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theleft side of the road and is rectangular in shape.Please evaluate the damagesituation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged buildings.", + "Step 2: There are some buildings located above the picture.", + "Step 3: There is a rectangular building located on the left side away fromthe road. All the surrounding buildings are far away from it.", + "Step 4: Bounding Box -[<146><56><163><73>] is the described building.", + "Step 5: Bounding Box -[<146><56><163><73>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<146><56><163><73>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000289_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0086", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located on theupper side of the road and is triangular in shape. This building is thesmallest one in the entire picture.Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 17minor-damaged buildings.", + "Step 2: There are buildings above the picture.", + "Step 3: There is a building located above the road, and all the surroundingbuildings are larger than it.", + "Step 4: Bounding Box -[<522><1><585><28>] is the described building.", + "Step 5: Bounding Box -[<522><1><585><28>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<522><1><585><28>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000501_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0087", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theleft side of the road, with a irregular shape. This building is the largest inthe entire picture. Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 112undamaged buildings.", + "Step 2: There are buildings on the left side of the picture.", + "Step 3: In this area, there is the largest building located on the left sideof the road. All the buildings around it are smaller than it.", + "Step 4: Bounding Box -[<0><502><140><683>] is the described building.", + "Step 5: Bounding Box -[<0><502><140><683>] has a slightly damaged roof and cracked walls.", + "Step 6: Bounding Box -[<0><502><140><683>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000461_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0088", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 52undamaged buildings.", + "Step 2: There is a building in the bottom right corner of the picture.", + "Step 3: There is a building in this area located in the bottom right cornerof the entire image.", + "Step 4: Bounding Box -[<670><820><742><1021>] is the described building.", + "Step 5: Bounding Box -[<670><820><742><1021>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<670><820><742><1021>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000400_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0089", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 138undamaged buildings.", + "Step 2: There is a T-shaped intersection in the bottom left corner of thepicture, and there are rectangular buildings on the left side of theintersection.", + "Step 3: There is a building in this area located in the bottom left corner ofthe intersection, connected by a path and road.", + "Step 4: Bounding Box -[<24><856><75><891>] is the described building.", + "Step 5: Bounding Box -[<24><856><75><891>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<24><856><75><891>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000381_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0090", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 2undamaged buildings and 1 unclassified buildings.", + "Step 2: There is a building in the bottom right corner of the picture, andthere are rectangular buildings on the upper side of it.", + "Step 3: There is a building in this area located in the bottom right cornerof the entire imagen it.", + "Step 4: Bounding Box -[<965><779><1024><875>] is the described building.", + "Step 5: Bounding Box -[<965><779><1024><875>] has a roof that is severely damaged and walls withlarge cracks.", + "Step 6: Bounding Box -[<965><779><1024><875>] is Major-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000369_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0091", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom side of the road, with a rectangular shape. This building is thelargest in the entire picture.Please evaluate the damage situation of thisbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 28undamaged buildings and 2 unclassified buildings.", + "Step 2: There is a building in the bottom right corner of the entire image,and there are rectangular buildings on the bottom side of the road.", + "Step 3: There is a building in this area located in the bottom right cornerof the entire image, and the surrounding buildings are smaller than it.", + "Step 4: Bounding Box -[<509><718><628><843>] is the described building.", + "Step 5: Bounding Box -[<509><718><628><843>] has a roof with minor damages and cracked walls.", + "Step 6: Bounding Box -[<509><718><628><843>] is Minor-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000346_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0092", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in thebottom left corner of the picture, on the left side of the leftmost road. Thebuilding is an irregular rectangle. Please evaluate the damage situation ofthis building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 31undamaged buildings、3 major damaged buildings、28 minor damaged buildings and 1unclassified buildings.", + "Step 2: There are some buildings located in the lower left corner of thepicture, with a parking lot and road in front of them.", + "Step 3: There are some buildings located in the bottom left corner of thepicture, which is the largest building in the bottom left corner of thepicture.", + "Step 4: Bounding Box -[<36><510><181><666>] is the described building.", + "Step 5: Bounding Box -[<36><510><181><666>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<36><510><181><666>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000145_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0093", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the upper right corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<800><828><845><865>] is the described building.", + "Step 5: Bounding Box -[<800><828><845><865>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<800><828><845><865>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0094", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located in theupper side of the road, with a rectangular shape. This building is the largestin the entire picture, and it is connected to the road through a small path.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There is a T-shaped intersection in the bottom right corner of thepicture, and there are rectangular buildings on the right side of theintersection.", + "Step 3: There is a building in this area located in the upper right corner ofthe intersection, connected by a path and road, and the surrounding buildingsare smaller than it.", + "Step 4: Bounding Box -[<800><828><845><865>] is the described building.", + "Step 5: Bounding Box -[<800><828><845><865>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<800><828><845><865>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0095", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:The building is located on theright side of the highway, L-shaped, it is the smallest white roofed building.Please evaluate the damage situation of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 2: There are 3 buildings located in the bottom left corner of thepicture.", + "Step 3: There is a building has an L-shaped white roof, with a highway on itsleft and a forest on its right.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: Bounding Box -[<336><881><360><911>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<336><881><360><911>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000380_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0096", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thebottom right corner of the picture and has a square shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 112undamaged buildings , 6 minor damaned buildings and 7 major damagedbuildings.", + "Step 2: There are 6 buildings in the bottom right corner of the picture.", + "Step 3: There is a building in this area which with a a square shape.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: Bounding Box -[<336><881><360><911>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<336><881><360><911>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000509_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0097", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in theupper left corner of the picture and is the longest building in the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 141undamaged buildings 20 minor-damage buildings ,4 major-damage buildings and 1unclassified building.", + "Step 2: There are 9 buildings in the upper left corner of the picture.", + "Step 3: There is a building that is longer than other buildings.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: Bounding Box -[<336><881><360><911>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<336><881><360><911>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000511_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0098", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in theupper left corner of the picture, on the upper side of the river. There aretwo similar buildings on the right side of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 134undamaged buildings ,4 minor-damage buildings.", + "Step 2: There are three buildings that are very similar.", + "Step 3: There are two similar buildings on the right side of a building.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: Bounding Box -[<336><881><360><911>] has a complete roof and upright walls without anygaps.", + "Step 6: Bounding Box -[<336><881><360><911>] is No-damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000512_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0099", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thelower left corner of the picture,with a forest on the right.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 28undamaged buildings 1 minor-damage buildings ,1 major-damage buildings.", + "Step 2: There are 15 buildings in the lower left corner of the picture.", + "Step 3: There is a forest on the right side of a building.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are slightly inclined, with someinconspicuous cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is minor-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000514_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0100", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building with a red roofedand rectangular shaped is located in the bottom left corner of the picture andis the largest building in the entire picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 115undamaged buildings 29 minor-damage buildings ,15 major-damage buildings and 3destroyed buildings.", + "Step 2: There are 14 buildings in the lower left corner of the picture.", + "Step 3: There is a building that is larger than other buildings.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000515_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0101", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thebottom right corner of the picture, on top of a highway. There is a red sedanunder this building on this road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 65undamaged buildings,13 minor-damage buildings ,1 major-damage buildings and 3destroyed buildings.", + "Step 2: There are 11 buildings in the bottom right corner of the picture.", + "Step 3: There is a building above the red sedan.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000516_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0102", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in theupper right corner of the intersection in the picture. The roof of thisbuilding is white.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 158undamaged buildings,4 minor-damage buildings.", + "Step 2: There are 21 buildings in the bottom right corner of the picture.", + "Step 3: There is a building with a white roof located in the upper rightcorner of the intersection.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000517_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0103", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thelower left corner of the picture and is the largest building near the parkinglot.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 130undamaged buildings,21 minor-damage buildings,9 major-damage buildings and 5destroyed buildings.", + "Step 2: There are 5 buildings in the bottom left corner of the picture.", + "Step 3: There is a building with a larger area than other buildings.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000519_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0104", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in theupper right corner of the picture and has a white L-shaped roof. There is asimilar building on its left.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 176undamaged buildings,15 minor-damage buildings,6 major-damage buildings.", + "Step 2: There are 28 buildings in the bottom left corner of the picture.", + "Step 3: There is a building with a white L-shaped roof.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000521_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0105", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located on theisland in the upper right corner of the picture and has a white roof. There isa road on its left.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 12undamaged buildings,2 minor-damage buildings.", + "Step 2: There are 7 buildings in the upper right corner of the picture.", + "Step 3: There is a building with a white shaped roof.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000521_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building damage assessment/0106", + "Question_Type": "Single Choice", + "Text": "Determine the degree of damage to the building from satellite andaerial images given the bounding boxes for referring objects. Bounding box inthe format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max, y_max). The resolution ofsatellite image is 1024 x 1024. Description:This building is located in thebottom right corner of the picture, with a forest above it. There is a similarbuilding on the left side of this building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 160undamaged buildings,1 minor-damage building.", + "Step 2: There are 11 buildings in the bottom right corner of the picture.", + "Step 3: There is a similar building on the left side of a building.", + "Step 4: Bounding Box -[<336><881><360><911>] is the described building.", + "Step 5: The walls and roof of this building are intact without any cracks.", + "Step 6: Bounding Box -[<336><881><360><911>] is no-damage." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Individual building damage assessment", + "Answer Choices": [ + "(A) No-damaged", + "(B) Minor damaged", + "(C) Major damaged", + "(D) Fully destroyed", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000524_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Multi-image_individual_visual_localization_task.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Multi-image_individual_visual_localization_task.json new file mode 100644 index 0000000000000000000000000000000000000000..471a049f8216b6aa9d10809a78fa67152cd7a6d8 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Multi-image_individual_visual_localization_task.json @@ -0,0 +1,3167 @@ +[ + { + "Question_id": "Multi-image individual visual localization task/0000", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This building is located in the lower left corner of the entire picture, with slight cracks in the walls and roof. And it is surrounded by green plants.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are18 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 13undamaged buildings and 5 minjor-damage buildings.", + "Step 3: In image 1, This building is located in the bottom left corner ofthe entire picture.", + "Step 4: In image 1, There is a small river on the left side of thisbuilding.", + "Step 5: In image 2, This building has a green roof.", + "Step 6: In image 2, There are slight cracks on the roof and walls of thisbuilding.", + "Step 7: Bounding Box -[<91><295><181><402>] is the Minor damaged." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<91><295><181><402>]", + "(B) Bounding Box -[<28><298><59><378>]", + "(C) Bounding Box -[<216><316><246><368>]", + "(D) Bounding Box -[<86><206><133><236>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000344_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0001", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This building is located in the lower right corner of the entire picture, with obvious cracks in the walls and roof, forming a parallelogrampattern. The roof is half white and half green, and there is a sandy area onthe right side.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are100 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 88major-damage buildings and 7 destroyed buildings and 5 unclassifiedbuildings.", + "Step 3: In image 1, There is a sandy land on its right side.", + "Step 4: In image 1, There is a rectangular building above it.", + "Step 5: In image 2, There are obvious cracks on the roof and walls.", + "Step 6: In image 2, this building is major-damaged.", + "Step 7: Bounding Box -[<568><641><646><759>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<568><641><646><759>]", + "(B) Bounding Box -[<629><539><669><581>]", + "(C) Bounding Box -[<395><627><445><673>]", + "(D) Bounding Box -[<597><801><681><843>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000361_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000361_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0002", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located at the bottom left of the entire picture,with a main road on its left and a forest on its right. Its roof and wallshave obvious cracks", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 149 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 139 major-damage buildings and 10 destroyed buildings.", + "Step 3: In image 1, there are some buildings located at the bottom left of the entire picture.", + "Step 4: In image 1,there is a building has a green rectangular roof with a similar building above it.", + "Step 5: In image 2, the roof and walls has obvious cracks.", + "Step 6: In image 2, this building is major-damage.", + "Step 7: Bounding Box -[<443><999><484><1022>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<443><999><484><1022>]", + "(B) Bounding Box -[<154><843><210><904>]", + "(C) Bounding Box -[<133><724><209><783>]", + "(D) Bounding Box -[<271><975><337><1011>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000365_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0003", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the lower left corner of the entire picture, with a green rectangular roof and no cracks. To the right is a roadintersection.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 156 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 156 undamaged buildings.", + "Step 3: In image 1, there are some buildings located in the lower left corner of the entire picture.", + "Step 4: In image 1, there is a building has a green rectangular roof with no cracks, and to the right is a road intersection.", + "Step 5: In image 2, the roof and walls of this building are intact without cracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<198><642><352><690>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<198><642><352><690>]", + "(B) Bounding Box -[<410><694><454><788>]", + "(C) Bounding Box -[<566><782><638><858>]", + "(D) Bounding Box -[<408><900><482><960>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000366_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000366_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0004", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape Above it is a wide highway.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are79 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 79undamaged building.", + "Step 3: In image 1, there are some buildings located in the lower leftcorner of the entire picture and is a rectangular building with a white roof.", + "Step 4: In image 1, Above the building is a very wide highway.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<0><761><181><829>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><761><181><829>]", + "(B) Bounding Box -[<213><683><271><735>]", + "(C) Bounding Box -[<365><703><411><733>]", + "(D) Bounding Box -[<465><699><503><743>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000367_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000367_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0005", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located above the road, undamaged, rectangular inshape, and is the largest red roofed building.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are134 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are134 undamaged buildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the picture.", + "Step 4: In image 1, there is a building has a red roof and an H-shapedstructure below ", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<540><182><595><265>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<540><182><595><265>]", + "(B) Bounding Box -[<532><301><567><351>]", + "(C) Bounding Box -[<609><291><662><374>]", + "(D) Bounding Box -[<702><309><739><334>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000379_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000379_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0006", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the lower left corner of the picture,undamaged, on the right side of the highway, and is the largest white roofedbuilding.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are43 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 3: In image 1, there are 3 buildings located in the lower leftcorner of the picture.", + "Step 4: In image 1, there is a building the largest white roofed buildingon the right side of the highway.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<43><574><278><867>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<43><574><278><867>]", + "(B) Bounding Box -[<290><640><325><658>]", + "(C) Bounding Box -[<305><680><332><720>]", + "(D) Bounding Box -[<300><743><340><770>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000380_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000380_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0007", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the lower right corner of the entire picture, undamaged, with a triangular roof, making it the smallest building.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are63 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 63undamaged buildings.", + "Step 3: In image 1, there are some buildings located in the lower rightcorner of the entire picture.", + "Step 4: In image 1, there is a building is the smallest triangularbuilding.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<987><0><1024><25>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<987><0><1024><25>]", + "(B) Bounding Box -[<504><19><571><79>]", + "(C) Bounding Box -[<504><121><569><194>]", + "(D) Bounding Box -[<506><274><579><346>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000396_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000396_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0008", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner ofimage1 pre_disaster. The building is No-damaged and located on the upper sideof the straight road ,with a rectangular shape. Around this building, there isa row of rectangular buildings similar to it, and it is located at the end ofthis row of buildings.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 41buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 41undamaged buildings", + "Step 3: In image 1, there are 15 buildings located in the upper right cornerof the picture.", + "Step 4: In image 1, there is a building located on the upper side of thestraight road. Around this building, there is a row of rectangular buildingssimilar to it, and it is at the end of this row of buildings.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<996><0><1024><48>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<284><116><357><189>]", + "(B) Bounding Box -[<128><106><231><146>]", + "(C) Bounding Box -[<996><0><1024><48>]", + "(D) Bounding Box -[<134><631><195><684>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000374_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000374_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0009", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This building is located above the road, undamaged, H-shaped, andhas a white roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are104 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are104 undamaged buildings.", + "Step 3: In image 1, there are some buildings in the upper left corner ofthe image.", + "Step 4: In image 1, there is an H-shaped building with a white roof here", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<0><0><156><140>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><0><156><140>]", + "(B) Bounding Box -[<58><202><76><224>]", + "(C) Bounding Box -[<136><222><174><254>]", + "(D) Bounding Box -[<234><232><262><258>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000413_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000413_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0010", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of theimage1 pre_disaster. The building is more damaged and is located on the leftside of the road in an inverted U-shape. This building is the smaller in thewhole picture.", + "CoT": [ + "Step 1: There's a river in the bottom left corner of the picture, and there'sa building below the river.", + "Step 2: An image is a photo taken after a disaster. There are 1 undamaged and1 unclassified and 186 severely damaged and 7 completely damaged.", + "Step 3: In Figure 1, there are 3 buildings in the lower left corner of theimage.", + "Step 4:In Figure 1, there are smaller buildings in the lower left corner ofthe river channel.", + "Step 5:In Figure 2, the roof and walls of this building are severely damaged,with many cracks, and the building is severely deformed or tilted.", + "Step 6: In image 2, this building is major-damage.", + "Step 7: Bounding Box -[<77><969><134><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<77><969><134><1024>]", + "(B) Bounding Box -[<673><563><708><594>]", + "(C) Bounding Box -[<652><779><739><809>]", + "(D) Bounding Box -[<648><814><744><847>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000434_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000434_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0011", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of the image1pre_disaster. The building is undamaged and is located in the middle of tworoads in a V-shaped. This building is the largest V-shaped building in thewhole map, and it is connected to the road on the left and right.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 158buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 137major-damage buildings and 21 minor-damage buildings.", + "Step 3: In image 1,Junction Y is on the left side of the image.", + "Step 4: In image 1, There is a V-shaped building underneath theintersection.", + "Step 5: In image 2, The roof and walls of the building are not intact, thereare a little cracks, and the building is a little deformed or tilted.", + "Step 6: In image 2, this building is minor-damage.", + "Step 7: Bounding Box -[<129><401><310><560>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<129><401><310><560>]", + "(B) Bounding Box -[<0><1><60><62>]", + "(C) Bounding Box -[<0><65><46><114>]", + "(D) Bounding Box -[<0><164><43><212>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000435_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0012", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the middle of the left side of image1pre_disaster.The building is No-damaged and located upper the grassland, witha rectangular shape.This building has a similar rectangular structure upperit.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 89buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 87undamaged buildings and 2 minor damaged buildings.", + "Step 3: In image 1, there are some buildings located in the middle of theleft side of the entire picture.", + "Step 4: In image 1, there is a building located upper the grassland. Upperit, there is a rectangular building similar to it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<42><416><113><448>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<54><497><148><555>]", + "(B) Bounding Box -[<439><309><478><349>]", + "(C) Bounding Box -[<42><416><113><448>]", + "(D) Bounding Box -[<188><493><252><548>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000443_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000443_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0013", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of the image1pre_disaster. The building is more damaged and is located on the left side ofthe river channel in the lower left corner, which is L-shaped. There is awhite roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 103buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 99buildings that were badly damaged and 4 that were completely damaged.", + "Step 3: In image 1,there are some buildings on the left side of the image.", + "Step 4: In image 1, There is a river channel in the lower left corner of theimage, with some buildings on the left side of the river and an L-shapedbuilding with a white roof on the left side of the river.", + "Step 5: In image 2,The roof and walls of this building were badly damaged,there were severe cracks, and the building was also heavily deformed ortilted.", + "Step 6: In image 2, this building is major-damage.", + "Step 7: Bounding Box -[<0><637><51><742>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><637><51><742>]", + "(B) Bounding Box -[<75><462><131><542>]", + "(C) Bounding Box -[<355><516><427><577>]", + "(D) Bounding Box -[<418><422><465><473>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000463_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000463_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0014", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located at the upper right edge before thedisaster in Image 1. The building was slightly damaged. It was square on theroad and had an irregular shape. This building is at the edge of the picture.There are no other buildings around it and it is separated from the buildingbelow by a road.", + "CoT": [ + "Step 1:Image 1 is a photo taken before the disaster occurred. There are 94buildings.", + "Step 2:Image 2 is a photo taken after the disaster occurred. There are 7minor-damage buildings and 87 major-damage buildings.", + "Step 3:In image 1,There are eight buildings in the lower right corner ofthe picture.", + "Step 4:In image 1,on the right edge of the picture,it is surrounded byroads and separated from other buildings.", + "Step 5:In image 2,the roof and walls of this building are slightly damaged,with some cracks. The building is somewhat deformed and tilted.", + "Step 6:In image 2,this building is Minor damaged.", + "Step 7:Bounding Box -[<952><319><1020><387>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<952><319><1020><387>]", + "(B) Bounding Box -[<692><891><750><957>]", + "(C) Bounding Box -[<783><933><846><981>]", + "(D) Bounding Box -[<246><846><312><914>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000471_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000471_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0015", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the right before the disasterin Image 1. The building is badly damaged and is located in the lower right ofthe road in a rectangular shape. The building is the largest on the right ofthe picture and is close to the road.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 37buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 33major-damage buildings,3 minor-damage buildings and 1 destroyed.", + "Step 3: In image 1, there are four buildings in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the lower right cornerof the intersection.", + "Step 5: In Image 2, the building's roof and walls are severely damaged,cracked, and the building is deformed or tilted.", + "Step 6: In image 2, this building is major-damage.", + "Step 7: Bounding Box -[<953><551><997><662>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<953><551><997><662>]", + "(B) Bounding Box -[<141><295><198><331>]", + "(C) Bounding Box -[<269><308><358><339>]", + "(D) Bounding Box -[<461><317><546><350>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000470_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0016", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of image1pre_disaster. The building is fully destroyed and trapezoidal. This buildingis the first one from left to right at the very top of the entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 35buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 1undamaged building, 5 minor damaged buildings, 9 major damaged buildings, 16fully destroyed buildings and 4 unclassified buildings.", + "Step 3: In image 1, there are some buildings in the upper left corner of thepicture.", + "Step 4: In image 1, there is a building that is the first one from left toright at the very top of the entire picture.", + "Step 5: In image 2, the building has completely collapsed with no remainingstructural integrity, leaving only rubble and debris.", + "Step 6: In image 2, this building is Fully destroyed.", + "Step 7: Bounding Box -[<58><0><78><13>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<387><102><482><146>]", + "(B) Bounding Box -[<321><463><406><543>]", + "(C) Bounding Box -[<684><168><761><233>]", + "(D) Bounding Box -[<58><0><78><13>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000198_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000198_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0017", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster.The building is minor damaged, located on the lower sideof the green belt, and has a square shape.This building is surrounded in themiddle by an L-shaped building. ", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 47buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 29undamaged buildings, 11 major damaged buildings and 7 minor damagedbuildings.", + "Step 3: In image 1, there are two buildings in the lower right corner of theimage.", + "Step 4: In image 1, there is a building located on the lower side of thegreen belt, surrounded by an L-shaped building in the middle.", + "Step 5: In image 2, the building has slight structural cracks and partialexterior wear, but remains mostly intact.", + "Step 6: In image 2, this building is Minor damaged.", + "Step 7: Bounding Box -[<936><948><1013><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<721><75><826><160>]", + "(B) Bounding Box -[<862><531><982><623>]", + "(C) Bounding Box -[<827><351><861><426>]", + "(D) Bounding Box -[<936><948><1013><1024>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000455_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0018", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is minor damaged and located in the upperleft side of the picture, with a rectangular shape. This building is medium inthe entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 193buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 3destroyed buildings,5 unclassified buildings,6 minor damaged buildings and 179major damaged buildings.", + "Step 3: In image 1, there is a building in the upper left corner of theimage.", + "Step 4: In image 1, there is the smallest building in the upper left cornerof the intersection, and there are buildings surround it.", + "Step 5: In image 2, the roof and walls of this building are intact with somecracks, and the building is little deformed or tilted.", + "Step 6: In image 2, this building is minor damaged.", + "Step 7: Bounding Box -[<86><68><127><97>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<192><227><287><256>]", + "(B) Bounding Box -[<86><68><127><97>]", + "(C) Bounding Box -[<321><26><387><124>]", + "(D) Bounding Box -[<192><227><287><256>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000347_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0019", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 53buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 51undamaged buildings and 2 ,minor damaged buildings.", + "Step 3: In image 1, there is a building in the right corner of the image.", + "Step 4: In image 1, there is the largest building in the upper right cornerof the intersection, and there is a road blow it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<765><270><870><487>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<656><4><1022><28>]", + "(B) Bounding Box -[<919><246><1023><397>]", + "(C) Bounding Box -[<465><444><560><487>]", + "(D) Bounding Box -[<765><270><870><487>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000375_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000375_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0020", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage2 post_disaster. The building is minor damaged and located in the upperside of the intersection, with a rectangular shape. This building is themiddle one in the entire picture, and it is connected to the tree.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 58buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 48minor damaged buildings and 10 destroyed buildings.", + "Step 3: In image 1, there are two buildings in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left corner ofthe intersection, and there are four buildings in the intersection.", + "Step 5: In image 2, the roof and walls of this building are intact withlittle cracks, and the building is deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<75><621><127><649>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<75><621><127><649>]", + "(B) Bounding Box -[<92><655><167><672>]", + "(C) Bounding Box -[<130><630><183><651>]", + "(D) Bounding Box -[<38><701><94><782>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000462_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0021", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire structure is located in the lower left corner ofImage1 pre-disaster. The building is fully destroyed and located in the firstof three buildings on the right side of the road bend, counted from left toright.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 9buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 9fully destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the lower left cornerof the picture.", + "Step 4: In image 1, there is a building positioned leftmost among threestructures right of the road bend.", + "Step 5: In image 2, the building has completely collapsed with no remainingstructural integrity, leaving only rubble and debris.", + "Step 6: In image 2, this building is Fully destroyed.", + "Step 7: Bounding Box -[<343><997><357><1012>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<343><997><357><1012>]", + "(B) Bounding Box -[<267><882><310><910>]", + "(C) Bounding Box -[<459><894><491><944>]", + "(D) Bounding Box -[<306><770><369><827>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000310_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0022", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is minor damaged and trapezoidal. Thisbuilding is the one closest to the lower right corner in the entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 335buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 279minor damaged buildings, 32 major damaged buildings, 18 fully destroyedbuildings and 6 unclassified buildings.", + "Step 3: In image 1, there are some buildings in the lower right corner of thepicture.", + "Step 4: In image 1, there is a building that is closest to the lower rightcorner of the entire picture.", + "Step 5: In image 2, the building has slight structural cracks and partialexterior wear, but remains mostly intact.", + "Step 6: In image 2, this building is Minor damaged.", + "Step 7: Bounding Box -[<1004><1014><1021><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<478><625><525><667>]", + "(B) Bounding Box -[<442><760><461><785>]", + "(C) Bounding Box -[<1004><1014><1021><1024>]", + "(D) Bounding Box -[<347><724><401><767>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000372_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000372_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0023", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is badly damaged and is located on the upperright side of the road. This building is the closest to the road in the firsthalf of the picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 17buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 10undamaged buildings, 3 unclassified buildings, 4 minor—damage buildings and 1major-damage building.", + "Step 3: In image 1, there are 6 similar buildings in the upper right cornerof the image.", + "Step 4: In image 1,in the upper right corner of the image there is a buildingslot that is the shortest distance from the road.", + "Step 5: In image 2, the roof and walls of the building were badly damaged,and the building was severely deformed or tilted.", + "Step 6: In image 2, this building is major-damage.", + "Step 7: Bounding Box -[<723><245><764><297>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<723><245><764><297>]", + "(B) Bounding Box -[<736><162><792><222>]", + "(C) Bounding Box -[<860><130><920><171>]", + "(D) Bounding Box -[<862><813><892><866>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000009_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000009_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0024", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located at the lower right corner ofimage1-pre_disaster. The building is undamaged. It is located in the upperright corner of the picture and is rectangular. There is a building with asimilar shape above this building and a path on its right.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 107buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 79undamaged buildings, 21 minor-damage buildings, 3 major-damage buildings, 1destroyed building and 3 unclassified buildings.", + "Step 3: In image 1, there is a building above and below it.", + "Step 4: In image 1, there is a building with a similar shape above thisbuilding and a path on its right.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<807><107><838><166>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<807><107><838><166>]", + "(B) Bounding Box -[<572><172><633><226>]", + "(C) Bounding Box -[<303><227><352><287>]", + "(D) Bounding Box -[<700><250><730><293>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000016_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0025", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner of theimage1 pre_disaster. The building is No-damaged and located in the left sideof the road, with a rectangular shape. This building is small in the entire picture, and it is connected to the road.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 14buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 3: In image 1, there are two buildings in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left corner ofthe intersection, and there is a small path around it.", + "Step 5: In image 2, the roof and walls of this building are intact with manycracks, and the building is badly deformed or tilted.", + "Step 6: In image 2, this building is major damaged.", + "Step 7: Bounding Box -[<929><200><964><267>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<814><227><869><266>]", + "(B) Bounding Box -[<693><217><775><300>]", + "(C) Bounding Box -[<929><200><964><267>]", + "(D) Bounding Box -[<912><323><963><387>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000035_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0026", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located at the lower left corner of image1pre_disaster. The building is major damaged. It is located in the upper rightcorner of the crossroads and is rectangular. There is an irregular buildingbeneath it.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 19buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 5undamaged buildings, 8 minor damaged buildings, 4 major damaged buildings and2 fully destroyed buildings.", + "Step 3: In image 1, there are two buildings in the upper right corner of thecrossroads.", + "Step 4: In image 1, there is an irregular building beneath a rectangularbuilding.", + "Step 5: In image 2, this building has severe structural collapse, extensivewall breaches, and partial roof failure.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<353><678><383><695>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<375><448><422><496>]", + "(B) Bounding Box -[<496><581><560><633>]", + "(C) Bounding Box -[<353><678><383><695>]", + "(D) Bounding Box -[<646><457><734><557>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000044_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0027", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner ofimage1 pre_disaster. The building is minor damaged and is the lowest of thethree buildings on the left side of the road.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 8buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 1undamaged building and 7 minor damaged buildings.", + "Step 3: In image 1, there are some buildings in the upper right corner of thepicture.", + "Step 4: In image 1, there is a building the lowest of the three buildings onthe left side of the road.", + "Step 5: In image 2, this building has slight structural cracks and partialexterior wear, but remains mostly intact.", + "Step 6: In image 2, this building is Minor damaged.", + "Step 7: Bounding Box -[<845><321><914><408>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<845><321><914><408>]", + "(B) Bounding Box -[<480><259><606><316>]", + "(C) Bounding Box -[<668><236><732><276>]", + "(D) Bounding Box -[<985><267><1024><313>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000130_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0028", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster.The building is undamaged and is located below the curvedroad in a rectangular shape. This building is the largest in the whole map.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 82buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 69undamaged buildings, 1 unclassified building, 11 slightly damaged buildings,and 1 severely damaged building.", + "Step 3: In image 1, there are 10 buildings in the lower right corner of theimage.", + "Step 4: In image 1,There is the largest building below the arc.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<762><670><896><774>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<762><670><896><774>]", + "(B) Bounding Box -[<595><298><629><362>]", + "(C) Bounding Box -[<666><298><696><359>]", + "(D) Bounding Box -[<746><329><789><376>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000147_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0029", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is No-damaged and located in the upper side of theroad,with a rectangular shape.On the right side of this building,there aretwo rectangular buildings with similar areas and shapes,and the rectangularareas of these two buildings are opposite.", + "CoT": [ + "Step 1:Image 1 is a photo taken before the disaster occurred. There are 94buildings.", + "Step 2:Image 2 is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 3:In image 1,there are many buildings in the upper corner of theimage.", + "Step 4:In image 1,there is the largest building in the upper corner of theintersection,except for two opposing and similar rectangular buildings. ", + "Step 5:In image 2,the roof and walls of this building are intact withoutcracks,and the building is not deformed or tilted.", + "Step 6:In image 2,this building is No-damaged.", + "Step 7:Bounding Box -[<563><67><665><334>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<563><67><665><334>]", + "(B) Bounding Box -[<172><398><202><438>]", + "(C) Bounding Box -[<157><538><203><683>]", + "(D) Bounding Box -[<556><834><629><901>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000418_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0030", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the right of the image1 ，thebuilding has major damage，the building is located above the river in themiddle of the picture,and to the left of it is a row of similar buildings,and it is the last of the row.", + "CoT": [ + "Step 1:Image 1 is a photo taken before the disaster occurred. There are 210buildings.", + "Step 2:Image 2 is a photo taken after the disaster occurred. There are 210major-damged buildings.", + "Step 3:In image 1,in the middle of the picture,there are some buildings,and below them is the largest river in the picture,which flows in an east-west direction.", + "Step 4:In image 1,In this row of buildings,counted from left to right,itis the rightmost one.", + "Step 5:In image 2,the roof of the building has large cracks and the wallshave slight collapses.", + "Step 6:In image 2,this building is major-damaged.", + "Step 7:Bounding Box -[<990><284><1024><323>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<990><284><1024><323>]", + "(B) Bounding Box -[<599><323><639><369>]", + "(C) Bounding Box -[<658><497><698><534>]", + "(D) Bounding Box -[<672><591><728><646>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000502_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000502_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0031", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left of the image1pre_disaster. The building is No-damaged and is square in shape and issurrounded by forests.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 8buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 5undamaged buildings ,2 minor-damaged buildings and 1 unclassified building.", + "Step 3: In image 1,this building is located in the lower left part of thepicture.", + "Step 4: In image 1,this building is the only square building in the lowerleft corner of the graphic.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<140><886><162><904>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<140><886><162><904>]", + "(B) Bounding Box -[<195><829><282><901>]", + "(C) Bounding Box -[<62><792><70><867>]", + "(D) Bounding Box -[<227><613><608><632>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000365_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0032", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the left sideof the image , with a Irregular shape.In this area there is a teardrop-shaped river, and each branch of the riverhas a building, which is the lowest building of the drop-shaped branch.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 35buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 31minor damaged buildings ,2 fully destroyed building and 3 major damagedbuildings.", + "Step 3: In image 1，there are many building on the left side of thepicture.", + "Step 4: In image 1, within this area, there is a large open space underneathit, and to the left is a 7-sided building.", + "Step 5: In image 2, the roof of the building is not damaged, but there areslight cracks on the walls.", + "Step 6: In image 2, this building is minor-damaged.", + "Step 7: Bounding Box -[<124><545><180><600>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<124><545><180><600>]", + "(B) Bounding Box -[<267><395><309><482>]", + "(C) Bounding Box -[<145><363><192><417>]", + "(D) Bounding Box -[<24><449><75><504>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000003_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000003_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0033", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is No-damaged,The building is rectangularin shape and has a grey roof", + "CoT": [ + "Step 1:Image 1 is a photo taken before the disaster occurred. There are 93buildings.", + "Step 2:Image 2 is a photo taken after the disaster occurred. There are 20minor-damaged buildings ，67 no-damaged buildings. ，4 major damaged buildings,1destroyed building and 1 un-classified building", + "Step 3:In image 1,there are some buildings here in the lower left cornerof the picture,", + "Step 4:In image 1,within this area,it is surrounded by forests,and thereare no buildings to its left or below.", + "Step 5:In image 2,the roof and walls of this building are intact withoutcracks,and the building is not deformed or tilted.", + "Step 6:In image 2,this building is No-damaged.", + "Step 7:Bounding Box -[<54><789><122><823>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<54><789><122><823>]", + "(B) Bounding Box -[<25><459><84><493>]", + "(C) Bounding Box -[<191><463><231><500>]", + "(D) Bounding Box -[<329><578><354><617>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000072_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0034", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is No-damaged and located in the bottom sideof the road, with a rectangular shape. This building is the largest in theintersection, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 89buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 59undamaged buildings,15 minor damaged buildings,11 major damaged buildings ,3destroyed buildings and 1 unclassified building.", + "Step 3: In image 1, there are 7 buildings in the lower left corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper right cornerof the intersection, and there is a small road above it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<154><934><218><969>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<70><948><82><967>]", + "(B) Bounding Box -[<0><948><29><975>]", + "(C) Bounding Box -[<154><934><218><969>]", + "(D) Bounding Box -[<173><1010><220><1024>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000152_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000152_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0035", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of Image 1pre_disaster. The building was completely destroyed and was located on theright side of the road in a rectangular shape. This building is the smallestin the entire frame.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 15buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 6minor-damage buildings,5 major-damage buildings,2 no-damage buildings and 2destroyed buildings.", + "Step 3:In image 1, there are six buildings on the right side of the road.", + "Step 4: In Image 1, the smallest building is located in the lower rightcorner of the intersection.", + "Step 5: In Image 2, the roof and walls of the building are completelydestroyed.", + "Step 6: In image 2, this building is destroyed.", + "Step 7: Bounding Box -[<269><557><291><582>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<269><557><291><582>]", + "(B) Bounding Box -[<433><513><454><535>]", + "(C) Bounding Box -[<376><618><408><647>]", + "(D) Bounding Box -[<381><398><403><420>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000151_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0036", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located at the lower left corner ofimage1-pre_disaster. The building is undamaged, located beneath the road andrectangular in shape. This building is located to the right of the largestbuilding in the entire picture and it is connected to the road through a smallpath below.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 25buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 21undamaged buildings, 2 major-damage buildings and 2 minor-damage buildings.", + "Step 3: In image 1, there are some buildings in the lower left corner of thepicture.", + "Step 4: In image 1, this building is located to the right of the largestbuilding in the entire picture and it is connected to the road through a smallpath below.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<297><815><327><845>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<297><815><327><845>]", + "(B) Bounding Box -[<611><815><641><831>]", + "(C) Bounding Box -[<727><741><793><783>]", + "(D) Bounding Box -[<713><909><739><941>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000183_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0037", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner of theimage1 pre_disaster. The building is Nodamaged and ,the building with thelargest area is located in the upper right corner with a square shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 88buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 50undamaged buildings ,23 minor-damaged buildings,7 major damaged buildings,6fully destroyed buildings and 2 unclassified buildings", + "Step 3: In image 1, there are many buildings in the upper right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left cornerof the intersection.", + "Step 5: In image 2, The roof of the building is not damaged, but there areslight cracks on the walls.", + "Step 6: In image 2, this building is minor damaged.", + "Step 7: Bounding Box -[<947><31><1024><100>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<947><31><1024><100>]", + "(B) Bounding Box -[<984><310><1010><329>]", + "(C) Bounding Box -[<369><344><396><374>]", + "(D) Bounding Box -[<285><413><321><434>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000253_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000253_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0038", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of image1pre_disaster. The building is No-damage and rectangular, located on the upperside of the road, and is the largest structure in the area by floor area.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 113buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 65undamaged buildings, 42 minor damaged buildings and 6 major damagedbuildings.", + "Step 3: In image 1, there are some buildings located in the upper left cornerof the picture.", + "Step 4: In image 1, there is a rectangular building upper the road, which isthe largest building in this area.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<0><225><98><300>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<573><154><666><205>]", + "(B) Bounding Box -[<194><220><237><282>]", + "(C) Bounding Box -[<0><225><98><300>]", + "(D) Bounding Box -[<619><286><661><337>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000181_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0039", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the right side of the river. Thebuilding, which was rectangular in shape, was completely destroyed,.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are10 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 4minor-damaged buildings and 1 unclassified buildings and 5destroyedbuildings.", + "Step 3: In image 1, there are 3 buildings located in the bottom leftcorner of the picture.", + "Step 4: In image 1, there is a building located on the right side of theriver.", + "Step 5: In image 2, the roof and walls of this building were completelydestroyed.", + "Step 6: In image 2, this building is destroyed.", + "Step 7: Bounding Box -[<263><631><291><659>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<263><631><291><659>]", + "(B) Bounding Box -[<309><392><348><437>]", + "(C) Bounding Box -[<368><487><451><559>]", + "(D) Bounding Box -[<466><314><506><375>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000190_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0040", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the center of the forest, the buildinghas obvious cracks on its walls and roof, forming a rectangular shape. Thisbuilding is the largest rectangle in the entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are23 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 8major-damaged buildings and 1 unclassified buildings and 10 destroyedbuildings and 4 minor-damage buildings.", + "Step 3: In image 1,There are some buildings located in the center of theimage.", + "Step 4: In image 1,There is a building with the largest rectangular greenroof.", + "Step 5: In image 2,There are obvious cracks on the walls and roof of thisbuilding.", + "Step 6: In image 2, this building is major-damaged.", + "Step 7: Bounding Box -[<229><417><263><447>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<229><417><263><447>]", + "(B) Bounding Box -[<112><559><136><584>]", + "(C) Bounding Box -[<174><608><192><647>]", + "(D) Bounding Box -[<97><668><127><705>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000221_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000221_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0041", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located on the right side of the road and isundamaged. It is the smallest L-shaped white roofed building.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are101 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred.There are 10undamaged buildings and 9 unclassified buildings and 67 minor-damge buildingsand 12 major-damage buildings and 3 destryed buildings.", + "Step 3: In image 1, there is a building in the upper right corner of theimage.", + "Step 4: In image 1, there is a building is the smallest L-shaped whiteroofed building located on the right side of the road.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<422><367><467><412>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<422><367><467><412>]", + "(B) Bounding Box -[<181><708><253><776>]", + "(C) Bounding Box -[<49><793><91><826>]", + "(D) Bounding Box -[<153><848><181><882>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000278_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0042", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located on an open space between two roads, with aroad intersection on the right side. The building is undamaged and has anL-shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are54 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred.There are 43undamaged buildings and 1 unclassified buildings and10 minor-damagebuildings.", + "Step 3: In image 1, There are some buildings located in the upper leftcorner of the image.", + "Step 4: In image 1, There is an L-shaped building and to its right is aroad intersection.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<304><488><351><548>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<304><488><351><548>]", + "(B) Bounding Box -[<441><475><478><502>]", + "(C) Bounding Box -[<561><467><591><495>]", + "(D) Bounding Box -[<691><435><741><479>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000000_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0043", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the right side of the road. Thebuilding is undamaged, rectangular in shape, and has a reddish brown roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are102 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 77undamaged buildings and 1 unclassified buildings and 4major-damage buildingsand 18 minor-damage buidlings and 2 destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the bottom rightcorner of the image.", + "Step 4: In image 1, there is a building with a rectangular reddish brownroof.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<619><937><650><967>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<619><937><650><967>]", + "(B) Bounding Box -[<673><893><705><933>]", + "(C) Bounding Box -[<677><963><705><983>]", + "(D) Bounding Box -[<573><979><611><1005>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000014_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000014_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0044", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the green belt in the center ofthe town. The building is undamaged and rectangular in shape. This buildinghas a reddish brown roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are36 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 12undamaged buildings and 1 unclassified buildings and 4 major-damage buildingsand 18 minor-damage buildings and 1 destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the upper leftcorner of the image.", + "Step 4: In image 1, there is a building with a rectangular reddish brownroof located on the green belt in the center of the town.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<83><387><147><458>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<83><387><147><458>]", + "(B) Bounding Box -[<50><310><76><352>]", + "(C) Bounding Box -[<104><358><147><387>]", + "(D) Bounding Box -[<184><418><208><434>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000034_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000034_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0045", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of the town. Theroof and walls of the building have slight cracks in a conical shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are57 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 44undamaged buildings and 9 minor-damage buildings and 4 major-damagebuildings.", + "Step 3: In image 1, there are some buildings located in the upper leftcorner of the image.", + "Step 4: In image 1, there is a building with a green conical roof locatedon the left side of the town.", + "Step 5: In image 2, there are slight cracks on the walls and roof of abuilding.", + "Step 6: In image 2, this building is minor-damaged.", + "Step 7: Bounding Box -[<0><3><38><98>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><3><38><98>]", + "(B) Bounding Box -[<64><235><135><357>]", + "(C) Bounding Box -[<90><447><142><515>]", + "(D) Bounding Box -[<205><515><250><585>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000056_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0046", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of the road. Thebuilding is undamaged and has a triangular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are75 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 54undamaged buildings and 14 minor-damage buildings and 6 major-damage buildingsand 1 destroyed building.", + "Step 3: In image 1, there are buildings located in the upper left cornerof the image.", + "Step 4: In image 1, There is a building with the largest triangular whiteroof.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<72><0><172><41>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<72><0><172><41>]", + "(B) Bounding Box -[<228><182><300><243>]", + "(C) Bounding Box -[<395><255><440><324>]", + "(D) Bounding Box -[<496><337><541><398>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000142_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0047", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the left side of the parkinglot on the left side of the highway. The building is undamaged and rectangularin shape. There is a very wide gray roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are102 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 70undamaged buildings and 10 major-damage buildings and 22 minor-damagebuildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the image.", + "Step 4: In image 1, there is a building located on the left side of theparking lot, which is a rectangular building with a very wide gray roof.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<629><0><771><139>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<629><0><771><139>]", + "(B) Bounding Box -[<868><91><951><171>]", + "(C) Bounding Box -[<908><271><1008><364>]", + "(D) Bounding Box -[<958><481><1016><574>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000146_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0048", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner of thepicture. The building is undamaged and located on the left side of the highwayon the right side of the road, in an L-shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are66 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 11undamaged buildings and 1 unclassified buildings and 23 destroyed buildingsand 21 minor-damage buildings and 10 major-damage buildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the image.", + "Step 4: In image 1, There is a building located on the left side of thehighway on the right, with an L-shaped gray roof.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<799><8><886><63>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<799><8><886><63>]", + "(B) Bounding Box -[<926><129><973><177>]", + "(C) Bounding Box -[<970><49><1013><82>]", + "(D) Bounding Box -[<1008><149><1024><199>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000165_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0049", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner of theintersection. The building is undamaged and has an L-shape. There is a whiteroof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are144 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred.There are 66undamaged buildings and 5 major-damage buildings and 69 minor-damagebuildings and 4 destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the image.", + "Step 4: In image 1, there is a building with an L-shaped white rooflocated in the upper right corner of the intersection.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<980><446><1024><487>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<980><446><1024><487>]", + "(B) Bounding Box -[<604><286><658><366>]", + "(C) Bounding Box -[<604><406><642><430>]", + "(D) Bounding Box -[<514><448><550><502>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000266_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0050", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the upper left corner of the diagramand is the largest rectangle in terms of area.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 19buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 10undamaged buildings and 3 major damaged buildings and 4 minor damagedbuildings and 2 unclassified buildings.", + "Step 3: In image 1, there are building in the upper left corner of thepicture.", + "Step 4: In image 1, there is a building in the upper left corner of thepicture and it is the largest rectangle in terms of area.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<0><0><253><140>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><0><253><140>]", + "(B) Bounding Box -[<579><47><611><97>]", + "(C) Bounding Box -[<647><0><687><41>]", + "(D) Bounding Box -[<564><6><593><28>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000261_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000261_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0051", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the bottom left corner of the diagramand is the largest building in terms of area.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 26buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 1undamaged buildings and 7 major damaged buildings and 14 minor damagedbuildingsand 4 destroyed buildings.", + "Step 3: In image 1, there are building in the bottom left corner of thepicture.", + "Step 4: In image 1, in the bottom left corner of the picture, there is abuilding with the largest area.", + "Step 5: In image 2, the roof and walls of this building are slight cracks.", + "Step 6: In image 2, this building is Minor damaged.", + "Step 7: Bounding Box -[<21><846><86><922>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<21><846><86><922>]", + "(B) Bounding Box -[<428><808><460><843>]", + "(C) Bounding Box -[<475><810><513><840>]", + "(D) Bounding Box -[<215><456><232><491>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000200_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000200_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0052", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the middle of the picture, closest tothe right and close to the small river, and presents the longest rectangle.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 124buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 14major damaged buildings and 2 minor damaged buildings and 108 destroyedbuildings.", + "Step 3: In image 1, there are building on the far right in the middle of thepicture.", + "Step 4: In image 1, in the middle right of the picture, there is a buildingnear the small river and it is the longest rectangle.", + "Step 5: In image 2, the roof and walls of this building are obvious cracks.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<0><361><60><400>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><361><60><400>]", + "(B) Bounding Box -[<261><527><297><561>]", + "(C) Bounding Box -[<292><448><329><484>]", + "(D) Bounding Box -[<156><537><191><559>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000385_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000385_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0053", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description:- The building is located in the upper right corner of thediagram, close to the road on the right side, and presents the largestT-shaped shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 99buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 33minor damaged buildings and 10 major damaged buildings and 54 undamagedbuildings and 2 destroyed buildings.", + "Step 3: In image 1, there are building near the right side road in the upperright corner of the picture.", + "Step 4: In image 1, in the upper right corner of the picture, there is abuilding near the right road and it presents the largest T-shaped shape.", + "Step 5: In image 2, the roof and walls of this building are obvious cracks.", + "Step 6: In image 2, this building is major damaged.", + "Step 7: Bounding Box -[<686><147><851><289>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<686><147><851><289>]", + "(B) Bounding Box -[<383><854><468><925>]", + "(C) Bounding Box -[<296><869><348><925>]", + "(D) Bounding Box -[<63><867><114><920>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000051_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0054", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the middle of the diagram, theleftmost and longest rectangle.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 54buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 37undamaged buildings and 15 minor damage buildings and 2 destroyed buildingsand 2 unclassified buildings.", + "Step 3: In image 1, there are building in the middle left part of thepicture.", + "Step 4: In image 1, in the middle of the picture, there is a building on theleft and the longest rectangle.", + "Step 5: In image 2, has a complete roof and upright walls without any gaps.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<18><502><77><552>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<18><502><77><552>]", + "(B) Bounding Box -[<76><18><93><48>]", + "(C) Bounding Box -[<30><25><43><56>]", + "(D) Bounding Box -[<44><76><63><106>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000335_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0055", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the lower right corner of the picturenear the road and has a roughly triangular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 13buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 2undamaged buildings and 4 minor damaged buildings and 6 major damagedbuildings and 1 destroyed building.", + "Step 3: In image 1, there are building in the bottom right corner of thepicture.", + "Step 4: In image 1, in the bottom right corner of the picture, there is abuilding near the road and it appears in a roughly triangular shape.", + "Step 5: In image 2, the roof and walls of this building are obvious cracks.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<950><695><1024><881>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<950><695><1024><881>]", + "(B) Bounding Box -[<79><808><104><905>]", + "(C) Bounding Box -[<82><480><143><568>]", + "(D) Bounding Box -[<64><740><124><800>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000124_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000124_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0056", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the upper left corner of the diagramand is the longest rectangle.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 33buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 6major damaged buildings and 8 minor damaged buildings and 17 destroyedbuildings and 2 unclassified buildings.", + "Step 3: In image 1, there are building in the upper left corner of thepicture.", + "Step 4: In image 1, there is a building in the upper left corner of thepicture, and the shape presented is the longest rectangle.", + "Step 5: In image 2, the roof and walls of this building are obvious cracks.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<290><174><330><208>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<290><174><330><208>]", + "(B) Bounding Box -[<511><904><528><926>]", + "(C) Bounding Box -[<339><667><363><687>]", + "(D) Bounding Box -[<695><587><719><615>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000231_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0057", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. The building is located on the rightside of the narrowest path in the bottom right corner of the picture and isthe longest square.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 48buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 34no-damaged buildings and 14 major-damage buildings.", + "Step 3: In image 1, There are many buildings in the lower right part of thepicture.", + "Step 4: In image 1, In the lower right part of the picture, there is abuilding near a narrow road, and the shape of the building is the longestrectangle.", + "Step 5: In image 2, There are obvious cracks on the roof and walls.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<803><605><874><690>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<206><520><228><554>]", + "(B) Bounding Box -[<34><469><72><517>]", + "(C) Bounding Box -[<803><605><874><690>]", + "(D) Bounding Box -[<905><832><947><879>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000338_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000338_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0058", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: In the upper right part of the picture, there is a building thatis the highest and the smallest.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 142buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 9 no-damaged buildings and 1 major damaged building and 132 minor damaged buildings.", + "Step 3: In image 1, There is a building in the top right part of thepicture.", + "Step 4: In image 1, In the top right part of the picture, there is abuilding, and the building that is closest to the top is still the smallestbuilding.", + "Step 5: In image 2, The building has minor roof and wall damage.", + "Step 6: In image 2, this building is Minor damaged.", + "Step 7: Bounding Box -[<121><105><167><124>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0059", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 257buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 257undamaged buildings and 3 unclassified buildings.", + "Step 3: In image 1, There are buildings on the T-shaped road near the road.", + "Step 4: In image 1, There is a T-shaped road near the road, which is dividedinto left and right branches. The building is ranked first in the left branchin order from left to right.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<1><371><37><443>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<531><25><597><113>]", + "(B) Bounding Box -[<255><877><351><933>]", + "(C) Bounding Box -[<1><371><37><443>]", + "(D) Bounding Box -[<995><295><1023><387>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000452_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0060", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 177buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 114major damaged buildings and 60 minor damaged buildings and 2 unclassifiedbuildings and 1 destroyed building.", + "Step 3: In image 1, there are building in the leftmost part of the picture.", + "Step 4: In image 1, there is a building in the leftmost part of the picture,and the building is the longest rectangle.", + "Step 5: In image 2, the roof and walls of this building are obvious cracks,and the building is major damaged.", + "Step 6: In image 2, this building is Major damaged.", + "Step 7: Bounding Box -[<159><601><295><789>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><826><15><876>]", + "(B) Bounding Box -[<42><961><154><1024>]", + "(C) Bounding Box -[<949><0><1012><19>]", + "(D) Bounding Box -[<159><601><295><789>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000491_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000491_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0061", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo,Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the lower left corner of the pictureand is undamaged. It is situated on the right side of the green belt,which isa highway. It is a rectangular white roofed building.", + "CoT": [ + "Step 1:Image 1 is a photo taken before the disaster occurred. There are20 buildings.", + "Step 2:Image 2 is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 3:In image 1,there are 8 buildings located in the lower left cornerof the picture.", + "Step 4:In image 1,there is a building situated on a green belt and tothe right is a highway.it has a rectangular white roofed building.", + "Step 5:In image 2,the roof and walls of this building are intact withoutcracks,and the building is not deformed or tilted.", + "Step 6:In image 2,this building is No-damaged.", + "Step 7:Bounding Box -[<421><906><601><1024>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<421><906><601><1024>]", + "(B) Bounding Box -[<669><860><707><936>]", + "(C) Bounding Box -[<685><748><731><800>]", + "(D) Bounding Box -[<743><898><769><956>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000469_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000469_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0062", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the upper left corner of the picture,there are slight cracks on the walls and roof, making it the smallest squaregreen roof building .", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are36 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 2undamaged buildings and 1 unclassified buildings and 33 minor-damagebuildings.", + "Step 3: In image 1, There are many buildings located in the upper leftcorner of the picture.", + "Step 4: In image 1,This building is the smallest square green roofbuilding.", + "Step 5: In image 2,There are slight cracks on the roof of this building.", + "Step 6: In image 2, this building is minor-damaged.", + "Step 7: Bounding Box -[<516><70><534><95>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<516><70><534><95>]", + "(B) Bounding Box -[<595><84><616><119>]", + "(C) Bounding Box -[<598><158><629><196>]", + "(D) Bounding Box -[<669><104><679><144>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000478_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000478_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0063", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located between two roads, undamaged andtriangular in shape. It is a parking lot.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are110 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 86undamaged buildings and 18 major-damage buildings and 6 minor-damgebuildings.", + "Step 3: In image 1, there are some buildings located in the bottom leftcorner of the picture.", + "Step 4: In image 1,there is a building is the largest triangular greenroof structure and serves as a parking lot.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<149><644><313><812>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<149><644><313><812>]", + "(B) Bounding Box -[<431><742><451><796>]", + "(C) Bounding Box -[<403><802><443><872>]", + "(D) Bounding Box -[<407><910><447><960>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000492_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0064", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located on the right side of the road. Thebuilding is undamaged.This building is the largest triangular green roofstructure.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are35 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 35undamaged buildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the image.", + "Step 4: In image 1, There is a building here with the largest triangulargreen roof.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<526><0><637><42>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<526><0><637><42>]", + "(B) Bounding Box -[<737><115><828><182>]", + "(C) Bounding Box -[<821><56><861><93>]", + "(D) Bounding Box -[<863><160><874><249>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000514_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000514_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0065", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located beneath the road,,with a rectangular shape. and it is connected to the road through a smallpath.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 93buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 93undamaged buildings.", + "Step 3: In image 1, there are some buildings here, located in the lower rightcorner of the wide road.", + "Step 4: In image 1, there is a building located at the bottom right of a wideroad, with a trapezoidal roof on its left and a narrow road below it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<901><579><1024><702>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<901><579><1024><702>]", + "(B) Bounding Box -[<790><440><820><470>]", + "(C) Bounding Box -[<769><549><821><624>]", + "(D) Bounding Box -[<932><389><969><450>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000397_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000397_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0066", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is Major-damaged with a rectangular shape.This building is the smallest in the entire map.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 36buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 29destroyed buildings and 7 major damaged buildings.", + "Step 3: In image 1, there are some buildings in the bottom right corner ofthe picture.", + "Step 4: In image 1,there is a white roofed building in the bottom rightcorner of the picture, and to its right is the largest rectangular shapedbuilding in the picture.", + "Step 5: In image 2,this window and door are severely damaged, and there is anadditional hole on the roof.", + "Step 6: In image 2, this building is Major-damaged.", + "Step 7: Bounding Box -[<559><676><593><699>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<559><676><593><699>]", + "(B) Bounding Box -[<358><512><396><551>]", + "(C) Bounding Box -[<823><517><863><556>]", + "(D) Bounding Box -[<854><621><924><706>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000493_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000493_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0067", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located below the road,rectangular in shape, and has an orange roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 80buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 40undamaged buildings 、4 unclassified buildings、31 minor damaged buildings、4major damaged buildings and 1 destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the bottom rightcorner of the picture.", + "Step 4: In image 1, the largest building with a rectangular orange roof islocated in the bottom right corner of the picture.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<460><515><501><568>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<460><515><501><568>]", + "(B) Bounding Box -[<176><271><200><296>]", + "(C) Bounding Box -[<117><281><140><302>]", + "(D) Bounding Box -[<70><291><88><309>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000129_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000129_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0068", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. It is located below the largestbuilding.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 34buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 23undamaged buildings、3 major damaged buildings、6 minor damaged buildings and 2unclassified buildings.", + "Step 3: In image 1, there are some buildings located in the bottom rightcorner of the picture.", + "Step 4: In image 1, there is a rectangular shape below the largest buildingin the entire picture.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<742><876><770><912>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<742><876><770><912>]", + "(B) Bounding Box -[<654><710><671><725>]", + "(C) Bounding Box -[<865><777><897><805>]", + "(D) Bounding Box -[<158><961><170><979>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000364_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000364_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0069", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of theimage1 pre_disaster. The building is No-damaged and located below the road, itis rectangular in shape. There is a row of cars parked in front of thisbuilding, and an office building behind it.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 28buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 22undamaged buildings and 6 minor damaged buildings.", + "Step 3: In image 1, there are some buildings located in the upper left cornerof the picture, below the road.", + "Step 4: In image 1, there is a building located below the left side of theroad, with a square in front of it and a row of cars parked. Behind it is arectangular shaped building.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<349><383><424><422>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<349><383><424><422>]", + "(B) Bounding Box -[<587><146><625><167>]", + "(C) Bounding Box -[<773><129><812><164>]", + "(D) Bounding Box -[<937><220><959><247>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000008_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0070", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of theimage1 pre_disaster. The building is No-damaged and at the intersection of thefirst horizontal road and the vertical road.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 67buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 48undamaged buildings、6 major damaged buildings、9 minor damaged buildings and 4unclassified buildings.", + "Step 3: In image 1, there are some buildings located in the upper left cornerof the picture, on the left side and below the road.", + "Step 4: In image 1, there are some buildings located at the intersection ofthe first horizontal road and the first vertical road, with irregularrectangular shapes.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<0><942><97><1002>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<0><942><97><1002>]", + "(B) Bounding Box -[<69><452><110><505>]", + "(C) Bounding Box -[<167><569><190><591>]", + "(D) Bounding Box -[<307><707><342><741>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000058_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000058_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0071", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 102buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 62undamaged buildings、4 major damaged buildings、35 minor damaged buildings and 1unclassified buildings.", + "Step 3: In image 1, there are some buildings located in the bottom rightcorner of the picture, with rectangular white roofs.", + "Step 4: In image 1, there are some buildings located in the bottom rightcorner of the picture, with white roofs in a rectangular shape. They aresituated in the upper left corner at the intersection of the second horizontalroad from top to bottom and the fifth vertical road from left to right.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<812><534><902><612>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<812><534><902><612>]", + "(B) Bounding Box -[<781><610><799><635>]", + "(C) Bounding Box -[<858><661><878><676>]", + "(D) Bounding Box -[<726><521><758><546>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000202_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000202_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0072", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of theimage1 pre_disaster. The building is No-damaged and located in the left sideof the road, with a rectangular shape. This building is the smallest in theintersection, and it is connected to the road.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 95buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 44undamaged buildings,12 major damaged buildings,4 destroyed buildings,22 minordamaged buildings and 13 unclassified buildings.", + "Step 3: In image 1, there are three buildings in the upper left corner of theimage.", + "Step 4: In image 1, there is the smallest building in the bottom right cornerof the intersection, and there is a small road on its left.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<152><239><172><264>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<141><142><167><184>]", + "(B) Bounding Box -[<152><239><172><264>]", + "(C) Bounding Box -[<113><22><146><55>]", + "(D) Bounding Box -[<0><186><65><219>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000184_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000184_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0073", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of theintersection on the left side of the picture. The building is undamaged andrectangular in shape. This building has a white roof and is the largestbuilding in the lower left corner of the intersection.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are70 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 35undamaged buildings and 18 major-damage buildings and 17 minor-damagebuildings.", + "Step 3: In image 1, there are some buildings located in the bottom leftcorner of the image.", + "Step 4: In image 1, There is a building with the largest white rectangularroof located in the lower left corner of the intersection.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<110><836><186><872>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<110><836><186><872>]", + "(B) Bounding Box -[<154><757><186><787>]", + "(C) Bounding Box -[<232><757><260><785>]", + "(D) Bounding Box -[<240><837><252><883>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000405_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000405_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0074", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The building is located in the upper right corner of the diagramnear the right side road and has a concave shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 50buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 36undamaged buildings and 1 destroyed building and 11 minor damaged buildingsand 2 major damaged buidings.", + "Step 3: In image 1, there are building in the upper right corner of thepicture.", + "Step 4: In image 1, in the upper right corner of the picture, there is abuilding located near the road on the right side and presenting a concaveshape.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<781><364><830><427>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<781><364><830><427>]", + "(B) Bounding Box -[<430><960><490><1020>]", + "(C) Bounding Box -[<744><29><795><104>]", + "(D) Bounding Box -[<777><134><804><194>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000454_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0075", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of Image 1pre_disaster. The building is minor damaged and is situated on the lower sideof the main road, presenting a convex shape. This building is connected to themain road via a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are214 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are185 undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower left corner ofthe picture.", + "Step 4: In image 1,there is a building located on the lower side of themain road, in a convex shape. This building is connected to the main road viaa narrow path.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<11><932><47><967>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<300><678><332><692>]", + "(B) Bounding Box -[<393><670><412><683>]", + "(C) Bounding Box -[<11><932><47><967>]", + "(D) Bounding Box -[<295><708><332><722>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000462_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0076", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of theintersection. The building is undamaged, T-shaped, and the largest buildingwith a reddish brown roof in the lower left corner of the intersection.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are93 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred.There are 71undamaged buildings and 5 unclassified buildings and 12 minor-damage buildingsand 4 major buildings and 1 destroyed buildings.", + "Step 3: In image 1, there are some buildings located in the bottom leftcorner of the image.", + "Step 4: In image 1, There is a building with the largest L-shaped reddishbrown roof located in the lower left corner of the intersection.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<73><468><160><558>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<73><468><160><558>]", + "(B) Bounding Box -[<78><632><152><689>]", + "(C) Bounding Box -[<208><656><258><712>]", + "(D) Bounding Box -[<172><602><222><629>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000473_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0077", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower right corner of Image1 pre_disaster. This building is minor damaged and is located on the left sideof the road, presenting an irregular shape. This building is connected to theroad via a narrow path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are155 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are127 undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower right corner ofthe picture.", + "Step 4: In image 1,there is a building located on the left side of theroad, which has an irregular shape. This building is connected to the road viaa narrow path.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<743><977><791><1020>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<841><775><860><782>]", + "(B) Bounding Box -[<811><813><841><825>]", + "(C) Bounding Box -[<743><977><791><1020>]", + "(D) Bounding Box -[<871><834><894><845>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000474_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000474_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0078", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner ofimage1 pre_disaster. The building is no-damaged and round. This building isthe smallest in the entire picture. Close to it and located below it, thereare two similar buildings.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 17buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 14undamaged buildings, 2 minor damaged buildings and 1 major damaged building.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the picture. ", + "Step 4: In image 1, there is a building that is the smallest in this area,with two similar buildings located close to it and directly below it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<698><0><708><8>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<598><37><620><61>]", + "(B) Bounding Box -[<755><74><797><110>]", + "(C) Bounding Box -[<698><0><708><8>]", + "(D) Bounding Box -[<565><83><600><109>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000275_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0079", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located at the lower left corner of image1pre_disaster. The building is no-damaged and located on the left side of theriver, in a rectangular shape. There are no other buildings upper it.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 78buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 55undamaged buildings, 14 minor damaged buildings and 9 major damagedbuildings.", + "Step 3: In image 1, there are some buildings located in the lower left cornerof the picture.", + "Step 4: In image 1, there is a building on the left side of the river. Thereare no other buildings upper it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<43><968><65><1022>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<266><622><309><694>]", + "(B) Bounding Box -[<346><711><393><777>]", + "(C) Bounding Box -[<43><968><65><1022>]", + "(D) Bounding Box -[<562><525><585><551>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000461_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0080", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of Image 1pre_disaster. This building is minor damaged and is situated on the upper sideof the road, presenting an irregular shape. This building is connected to theroad via a narrow path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are34 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 3: In image 1,there are many buildings in the upper left corner ofthe picture.", + "Step 4: In image 1,there is a building located on the upper side of theroad, in an irregular shape. This building is connected to the road via anarrow path.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<104><101><163><141>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<299><94><319><106>]", + "(B) Bounding Box -[<361><101><387><115>]", + "(C) Bounding Box -[<104><101><163><141>]", + "(D) Bounding Box -[<418><92><462><105>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000435_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0081", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower right corner of Image1 pre_disaster. This building has suffered minor damage and is situated on thelower side of the road, presenting a convex shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are24 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 5undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower right corner ofthe picture.", + "Step 4: In image 1,there is a building located on the lower side of theroad, in the shape of a convex form.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<724><946><781><986>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<835><893><846><905>]", + "(B) Bounding Box -[<856><926><870><934>]", + "(C) Bounding Box -[<724><946><781><986>]", + "(D) Bounding Box -[<844><956><862><969>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000265_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0082", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower right corner of Image1 pre_disaster. This building has suffered minor damage and is situated on thelower side of the road, presenting an irregular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred.There are 89buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred.There are 10undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower right corner ofthe picture.", + "Step 4: In image 1,there is a building located beneath the road, which hasan irregular shape.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<631><951><667><976>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<751><936><762><948>]", + "(B) Bounding Box -[<789><937><802><946>]", + "(C) Bounding Box -[<631><951><667><976>]", + "(D) Bounding Box -[<757><961><771><972>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000204_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000204_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0083", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper right corner of Image1 pre_disaster. This building has suffered minor damage and is located on theright side adjacent to the road, presenting an irregular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are69 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 3: In image 1,there are many buildings in the upper right corner ofthe picture.", + "Step 4: In image 1,there is a building located on the right side of theroad, adjacent to it, and it has an irregular shape.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<1004><243><1024><311>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<814><68><837><82>]", + "(B) Bounding Box -[<748><72><773><85>]", + "(C) Bounding Box -[<1004><243><1024><311>]", + "(D) Bounding Box -[<816><104><843><122>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000167_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000167_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0084", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of Image 1pre_disaster. This building is undamaged and is situated on the left side faraway from the crossroads, in a rectangular shape. This building is thesmallest one in the entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are226 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower left corner ofthe picture.", + "Step 4: In image 1,there is a building located on the left side far awayfrom the crossroads, in a rectangular shape. It is the smallest one among thesurrounding buildings.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<91><870><110><885>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<31><673><55><691>]", + "(B) Bounding Box -[<97><675><121><690>]", + "(C) Bounding Box -[<91><870><110><885>]", + "(D) Bounding Box -[<157><670><190><685>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000133_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000133_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0085", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower left corner of Image 1pre_disaster. This building has suffered minor damage and is situated on theleft side of the middle road, presenting an irregular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are24 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 16undamaged buildings.", + "Step 3: In image 1,there are many buildings located in the lower leftcorner of the image.", + "Step 4: In image 1,there is an irregularly-shaped building located on theleft side far away from the middle road. The surrounding buildings arerelatively sparse.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<154><994><205><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<672><796><716><823>]", + "(B) Bounding Box -[<712><888><742><905>]", + "(C) Bounding Box -[<154><994><205><1024>]", + "(D) Bounding Box -[<668><931><691><948>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000039_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000039_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0086", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the lower right corner of Image1 pre_disaster. This building has suffered minor damage and is situated belowthe road, presenting a rectangular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are137 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 42undamaged buildings.", + "Step 3: In image 1,there are many buildings in the lower right corner ofthe image.", + "Step 4: In image 1,there is a building located on the right lower side faraway from the road, and the surrounding buildings are rather dense.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is minor-damaged.", + "Step 7: Bounding Box -[<920><807><943><828>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<721><878><740><894>]", + "(B) Bounding Box -[<735><954><781><967>]", + "(C) Bounding Box -[<920><807><943><828>]", + "(D) Bounding Box -[<775><867><795><881>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000373_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000373_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0087", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of Image 1pre_disaster. This building is minor-damaged and is on the right side of theroad, in a rectangular shape. The building is adjacent to the road throughoutthe entire picture.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are17 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 1undamaged buildings.", + "Step 3: In image 1, there are some buildings located in the upper leftcorner of the picture.", + "Step 4: In image 1, There is a building located on the right side of theroad.", + "Step 5: In image 2, the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2, this building is Minor-damaged.", + "Step 7: Bounding Box -[<430><189><447><210>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<496><118><539><146>]", + "(B) Bounding Box -[<526><192><559><214>]", + "(C) Bounding Box -[<430><189><447><210>]", + "(D) Bounding Box -[<558><245><586><256>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000289_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0088", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper left corner of Image 1pre_disaster. The building is minor-damaged and is situated on the side abovethe road, presenting an irregular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are36 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 17minor-damaged buildings.", + "Step 3: In image 1, there are many buildings above the picture.", + "Step 4: In image 1, there is a building located at the upper left cornerof the road, and the surrounding buildings are rather sparse.", + "Step 5: In image 2, the roof and walls of this building have sufferedminor damages. There are some cracks on the walls.", + "Step 6: In image 2, this building is Minor-damaged.", + "Step 7: Bounding Box -[<54><0><126><67>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<163><72><207><104>]", + "(B) Bounding Box -[<251><115><326><142>]", + "(C) Bounding Box -[<54><0><126><67>]", + "(D) Bounding Box -[<84><112><122><130>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000501_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0089", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located at the center of Image 1 (beforethe disaster). This building is slightly damaged and is situated on the upperside of the road, presenting an irregular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are159 buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 11undamaged buildings.", + "Step 3: In image 1,there are buildings on the upper side of the picture", + "Step 4: In image 1,there is a building located on the right side of theroad, with an irregular shape.", + "Step 5: In image 2,the roof and walls of this building have slight cracksand the building itself has also deformed.", + "Step 6: In image 2,this building is Minor-damaged.", + "Step 7: Bounding Box -[<266><395><322><441>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<266><395><322><441>]", + "(B) Bounding Box -[<186><434><198><447>]", + "(C) Bounding Box -[<144><431><161><444>]", + "(D) Bounding Box -[<90><395><110><409>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000461_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0090", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is No-damaged and located in the left sideof the road, with a rectangular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 89buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 89undamaged buildings.", + "Step 3: In image 1, there is a building in the lower left corner of theimage.", + "Step 4: In image 1, there is a building in the left side of the road.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<31><969><91><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<697><875><721><909>]", + "(B) Bounding Box -[<31><969><91><1024>]", + "(C) Bounding Box -[<817><809><853><859>]", + "(D) Bounding Box -[<943><661><989><683>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000430_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000430_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0091", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is No-damaged and located in the bottom sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 52buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 52undamaged buildings.", + "Step 3: In image 1, there is a building in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left corner ofthe intersection, and there is a small path around it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<276><821><549><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<60><761><107><790>]", + "(B) Bounding Box -[<276><821><549><1024>]", + "(C) Bounding Box -[<102><849><179><878>]", + "(D) Bounding Box -[<98><924><142><952>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000400_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000400_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0092", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 56buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 56undamaged buildings.", + "Step 3: In image 1, there is a building in the lower right corner of theimage.", + "Step 4: In image 1, there is a building in the bottom right corner of theentire image.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<887><657><994><781>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<932><840><987><867>]", + "(B) Bounding Box -[<887><657><994><781>]", + "(C) Bounding Box -[<839><849><895><872>]", + "(D) Bounding Box -[<674><832><742><852>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000389_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000389_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0093", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 142buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 138undamaged buildings.", + "Step 3: In image 1, there is a building in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the center of the entireimage.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<338><426><485><626>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<576><303><605><327>]", + "(B) Bounding Box -[<626><300><649><320>]", + "(C) Bounding Box -[<685><320><713><340>]", + "(D) Bounding Box -[<338><426><485><626>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000381_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000381_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0094", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 99buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 2undamaged buildings and 1 unclassified buildings.", + "Step 3: In image 1, there is a building in the upper right corner of theimage.", + "Step 4: In image 1, there is a building in the upper right corner of theentire image.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<956><0><1019><40>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<956><0><1019><40>]", + "(B) Bounding Box -[<977><92><1010><121>]", + "(C) Bounding Box -[<980><131><1012><153>]", + "(D) Bounding Box -[<973><169><1004><189>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000369_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000369_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0095", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom left corner of theimage1 pre_disaster. The building is Minor-damaged and located in the bottomside of the road, with a rectangular shape.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 51buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 28undamaged buildings and 2 unclassified buildings.", + "Step 3: In image 1, there is a building in the lower left corner of theimage.", + "Step 4: In image 1, there is a building in the bottom left corner of theentire image, and there is a path small running through it.", + "Step 5: In image 2, the roof of this building is slightly damaged and hassome cracks.", + "Step 6: In image 2, this building is Minor-damaged.", + "Step 7: Bounding Box -[<19><722><82><840>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<19><722><82><840>]", + "(B) Bounding Box -[<57><892><95><922>]", + "(C) Bounding Box -[<141><889><185><925>]", + "(D) Bounding Box -[<232><888><273><919>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000346_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0096", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the upper rightt corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. The building is located above the pathand there are no buildings around it.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 63buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 31undamaged buildings、3 major damaged buildings、28 minor damaged buildings and 1unclassified buildings.", + "Step 3: In image 1, there are some buildings located in the upper rightcorner of the picture, above a small path.", + "Step 4: In image 1, there are some buildings located in the upper rightcorner of the picture, above a small road, and to its left is an abandonedparking lot.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<977><63><1005><128>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<977><63><1005><128>]", + "(B) Bounding Box -[<694><28><724><51>]", + "(C) Bounding Box -[<846><400><881><444>]", + "(D) Bounding Box -[<993><357><1023><408>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000145_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000145_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0097", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 14buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 3: In image 1, there is a building in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left corner ofthe intersection, and there is a small path around it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0098", + "Question Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: The entire building is located in the bottom right corner of theimage1 pre_disaster. The building is No-damaged and located in the upper sideof the road, with a rectangular shape. This building is the largest in theentire picture, and it is connected to the road through a small path.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 14buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 3: In image 1, there is a building in the lower right corner of theimage.", + "Step 4: In image 1, there is the largest building in the upper left corner ofthe intersection, and there is a small path around it.", + "Step 5: In image 2, the roof and walls of this building are intact withoutcracks, and the building is not deformed or tilted.", + "Step 6: In image 2, this building is No-damaged.", + "Step 7: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Multi-image individual visual localization task/0099", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This lightly damaged building is located in the lower left cornerof the picture, with a V-shaped gray roof.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 119buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 106undamaged buildings,11 minor-damage buildings and 2 major-damage buildings.", + "Step 3: In image 1, there are 20 buildings in the lower left corner of theimage.", + "Step 4: In image 1, there is a V-shape building in the lower left corner ofthe image, and with a gray roof.", + "Step 5: In image 2, the roof and walls of this building have slight cracks,and the building has slight deformations or tilts.", + "Step 6: In image 2, this building is minor-damage.", + "Step 7: Bounding Box -[<800><828><845><865>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<800><828><845><865>]", + "(B) Bounding Box -[<720><997><753><1024>]", + "(C) Bounding Box -[<121><105><167><124>]", + "(D) Bounding Box -[<626><720><660><747>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000528_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000528_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Multi-image individual visual localization task/0100", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This minor-damage building is located in the bottom right cornerof the picture, above the road and to the right of the lake.", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 39buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 34undamaged buildings,3 minor-damage buildings and 2 major-damage buildings.", + "Step 3: In image 1, there are 3 buildings in the lower righr corner of theimage.", + "Step 4: In image 1, there is a lake in the lower right corner of theimage,There is a building by the lake.", + "Step 5: In image 2, the roof and walls of this building have slight cracks,and the building has slight deformations or tilts.", + "Step 6: In image 2, this building is minor-damage.", + "Step 7: Bounding Box -[<800><828><845><865>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<800><828><845><865>]", + "(B) Bounding Box -[<720><997><753><1024>]", + "(C) Bounding Box -[<121><105><167><124>]", + "(D) Bounding Box -[<626><720><660><747>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000535_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000535_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Multi-image individual visual localization task/0101", + "Question_Type": "Single Choice", + "Text": "Image1 is pre_disaster photo, Image2 is post_disaster photo.The following description is about the object in the pre disaster photo. Please locate the object in the post disaster photo according to the description.Description: This building, located in the lower right corner of the picture,is the largest structure in the vicinity..", + "CoT": [ + "Step 1: Image 1 is a photo taken before the disaster occurred. There are 80buildings.", + "Step 2: Image 2 is a photo taken after the disaster occurred. There are 79undamaged buildings,1 minor-damage building.", + "Step 3: In image 1, there are 6 buildings in the lower righr corner of theimage.", + "Step 4: In image 1, there is a building that is larger than other nearbybuildings.", + "Step 5: In image 2, the roof and walls of this building have slight cracks,and the building has slight deformations or tilts.", + "Step 6: In image 2, this building is minor-damage.", + "Step 7: Bounding Box -[<800><828><845><865>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Multi-image individual visual localization task", + "Answer Choices": [ + "(A) Bounding Box -[<800><828><845><865>]", + "(B) Bounding Box -[<720><997><753><1024>]", + "(C) Bounding Box -[<121><105><167><124>]", + "(D) Bounding Box -[<626><720><660><747>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000536_pre_disaster.png", + "raw/Pedosphere/diaster/XView/hurricane-michael_00000536_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Spatial_relationships_under_complex_conditions.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Spatial_relationships_under_complex_conditions.json new file mode 100644 index 0000000000000000000000000000000000000000..c8bf57eb13d74b6836693ecdbc2a3649f5e30f25 --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Spatial_relationships_under_complex_conditions.json @@ -0,0 +1,2774 @@ +[ + { + "Question_id": "Spatial relationships under complex conditions/0000", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building on the left side ofthe river, where is the square building with a green roof", + "CoT": [ + "Step 1: Bounding Box -[<2><6><61><51>] has green square roof.", + "Step 2: Bounding Box -[<2><6><61><51>] is located in the upper left corner of the image.", + "Step 3: There is a rectangular building on the left side of the river.", + "Step 4: Bounding Box -[<398><60><451><143>] is above the center of the image.", + "Step 5: Bounding Box -[<2><6><61><51>] on the left from Bounding Box -[<398><60><451><143>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000344_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0001", + "Question Type": "Single Choice", + "Text": "From the perspective of the triangular building near the sandy road,where is the square building near the oasis？", + "CoT": [ + "Step 1: Bounding Box -[<139><1><215><79>] has a square building with half a white roof.", + "Step 2: Bounding Box -[<139><1><215><79>] is located in the upper left corner of the entireimage.", + "Step 3: Bounding Box7 is the largest triangular building on the left side ofthe picture .", + "Step 4: Bounding Box -[<0><289><51><377>] is located in the upper left corner of the image", + "Step 5: Bounding Box -[<139><1><215><79>] on the right from Bounding Box -[<0><289><51><377>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000361_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0002", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest L-shaped building, where is theother L-shaped white roof in the opposite direction?", + "CoT": [ + "Step 1: Bounding Box -[<704><860><837><991>] the angle of the largest L-shaped building.", + "Step 2: Bounding Box -[<704><860><837><991>] is located in the bottom right corner of thepicture.", + "Step 3:Bounding Box -[<693><748><779><863>] has an L-shaped white roof and a similar buildingbelow it.", + "Step 4: Bounding Box -[<693><748><779><863>] is located in the upper right corner of thepicture.", + "Step 5: Bounding Box -[<704><860><837><991>] on the below from Bounding Box -[<693><748><779><863>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0003", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular green building above theplayground, where is the location of the L-shaped building near theintersection?", + "CoT": [ + "Step 1: Bounding Box -[<0><833><150><885>] is above the playground.", + "Step 2: Bounding Box -[<0><833><150><885>] is located in the bottom left corner of thepicture.", + "Step 3: Bounding Box -[<386><545><500><671>] on its left is the intersection of the road.", + "Step 4: Bounding Box -[<386><545><500><671>] is located in the center of the picture.", + "Step 5: Bounding Box -[<386><545><500><671>] on the right from Bounding Box -[<0><833><150><885>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000366_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0004", + "Question Type": "Single Choice", + "Text": "From the perspective of the smallest rectangular building above thehighway, where is the largest rectangular building above the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<379><357><409><374>] is the smallest rectangular building.", + "Step 2: Bounding Box -[<379><357><409><374>] is located in the center of the picture, below it is avery wide highway.", + "Step 3: Bounding Box -[<369><211><549><298>] is the largest rectangular building with a white roofabove the parking lot.", + "Step 4: Bounding Box -[<369><211><549><298>] is located in the center of the picture, above theparking lot on the highway.", + "Step 5: Bounding Box -[<379><357><409><374>] on the below from Bounding Box -[<369><211><549><298>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000367_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0005", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest white roofed building on theleft side of the parking lot, where is the largest H-shaped white roofedbuilding?", + "CoT": [ + "Step 1: Bounding Box -[<422><735><502><955>] is the largest rectangular building with a whiteroof.", + "Step 2: Bounding Box -[<422><735><502><955>] on the left side of the parking lot located in thelower right corner of the picture.", + "Step 3: Bounding Box -[<550><383><784><621>] is the largest H-shaped white roofed building.", + "Step 4: Bounding Box -[<550><383><784><621>] is located in the center of the picture, below it is aroad.", + "Step 5: Bounding Box -[<550><383><784><621>] on the above from Bounding Box -[<422><735><502><955>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000379_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0006", + "Question Type": "Single Choice", + "Text": "From the perspective of the smallest white roofed square building onthe right side of the parking lot, where is the largest L-shaped whitebuilding below the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<929><831><984><884>] is the smallest square white roofed building.", + "Step 2: Bounding Box -[<929><831><984><884>] is located in the lower right corner of the entireimage, to its left is a parking lot.", + "Step 3: Bounding Box -[<533><899><804><1024>] at the bottom of the image，it have an L-shaped whiteroof.", + "Step 4: Bounding Box -[<533><899><804><1024>] is located below the parking lot, with roads on bothsides, it is the largest L-shaped white roofed building below the parkinglot.", + "Step 5: Bounding Box -[<533><899><804><1024>] on the below from Bounding Box -[<929><831><984><884>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000380_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0007", + "Question Type": "Single Choice", + "Text": "From the perspective of the white rectangular building below theparking lot, where is the building exactly like it?", + "CoT": [ + "Step 1: Bounding Box -[<217><889><269><1021>] is the longest white roofed building.", + "Step 2: Bounding Box -[<217><889><269><1021>] is located in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<369><884><427><1024>] have an identical building on the left .", + "Step 4: Bounding Box -[<369><884><427><1024>] is located in the bottom left corner of thepicture.", + "Step 5: Bounding Box -[<217><889><269><1021>] is on the left from Bounding Box -[<369><884><427><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000396_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0008", + "Question Type": "Single Choice", + "Text": "Where is the square building located in the green belt from theperspective of the smallest building near the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<992><653><1022><683>] is a square building located in the green belt.", + "Step 2: Bounding Box -[<992><653><1022><683>] is located at the lower right of the picture.", + "Step 3: Bounding Box -[<190><260><204><271>] is the smallest building near the parking lot.", + "Step 4: Bounding Box -[<190><260><204><271>] is located at the upper left corner of the picture.", + "Step 5: Bounding box -[<992><653><1022><683>] on the right from Bounding Box -[<190><260><204><271>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000374_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0009", + "Question Type": "Single Choice", + "Text": "Where is the first rectangular building in the first row on the farright of the entire picture located in the last building in the first row?", + "CoT": [ + "Step 1: Bounding Box -[<715><100><759><256>] is a the longest rectangular building,to its right andabove are roads.", + "Step 2: Bounding Box -[<715><100><759><256>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<713><949><763><1024>] is a the shortest rectangular building，to its rightand above are roads.", + "Step 4: Bounding Box -[<713><949><763><1024>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<715><100><759><256>] is on the above from Bounding Box -[<713><949><763><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000413_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0010", + "Question Type": "Single Choice", + "Text": "Judging by the largest building under the river, where is the squarebuilding above the white cement floor?", + "CoT": [ + "Step 1: Bounding box -[<4><962><72><1024>] is the largest building under the river.", + "Step 2: Bounding box -[<4><962><72><1024>] is located in the lower-left corner of the picture.", + "Step 3: The square building above the white cement floor is the Bounding Box7.", + "Step 4: Bounding Box -[<968><44><1024><119>] is located in the upper right corner of the picture.", + "Step 5: From the perspective of bounding box 6, bounding box 7 below." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Top right", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000434_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0011", + "Question Type": "Single Choice", + "Text": "Where is The building with the longest light gray roof from theperspective of The largest O-shaped building in terms of area?", + "CoT": [ + "Step 1: Bounding Box -[<129><727><353><873>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<129><727><353><873>] is located in the bottom right corner of thepicture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<743><848><1024><890>] is the smallest of them.", + "Step 4: Bounding Box -[<743><848><1024><890>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<129><727><353><873>] on the below from Bounding Box -[<743><848><1024><890>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0012", + "Question Type": "Single Choice", + "Text": "Where is the L-shaped building between the two parking lots from theperspective of the largest building in the diagram?", + "CoT": [ + "Step 1: Bounding Box -[<21><264><257><462>] is located between two parking lots and is in theshape of an L.", + "Step 2: Bounding Box -[<21><264><257><462>] is located in the middle of the left side of thepicture.", + "Step 3: Bounding Box -[<782><322><1024><662>] is the largest building in the entire picture.", + "Step 4: Bounding Box -[<782><322><1024><662>] is located in the middle of the right side of thepicture.", + "Step 5: Bounding Box -[<21><264><257><462>] on the left from Bounding Box -[<782><322><1024><662>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000443_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0013", + "Question Type": "Single Choice", + "Text": "Judging from the smallest triangular building in the lower rightcorner of the river channel on the right side of the image, where is theinverted L-shaped building with white roof on the left side of the riverchannel on the right side of the image?", + "CoT": [ + "Step 1: Bounding box -[<696><975><757><1024>] is an inverted L-shaped building with a white roof.", + "Step 2:Bounding box -[<696><975><757><1024>] is located on the right side of the picture, to theleft of the river.", + "Step 3:On the right side of the image, there are four white-roofed buildingson the left side of the river, and Bounding Box -[<696><975><757><1024>] is inverted L-shaped.", + "Step 4:Bounding box -[<989><1002><1024><1024>] is located in the lower-right corner of the picture.", + "Step 5:From the perspective of Bounding Box -[<989><1002><1024><1024>], Bounding Box -[<696><975><757><1024>] is locateddirectly to the left." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Directly left", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000463_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0014", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest building in the whole map, whereis the slightly damaged building at the bottom??", + "CoT": [ + "Step 1: Bounding Box -[<973><871><1024><948>] is the lowest slightly damaged building.", + "Step 2: Bounding Box -[<973><871><1024><948>] is located in the bottom right corner of thepicture.", + "Step 3: There are four buildings next to each other, and Bounding Box -[<466><772><647><1024>] isthe largest..", + "Step 4: Bounding Box -[<466><772><647><1024>] is located right below the image.", + "Step 5: Bounding Box -[<973><871><1024><948>] is to the right of Bounding Box -[<466><772><647><1024>]." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000470_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0015", + "Question Type": "Single Choice", + "Text": "Where is the first building in the row of similar structures belowthe road, viewed from the isolated building at the bottom-left corner of theimage?", + "CoT": [ + "Step 1: Bounding Box -[<741><741><762><757>] is the first building in the row of similar structuresbelow the road.", + "Step 2: Bounding Box -[<741><741><762><757>] is located at the lower right corner of the picture.", + "Step 3: Bounding Box -[<81><677><104><697>] is the isolated building at the bottom-left corner ofthe image with no surrounding structures.", + "Step 4: Bounding Box -[<81><677><104><697>] is located in the lower left corner of the picture.", + "Step 5: Bounding Box -[<741><741><762><757>] is on the right from Bounding Box -[<81><677><104><697>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000198_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0016", + "Question Type": "Single Choice", + "Text": "Where is the L-shaped building located between the water pool and theother L-shaped structure, from the perspective of the only triangular buildingin the diagram?", + "CoT": [ + "Step 1: Bounding Box -[<322><339><395><499>] is an L-shaped building located between the pool andthe L-shaped building.", + "Step 2: Bounding Box -[<322><339><395><499>] is located in the middle of the picture.", + "Step 3: Bounding Box -[<555><533><719><650>] is the only triangular building in the picture.", + "Step 4: Bounding Box -[<555><533><719><650>] is on the left side of the picture.", + "Step 5: Bounding Box -[<322><339><395><499>] is on the right from Bounding Box -[<555><533><719><650>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000455_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0017", + "Question Type": "Single Choice", + "Text": "Where is the smallest square roofed building from the perspective ofthe building with the smallest building?", + "CoT": [ + "Step 1: Bounding Box -[<536><1018><557><1024>] is the smallest square roofed building.", + "Step 2: Bounding Box -[<536><1018><557><1024>] is located in the bottom corner of the picture.", + "Step 3: There are seven buildings that are not adjacent to the road, andBounding Box -[<975><30><991><67>] is the smallest of them.", + "Step 4: Bounding Box -[<975><30><991><67>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<536><1018><557><1024>] on the below from Bounding Box -[<975><30><991><67>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000347_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0018", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<91><821><133><918>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<91><821><133><918>] is located in the bottom left corner of the picture.", + "Step 3: There are three white buildings that are adjacent to the road, andBounding Box -[<91><821><133><918>] is the smallest of them.", + "Step 4: Bounding Box -[<465><821><536><920>] is located at the bottom of the picture.", + "Step 5: Bounding Box -[<91><821><133><918>] on the left from Bounding Box -[<465><821><536><920>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000375_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0019", + "Question Type": "Single Choice", + "Text": "Where is the smallest square roofed building from the perspective ofthe building with the smallest area that is not adjacent to the road?", + "CoT": [ + "Step 1: Bounding Box -[<82><442><102><463>] is the smallest square roofed building.", + "Step 2: Bounding Box -[<927><185><978><224>] is located in the upper right corner of the picture.", + "Step 3: There are two buildings that are not adjacent to the road, andBounding Box -[<82><442><102><463>] is the smallest of them.", + "Step 4: Bounding Box -[<82><442><102><463>] is located in the left corner of the picture.", + "Step 5: Bounding Box -[<927><185><978><224>] on the upper right from Bounding Box -[<82><442><102><463>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0020", + "Question Type": "Single Choice", + "Text": "Where is the rightmost building among the three structures on theright side of the road bend, viewed from the isolated triangular building inthe lower left corner of the image?", + "CoT": [ + "Step 1: Bounding Box -[<362><1007><385><1024>] is the rightmost building among the three structureson the right side of the road bend.", + "Step 2: Bounding Box -[<362><1007><385><1024>] is located in the lower left corner of the picture.", + "Step 3: Bounding Box -[<10><992><70><1024>] is the isolated triangular building.", + "Step 4: Bounding Box -[<10><992><70><1024>] is located in the lower left corner of the picture.", + "Step 5: Bounding Box -[<362><1007><385><1024>] is on the right from Bounding Box -[<10><992><70><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000310_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0021", + "Question Type": "Single Choice", + "Text": "Where is the N-shaped building closest to the coastline from theperspective of the only M-shaped structure in the diagram?", + "CoT": [ + "Step 1: Bounding Box -[<593><676><674><755>] is the N-shaped building closest to the coastline.", + "Step 2: Bounding Box -[<593><676><674><755>] is located at the lower right corner of the picture.", + "Step 3: Bounding Box -[<417><808><559><908>] is the only M-shaped structure in the picture.", + "Step 4: Bounding Box -[<417><808><559><908>] is located in the middle of the bottom of thepicture.", + "Step 5: Bounding Box -[<593><676><674><755>] is on the right from Bounding Box -[<417><808><559><908>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000372_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0022", + "Question Type": "Single Choice", + "Text": "Where is the smallest building on the image from the point of view ofa slightly damaged building close to the road?", + "CoT": [ + "Step 1: Bounding box -[<696><902><709><917>] is the smallest building in the image.", + "Step 2:Bounding box -[<696><902><709><917>] is located in the upper-left corner of the picture.", + "Step 3: Bounding box -[<928><259><939><268>] is a slightly damaged building near the highway.", + "Step 4:Bounding box -[<928><259><939><268>] is located in the lower-right corner of the picture.", + "Step 5:From the perspective of Bounding Box -[<928><259><939><268>], Bounding Box -[<696><902><709><917>] is located inthe top left." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Top left", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0023", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<107><77><136><95>] is the smallest white square roofed building.", + "Step 2: Bounding box -[<107><77><136><95>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<248><348><279><392>] is the smallest of them.", + "Step 4: Bounding Box -[<248><348><279><392>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<107><77><136><95>] is on the above from Bounding Box -[<248><348><279><392>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000016_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0024", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<0><19><58><53>] is the smallest black square roofed building.", + "Step 2: Bounding Box -[<0><19><58><53>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<78><28><131><61>] is similar size to them.", + "Step 4: Bounding Box -[<78><28><131><61>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<0><19><58><53>] is on the left from Bounding Box -[<78><28><131><61>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000035_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0025", + "Question Type": "Single Choice", + "Text": "Where is the building closest to the right edge of the image from theperspective of the structure at the lower left corner of the intersection andto the left of the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<1009><848><1024><900>] is the building closest to the right edge of thepicture.", + "Step 2: Bounding Box -[<1009><848><1024><900>] is located at the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><935><54><1024>] is located at the lower left corner of theintersection and on the left side of the parking lot.", + "Step 4: Bounding Box -[<0><935><54><1024>] is located at the lower left of the picture.", + "Step 5: Bounding Box -[<1009><848><1024><900>] is on the right from Bounding Box -[<0><935><54><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000044_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0026", + "Question Type": "Single Choice", + "Text": "Where is the smallest triangular building in the picture from theperspective of the square building below the semi-circular road?", + "CoT": [ + "Step 1: Bounding Box -[<1005><332><1024><364>] is the smallest triangular building in the picture.", + "Step 2: Bounding Box -[<1005><332><1024><364>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<934><550><982><598>] is a square building beneath the semi-circular road.", + "Step 4: Bounding Box -[<934><550><982><598>] is located near the middle on the right side of thepicture.", + "Step 5: Bounding Box -[<1005><332><1024><364>] is above from Bounding Box -[<934><550><982><598>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000130_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0027", + "Question Type": "Single Choice", + "Text": "From the point of view of the smallest white-roofed building near theintersection, where is the smallest white-roofed building near the curvedroad?", + "CoT": [ + "Step 1: Bounding box -[<981><600><1024><644>] is the smallest white square-roofed building near thecurved road", + "Step 2: Bounding Box -[<981><600><1024><644>] is located in the bottom right corner of thepicture.", + "Step 3: Part of the building is adjacent to the intersection, and boundingbox 7 is white-roofed.", + "Step 4: Bounding box -[<459><320><492><366>] is in the middle of the picture..", + "Step 5: From the perspective of bounding box 7, bounding box 6 is at thebottom right." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Bottom right", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000147_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0028", + "Question Type": "Single Choice", + "Text": "From the point of view of the largest concave building on the rightside of the picture, where is the closest and largest green roof building?", + "CoT": [ + "Step 1: Bounding Box -[<742><437><973><691>] is the green building with the largest image area inthe whole image.", + "Step 2: Bounding Box -[<742><437><973><691>] is in the middle right of the picture.", + "Step 3: There is only one concave building in this picture, and Bounding Box7 is this building.", + "Step 4: Bounding Box -[<860><452><882><595>] is located in the right corner of the picture.", + "Step 5: Bounding Box -[<742><437><973><691>] on the outside from Bounding Box -[<860><452><882><595>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Inside", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000418_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0029", + "Question Type": "Single Choice", + "Text": "Judging from the smallest building in the vicinity of the circularbuilding in the picture,where is the closest building to it ?", + "CoT": [ + "Step 1:Bounding Box -[<256><631><274><646>]is the smallest rectangular building around the ringbuilding.", + "Step 2:Bounding Box -[<256><631><274><646>]is in the lower left part of the picture.", + "Step 3:There are five buildings around and ring building Bounding Box -[<286><652><306><671>]isin the upper right corner of the ring building.", + "Step 4:Bounding Box -[<286><652><306><671>]is located in the bottom left corner of thepicture.", + "Step 5:Bounding Box -[<256><631><274><646>]is in the upper left from Bounding Box -[<286><652><306><671>]'sperspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Bottom right", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000502_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0030", + "Question Type": "Single Choice", + "Text": "From the point of view of the rectangular building in the lower rightcorner of the picture, where is the closest building to it ?", + "CoT": [ + "Step 1: There are two rectangular buildings arranged vertically, with theBounding Box -[<961><997><981><1019>] being the smaller one.", + "Step 2: Bounding Box -[<961><997><981><1019>] is located in the bottom right corner of thepicture.", + "Step 3: There are 2 buildings in the bottom right corner of the picture, andBounding Box -[<956><965><978><987>] is the largest of them.", + "Step 4: Bounding Box -[<956><965><978><987>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<961><997><981><1019>] is on the below from Bounding Box -[<956><965><978><987>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000365_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0031", + "Question Type": "Single Choice", + "Text": "From the point of view of the smallest building in the upper leftcorner of the picture, where is the closest building to it?", + "CoT": [ + "Step 1: Bounding Box -[<0><186><25><234>] is the smallest green square in the top left corner", + "Step 2: Bounding Box -[<0><186><25><234>] is located in the upper left corner of the picture.", + "Step 3:In the upper left corner of the picture, there are two buildings sideby side, with A being the larger one.", + "Step 4: Bounding Box -[<29><186><123><234>] is lin the upper left corner of the picture.", + "Step 5: Bounding Box -[<0><186><25><234>] is on the left from Bounding Box -[<29><186><123><234>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000003_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0032", + "Question Type": "Single Choice", + "Text": "Counting from the top down, from the point of view of the largestbuilding above the first transverse road, where is the building in the shapeof an airplane?", + "CoT": [ + "Step 1: Bounding Box -[<14><321><93><402>] is the largest white square roofed building.", + "Step 2: Bounding Box -[<14><321><93><402>] is located in the upper left corner of the picture.", + "Step 3:This building is the only airplane-shaped building in the entireimage..", + "Step 4: Bounding Box -[<22><135><84><221>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<14><321><93><402>] is on the below from Bounding Box -[<22><135><84><221>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000072_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0033", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<434><612><450><635>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<434><612><450><635>] is located in the center of the picture.", + "Step 3: There are two buildings that are not adjacent to the road, andBounding Box -[<434><612><450><635>] is the smallest of them.", + "Step 4: Bounding Box -[<472><470><518><504>] is located in the upper right corner of the BoundingBox 6.", + "Step 5: Bounding Box -[<434><612><450><635>] is on the below from Bounding Box -[<472><470><518><504>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Left", + "(B) Below", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000152_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0034", + "Question Type": "Single Choice", + "Text": "From the point of view of the topmost slightly damaged building,where is the topmost severely damaged building??", + "CoT": [ + "Step 1: Bounding Box -[<0><66><69><127>] is the building at the bottom left of theintersection.", + "Step 2: Bounding Box -[<0><66><69><127>] is located in the top left corner of the picture.", + "Step 3: There are three buildings adjacent to the road, of which Bounding Box7 is the top one..", + "Step 4: Bounding box -[<102><183><157><247>] is located on the left side of the picture.", + "Step 5: Bounding Box -[<0><66><69><127>] is at the bottom right from the perspective ofBounding Box -[<102><183><157><247>]." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Bottom right", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000151_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0035", + "Question Type": "Single Choice", + "Text": "From the perspective of the building of the larger of the twobuildings enclosed by the largest building in the picture, where is thesmallest building with a white square roof to the right of the largestbuilding in the picture?", + "CoT": [ + "Step 1: Bounding Box -[<341><799><359><835>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<341><799><359><835>] is located in the bottom right corner of thepicture.", + "Step 3: Box 7 is the building of the larger of the two buildings enclosed bythe largest building in the picture", + "Step 4: Box 7 is located at the lower left corner of the picture.", + "Step 5: Bounding Box -[<341><799><359><835>] is on the below from Bounding Box -[<355><615><403><651>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000183_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0036", + "Question Type": "Single Choice", + "Text": "Where is the nearest building to the right side of the lake in thepicture??", + "CoT": [ + "Step 1: Bounding Box -[<731><270><751><289>] is the smallest rectangular structure around thislake..", + "Step 2: Bounding Box -[<731><270><751><289>] is located in the upper right corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<772><265><802><294>] is the smallest of them.", + "Step 4: Bounding Box -[<772><265><802><294>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<731><270><751><289>] is on the left from Bounding Box -[<772><265><802><294>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000253_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0037", + "Question Type": "Single Choice", + "Text": "Where is the largest T-shaped building relative to the largestrectangular building in the image?", + "CoT": [ + "Step 1: Bounding Box -[<0><894><95><1024>] is the largest T-shaped building in the picture.", + "Step 2: Bounding Box -[<0><894><95><1024>] is located in the lower left corner of the picture.", + "Step 3: Bounding Box -[<1><635><291><773>] is the largest rectangular building in the picture.", + "Step 4: Bounding Box -[<1><635><291><773>] is located in the middle of the left side of thepicture.", + "Step 5: Bounding Box -[<0><894><95><1024>] is below from Bounding Box -[<1><635><291><773>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000181_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0038", + "Question Type": "Single Choice", + "Text": "From the perspective of the smallest building on the right side ofthe river, where is the rectangular building with the largest green roof onthe right side of the river?", + "CoT": [ + "Step 1: Bounding Box -[<789><477><797><489>] is the smallest rectangular building is located on theright side of the river.", + "Step 2: Bounding Box -[<789><477><797><489>] is located in the upper right corner of the image .", + "Step 3: Bounding Box -[<482><145><502><191>] is the rectangular building with the largest greenroof on the right side of the river.", + "Step 4: Bounding Box -[<482><145><502><191>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<482><145><502><191>] on the above from Bounding Box -[<789><477><797><489>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000190_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0039", + "Question Type": "Single Choice", + "Text": "From the perspective of the smallest white rectangular building onthe left side of the cliff, where is the smallest green roof building abovethe road?", + "CoT": [ + "Step 1: Bounding Box -[<147><901><167><916>] is the smallest white roofed building located on theleft side of the cliff.", + "Step 2: Bounding Box -[<147><901><167><916>] is located in the bottom left corner of the image.", + "Step 3: Bounding Box -[<187><12><208><32>]is the smallest green roof building and located abovethe road.", + "Step 4: Bounding Box -[<187><12><208><32>] is located in the upper left corner of the image.", + "Step 5: Bounding Box -[<187><12><208><32>] on the below from Bounding Box -[<147><901><167><916>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000221_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0040", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building with the largestwhite roof on the left side of the road, where is the smallest L-shaped greenroof building on the right side of the city?", + "CoT": [ + "Step 1: Bounding Box -[<266><903><309><956>] the rectangular building with the largest white roofon the left side of the road.", + "Step 2: Bounding Box -[<266><903><309><956>] is located in the upper left corner of the picture.", + "Step 3:Bounding Box -[<249><410><322><479>] is the smallest L-shaped building with a green roof onthe right side of the city .", + "Step 4: Bounding Box -[<249><410><322><479>] is located in the bottom left corner of the image.", + "Step 5: Bounding Box -[<266><903><309><956>] on the below from Bounding Box -[<249><410><322><479>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000278_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0041", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest rectangular white roofed buildingbelow the lake, where is the position of the last building in the first row onthe right side of the road intersection?", + "CoT": [ + "Step 1: Bounding Box -[<506><801><585><858>] is the largest rectangular white roofed building belowthe lake .", + "Step 2: Bounding Box -[<506><801><585><858>] is located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<738><1003><787><1024>] is the smallest rectangular green roof buildinglocated on the right side of the road intersection.", + "Step 4: Bounding Box -[<738><1003><787><1024>] is located in the bottomright corner of the picture.", + "Step 5: Bounding Box -[<738><1003><787><1024>] on the right from Bounding Box -[<506><801><585><858>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000000_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0042", + "Question Type": "Single Choice", + "Text": "From the perspective of the longest rectangular building above theparking lot, where is the largest L-shaped green roof building on the rightside of the intersection?", + "CoT": [ + "Step 1: Bounding Box -[<696><902><709><917>] is the longest rectangular building.", + "Step 2: Bounding Box -[<696><902><709><917>] is located in the upper left corner of the picture.", + "Step 3: Bounding Box -[<928><259><939><268>] is the largest L-shaped green roof building on theright side of the intersection.", + "Step 4: Bounding Box -[<928><259><939><268>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<928><259><939><268>] on the right from Bounding Box -[<696><902><709><917>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0043", + "Question Type": "Single Choice", + "Text": "Where is the square building with a reddish brown roof on the rightside of the highway located on the square building with a white roof on theright side of the highway?", + "CoT": [ + "Step 1: Bounding Box -[<977><760><1022><812>] is the largest square building with a reddish brownroof on the right side of the highway.", + "Step 2: Bounding Box -[<977><760><1022><812>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<991><191><1024><247>]i s the largest square building with a white roof onthe right side of the highway.", + "Step 4: Bounding Box -[<991><191><1024><247>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<991><191><1024><247>] on the above from Bounding Box -[<977><760><1022><812>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000034_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0044", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest rectangular green roof buildingbelow the town, where is the smallest rectangular green roof in the center ofthe town?", + "CoT": [ + "Step 1: Bounding Box -[<540><963><616><1024>] is the largest rectangular green roof building belowthe town.", + "Step 2: Bounding Box -[<540><963><616><1024>] is located in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<393><1><408><23>] is the smallest rectangular green roof in the centerof the town.", + "Step 4: Bounding Box -[<393><1><408><23>] is located above the center of the image.", + "Step 5: Bounding Box -[<393><1><408><23>] on the above from Bounding Box -[<540><963><616><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000056_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0045", + "Question Type": "Single Choice", + "Text": "From the perspective of the yellow brown square building on the rightside of the parking lot, where is the largest L-shaped building beneath thelake?", + "CoT": [ + "Step 1: Bounding Box -[<92><260><131><300>] is a square brown roofed building located on the rightside of the parking lot.", + "Step 2: Bounding Box -[<92><260><131><300>] is located in the upper left corner of the picture.", + "Step 3: Bounding Box -[<85><845><124><904>] is the largest L-shaped building below the lake.", + "Step 4: Bounding Box -[<85><845><124><904>] is located in the bottom left corner of the picture.", + "Step 5: Bounding Box -[<85><845><124><904>] on the below from Bounding Box -[<92><260><131><300>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000142_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0046", + "Question Type": "Single Choice", + "Text": "From the perspective of the smallest white roofed rectangularbuilding on the left side of the highway,Where is the rectangular buildingwith the first green roof from the left below the parking lot on the rightside of the highway?", + "CoT": [ + "Step 1: Bounding Box -[<633><929><701><984>] is the smallest white rectangular building on the leftside of the highway.", + "Step 2: Bounding Box -[<633><929><701><984>] is located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<493><619><556><704>] is the rectangular building with the first green rooffrom the left below the parking lot on the right side of the highway.", + "Step 4: Bounding Box -[<493><619><556><704>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<633><929><701><984>] on the below from Bounding Box -[<493><619><556><704>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000146_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0047", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building with a very widegray roof on the left open space of the right highway, where is the locationof the L-shaped building with a yellow brown roof on the left side of theright highway?", + "CoT": [ + "Step 1: Bounding Box -[<863><845><926><909>] is the largest L-shaped building with a yellow brownroof is located on the left side of the highway on the right.", + "Step 2: Bounding Box -[<863><845><926><909>] is located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<624><168><759><218>] is the rectangular building with the widest gray roofis located on the left side of the highway on the right", + "Step 4: Bounding Box -[<624><168><759><218>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<863><845><926><909>] on the below from Bounding Box -[<624><168><759><218>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000165_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0048", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest white rectangular building in theupper right corner of the intersection, where is the largest reddish brownL-shaped building in the lower right corner of the intersection?", + "CoT": [ + "Step 1: Bounding Box -[<913><234><993><312>] is the largest white rectangular building in the upperright corner of the intersection.", + "Step 2: Bounding Box -[<913><234><993><312>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<925><897><964><952>] is the the largest reddish brown L-shaped building inthe lower right corner of the intersection.", + "Step 4: Bounding Box -[<925><897><964><952>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<925><897><964><952>] on the below from Bounding Box -[<913><234><993><312>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000266_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0049", + "Question Type": "Single Choice", + "Text": "From the perspective of the longer L-shaped building in the bottomright corner of the figure, where is the smallest building located near theroad in the bottom left corner of the figure?", + "CoT": [ + "Step 1: Bounding Box -[<2><611><28><657>] is located in the lower left corner of the picturenear a relatively wide road and has the smallest area.", + "Step 2: Bounding Box -[<2><611><28><657>] is located in the lower left corner of the picturenear a relatively wide road.", + "Step 3: Bounding Box -[<998><575><1024><887>] is located in the lower right corner of the picturenear a wider road and has a relatively long L-shaped shape.", + "Step 4: Bounding Box -[<998><575><1024><887>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<2><611><28><657>] is on the left from Bounding Box -[<998><575><1024><887>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000261_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0050", + "Question Type": "Single Choice", + "Text": "From the perspective of the building on the right side of thepicture, which is close to the narrow path and has a concave shape, where isthe building in the bottom right corner of the picture and has a convexshape?", + "CoT": [ + "Step 1: Bounding Box -[<818><963><873><1015>] is located in the bottom right corner of the pictureand has a convex shape.", + "Step 2: Bounding Box -[<818><963><873><1015>] is located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<806><517><858><568>] is located on the right side of the picture near thenarrow road and has a concave shape.", + "Step 4: Bounding Box -[<806><517><858><568>] is located on the right side of the picture, close tothe narrow road.", + "Step 5: Bounding Box -[<818><963><873><1015>] is on the below from Bounding Box -[<806><517><858><568>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000200_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0051", + "Question Type": "Single Choice", + "Text": "From the perspective of the L-shaped building located at the top ofthe diagram, where is the L-shaped building located on the leftmost side ofthe diagram and to the right of the small river?", + "CoT": [ + "Step 1: Bounding Box -[<25><1005><57><1024>] is located at the bottom left of the diagram andappears L-shaped at the bottom right of the small river.", + "Step 2: Bounding Box -[<25><1005><57><1024>] is located at the bottom left corner of the diagram.", + "Step 3: Box 7 is located at the top of the diagram and appears L-shaped .", + "Step 4: Bounding Box -[<438><27><467><65>] is located at the top of the picture .", + "Step 5: Bounding Box -[<25><1005><57><1024>] is on the below from Bounding Box -[<438><27><467><65>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000385_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0052", + "Question Type": "Single Choice", + "Text": "From the perspective of the n-type building in the bottom left cornerof the figure, where is the M-shaped building located in the top right cornerof the figure?", + "CoT": [ + "Step 1: Bounding Box -[<266><97><351><274>] is located in the upper left corner of the picture andpresents a large M-shape.", + "Step 2: Bounding Box -[<266><97><351><274>] is located in the upper left corner of the picture.", + "Step 3: Bounding Box -[<74><664><144><734>] is located in the bottom left corner of the pictureand appears in an n-type shape.", + "Step 4: Bounding Box -[<74><664><144><734>] is is located in the lower left corner of thepicture.", + "Step 5: Bounding Box -[<266><97><351><274>] is on the Above from Bounding Box -[<74><664><144><734>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000051_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0053", + "Question Type": "Single Choice", + "Text": "From the perspective of the longest rectangular building in the topleft corner, what is the orientation of the heart-shaped building in the topleft corner?", + "CoT": [ + "Step 1: Bounding Box -[<377><260><408><295>] is in the upper left corner of the picture, whichappears in the shape of a small heart.", + "Step 2: Bounding Box -[<377><260><408><295>] is located in the upper left part of the picture.", + "Step 3: Bounding Box -[<317><25><364><76>] is the rectangle that is closest to the upper left andhas the longest shape.", + "Step 4: Bounding Box -[<317><25><364><76>] is located in the upper left part of the picture.", + "Step 5: Bounding Box -[<377><260><408><295>] is on the below from Bounding Box -[<317><25><364><76>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000335_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0054", + "Question Type": "Single Choice", + "Text": "From the perspective of the building located near the road in theupper right corner of the image and with the smallest area, where is theL-shaped building located near the road in the lower right corner of theimage?", + "CoT": [ + "Step 1: Bounding Box -[<731><510><809><619>] is located in the lower right corner of the picturenear the road and presents an L-shape.", + "Step 2: Bounding Box -[<731><510><809><619>] is located on the right side of the picture.", + "Step 3: Bounding Box -[<639><240><659><267>] is located in the upper right corner of the picturenear the road and is the smallest in area.", + "Step 4: Bounding Box -[<639><240><659><267>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<731><510><809><619>] is on the below from Bounding Box -[<639><240><659><267>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000124_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0055", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building that is farthest tothe right and longest in the middle, what is the orientation of the squarebuilding that is farthest to the upper right and largest?", + "CoT": [ + "Step 1: Bounding Box -[<651><19><682><50>] is is the largest square located in the top rightcorner of the image.", + "Step 2: Bounding Box -[<651><19><682><50>] is located in the upper right part of the figure.", + "Step 3: Bounding Box -[<988><561><1024><597>] is the longest rectangle located to the right in themiddle of the picture.", + "Step 4: Bounding Box -[<988><561><1024><597>] is the building located furthest to the right in themiddle of the picture.", + "Step 5: Bounding Box -[<651><19><682><50>] is on the Above from Bounding Box -[<988><561><1024><597>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000231_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0056", + "Question Type": "Single Choice", + "Text": "What is the orientation of the building at the bottom and closest tothe narrowest road in a triangular shape and closest to the wider road?", + "CoT": [ + "Step 1: Bounding Box -[<905><832><947><879>] is located at the bottom right corner of thepicture.", + "Step 2: Bounding Box -[<905><832><947><879>] is located at the bottom right of the picture andclose to the narrowest road.", + "Step 3: Bounding Box -[<518><0><618><26>] i is located at the top right corner of the pictureand appears as a triangle.", + "Step 4: Bounding Box -[<518><0><618><26>] is located at the top right corner of the picture,presenting a triangle and closest to the wide road in the picture.", + "Step 5: Bounding Box -[<905><832><947><879>] is located in the bottom right corner of Box 12'sperspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000338_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0057", + "Question Type": "Single Choice", + "Text": "From the perspective of the first building in the order of left toright above the circular road on the left island, where is the building at thebottom of the rightmost path?", + "CoT": [ + "Step 1: Bounding Box -[<950><984><999><1024>] is located at the bottom right corner of thepicture.", + "Step 2: Bounding Box -[<950><984><999><1024>] is located at the bottom right corner of the pictureand at the bottom right corner of the path.", + "Step 3: Bounding Box -[<170><563><233><640>] is There are buildings on the small island in themiddle of the far left side in the picture.", + "Step 4: Bounding Box -[<170><563><233><640>] is located on the leftmost island in the middle of thepicture, and the position above the circular road inside the island is countedfrom left to right.", + "Step 5: Bounding Box -[<950><984><999><1024>] on the below from Bounding Box -[<170><563><233><640>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000433_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0058", + "Question Type": "Single Choice", + "Text": "From the perspective of the eleventh building from left to right onthe left branch of the T-shaped road near the road, where is the firstbuilding from left to right on the right branch of the T-shaped road near theroad?", + "CoT": [ + "Step 1: Bounding Box -[<532><329><576><407>] There is a building located in the bottom left cornerof the picture, presenting an M-shape.", + "Step 2: Bounding Box -[<532><329><576><407>] is located in the lower left corner of the picture,presenting an M-shape, and three small paths are clearly visible in the lowerleft part. This building is located near the second small path.", + "Step 3: Bounding Box -[<444><334><509><419>] is the smallest rectangular building closest to theroad in the picture.", + "Step 4: Bounding Box -[<444><334><509><419>] is located in the smallest rectangular buildingclosest to the road and there are three small paths under the road in thepicture. This building is close to the third small path.", + "Step 5: Bounding Box -[<532><329><576><407>] is on the right from Bounding Box -[<444><334><509><419>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000452_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0059", + "Question Type": "Single Choice", + "Text": "From the perspective of the building with a clear L-shape in the topright corner, what is the orientation of the building with an L-shape in thebottom left corner?", + "CoT": [ + "Step 1: Bounding Box -[<0><962><25><1007>] is located in the bottom left corner of the diagramand presents the smallest L-shape.", + "Step 2: Bounding Box -[<0><962><25><1007>] is located in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<962><260><1008><298>] is located in the upper right corner of the pictureand is clearly L-shaped.", + "Step 4: Bounding Box -[<962><260><1008><298>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<0><962><25><1007>] is on the below from Bounding Box -[<962><260><1008><298>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000491_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0060", + "Question Type": "Single Choice", + "Text": "From the perspective of the longest white rectangular building in theparking lot, where is the trapezoidal building with a white roof?", + "CoT": [ + "Step 1: Bounding Box -[<957><154><1024><258>] is the largest white trapezoidal building.", + "Step 2: Bounding Box -[<957><154><1024><258>] is located in the upper right corner of the image .", + "Step 3: Box 7 is the rectangular building with the longest white roof in thecenter of the parking lot.", + "Step 4: Bounding Box -[<381><602><461><822>] is located in the bottom left corner of the picture.", + "Step 5: Bounding Box -[<957><154><1024><258>] is on the right from Bounding Box -[<381><602><461><822>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000469_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0061", + "Question Type": "Single Choice", + "Text": "From the perspective of the first rectangular building in the firstrow of the green belt on the far left side of the road, where is the firstsquare building in the first row of the green belt on the right side of theroad?", + "CoT": [ + "Step 1: Bounding Box -[<401><33><434><93>] is the first rectangular building on the green belt onthe left side of the road.", + "Step 2: Bounding Box -[<401><33><434><93>] is located in the upper left corner of the image.", + "Step 3: Bounding Box -[<400><172><455><217>] is the first square building in the first row of thegreen belt on the right side of the road.", + "Step 4: Bounding Box -[<400><172><455><217>] is located in the upper left corner of the image.", + "Step 5: Bounding Box -[<401><33><434><93>] is on the above from Bounding Box -[<400><172><455><217>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000478_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0062", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building with a white roofbelow the parking lot, where is the longest L-shaped white roof building onthe left side of the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<161><883><338><966>] is the largest rectangular white roofed building.", + "Step 2: Bounding Box -[<161><883><338><966>] is located in the bottom left corner of the image.", + "Step 3: Bounding Box -[<64><591><209><883>] is the longest L-shaped white roofed building.", + "Step 4: Bounding Box -[<64><591><209><883>] is located in the bottom left corner of the image.", + "Step 5: Bounding Box -[<64><591><209><883>] is on the above from Bounding Box -[<161><883><338><966>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000492_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0063", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest L-shaped white roofed building,where is the longest rectangular green roofed building below the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<144><238><310><355>] is the largest L-shaped white roofed building.", + "Step 2: Bounding Box -[<144><238><310><355>] is located in the bottom left corner of the image.", + "Step 3: Bounding Box -[<276><363><417><470>] is located below the parking lot, to the right is theroad. It is the longest rectangular green roof building", + "Step 4: Bounding Box -[<276><363><417><470>] is located in the bottom left corner of the image.", + "Step 5: Bounding Box -[<276><363><417><470>] on the below from Bounding Box -[<144><238><310><355>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000514_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0064", + "Question Type": "Single Choice", + "Text": "From the perspective of the building on the left side located at theintersection of two roads, where is the smallest purple red roof building?", + "CoT": [ + "Step 1: Bounding Box -[<698><428><760><483>] is on the left side of the intersection of tworoads.", + "Step 2: Bounding Box -[<698><428><760><483>] is in the upper right corner of the picture.", + "Step 3: The smallest purple red roof building in the entire picture.", + "Step 4: Bounding Box -[<328><831><410><902>] is in the bottom left corner of the picture.", + "Step 5: Bounding Box -[<698><428><760><483>] is on the below from Bounding Box -[<328><831><410><902>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000397_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0065", + "Question Type": "Single Choice", + "Text": "From the perspective of the second largest white roof building areain the bottom right corner of the picture, where is the third largest whiteroof building area?", + "CoT": [ + "Step 1: Bounding Box -[<589><809><627><892>] is the white roof is the second largest building inthe entire picture.", + "Step 2: Bounding Box -[<589><809><627><892>] is in the bottom right corner of the picture", + "Step 3: There are some buildings located in the bottom right corner of thepicture, which is the third largest building.", + "Step 4: Bounding Box -[<654><816><697><889>] is in the bottom right corner of the picture.", + "Step 5: Bounding Box -[<589><809><627><892>] on the right from Bounding Box -[<654><816><697><889>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000493_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0066", + "Question Type": "Single Choice", + "Text": "Where is the rectangular building with a gray roof located above theintersection of the road?", + "CoT": [ + "Step 1: Bounding Box -[<312><195><341><225>] is the rectangular shaped building above theintersection of this road.", + "Step 2: Bounding Box -[<312><195><341><225>] is located in the upper left corner of the entireimage.", + "Step 3: There are some buildings located in the bottom right corner of thepicture.", + "Step 4: Bounding Box -[<133><539><245><621>] is located in the lower left corner of the entireimage, there is the largest building with a rectangular gray roof.", + "Step 5: Bounding Box -[<312><195><341><225>] is on the below from Bounding Box -[<133><539><245><621>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000129_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0067", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest rectangular shaped building inthe entire image, where is the building with a gray roof and an N-shapedroof?", + "CoT": [ + "Step 1: Bounding Box -[<468><383><566><460>] is the largest rectangular shaped building in theentire image.", + "Step 2: Bounding Box -[<468><383><566><460>] is located directly above the picture.", + "Step 3: There are some buildings in the bottom right corner of the picture,which are the largest N-shaped buildings in the entire picture.", + "Step 4: Bounding Box -[<754><797><869><876>] is located in the lower right corner of the picture.", + "Step 5: Bounding Box -[<468><383><566><460>] is on the below from Bounding Box -[<754><797><869><876>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000364_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0068", + "Question Type": "Single Choice", + "Text": "From the perspective of the buildings in the sea area on the leftside below the road, where is the rectangular building above the turning pointon the left side of the road?", + "CoT": [ + "Step 1: Bounding Box -[<153><308><304><460>] is located below the road, with the ocean behind it.", + "Step 2: Bounding Box -[<153><308><304><460>] is located in the upper left corner of the picture.", + "Step 3: There are two buildings located above the leftmost road here.", + "Step 4: Bounding Box -[<152><210><181><252>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<153><308><304><460>] is on the above from Bounding Box -[<152><210><181><252>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000008_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0069", + "Question Type": "Single Choice", + "Text": "From the perspective of the building on the right side at theintersection of the second horizontal road and the second vertical road, whereis the building on the lower left side at the intersection of the threevertical roads and the second horizontal road?", + "CoT": [ + "Step 1: Bounding Box -[<636><716><798><782>] is located above the second horizontal road and to theright of the second vertical road.", + "Step 2: Bounding Box -[<636><716><798><782>] is located in the lower right corner of the picture.", + "Step 3: There are some buildings located below the second horizontal road andto the left of the fourth vertical road.", + "Step 4: Bounding Box -[<770><820><827><957>] is located in the lower right corner of the picture.", + "Step 5: Bounding Box -[<636><716><798><782>] is on the below from Bounding Box -[<770><820><827><957>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000058_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0070", + "Question Type": "Single Choice", + "Text": "From the perspective of the rectangular building with a white roof onthe left side of the picture, where is the building located below theintersection of the two roads in the lower left corner of the picture?", + "CoT": [ + "Step 1: Bounding Box -[<51><511><123><558>] is located on the upper left corner of theintersection of the first horizontal road from top to bottom and the secondvertical road from left to right, with a rectangular white roof.", + "Step 2: Bounding Box -[<51><511><123><558>] is located on the far left side of the picture.", + "Step 3: There are some buildings located at the bottom left of the picture,with the second horizontal road from top to bottom in front and the thirdvertical road from left to right on the left.", + "Step 4: Bounding Box -[<300><759><396><826>] is located in the lower left corner of the picture.", + "Step 5: Bounding Box -[<51><511><123><558>] is on the below from Bounding Box -[<300><759><396><826>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000202_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0071", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<673><532><703><572>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<673><532><703><572>] is located in the right side of the picture.", + "Step 3: There are six buildings that are adjacent to the road, and BoundingBox 6 is the smallest of them.", + "Step 4: Bounding Box -[<569><595><602><650>] is located in the center of the picture.", + "Step 5: Bounding Box -[<673><532><703><572>] is on the right from Bounding Box -[<569><595><602><650>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000184_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0072", + "Question Type": "Single Choice", + "Text": "From the perspective of the longest rectangular building on the leftside of the highway, where is the largest square white roofed building on theright side of the highway?", + "CoT": [ + "Step 1: Bounding Box -[<448><31><550><122>] is the longest rectangular building on the left sideof the highway", + "Step 2: Bounding Box -[<448><31><550><122>] is located in the upper left corner of the picture.", + "Step 3: Bounding Box -[<1><95><261><130>] is the largest square white roofed building on theright side of the highway.", + "Step 4: Bounding Box -[<1><95><261><130>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<448><31><550><122>] on the right from Bounding Box -[<1><95><261><130>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000405_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0073", + "Question Type": "Single Choice", + "Text": "From the perspective of the building in the lower right corner of thefigure, which is close to the ring road and presents a convex shape, the lowerright corner of the figure is close to the ring road and presents a convexshape ♥ Where is the type of building?", + "CoT": [ + "Step 1: Bounding Box -[<809><798><877><858>] is located near the circular path in the lower rightcorner of the figure and has a similar shape ♥ type.", + "Step 2: Bounding Box -[<809><798><877><858>] is located near the circular road in the lower rightcorner of the figure.", + "Step 3: Bounding Box -[<754><918><810><1021>] is located near the circular path in the lower rightcorner of the figure and has a convex shape.", + "Step 4: Bounding Box -[<754><918><810><1021>] is located near the circular road in the lower rightcorner of the figure.", + "Step 5: Bounding Box -[<809><798><877><858>] is on the above from Bounding Box -[<754><918><810><1021>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000454_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0074", + "Question Type": "Single Choice", + "Text": "Where is the grey four-cornered roof building from the perspective ofthe buildings located at the bottom right corner of the picture that do notclosely border the main roads?", + "CoT": [ + "Step 1: Bounding Box -[<349><390><402><461>] is a four-cornered building with a grey roof.", + "Step 2: Bounding Box -[<349><390><402><461>] is located in the center of the picture.", + "Step 3: There are many buildings located in the lower right corner of thepicture and not adjacent to the main road,and Bounding Box -[<881><926><916><952>] is the smallestof them.", + "Step 4: Bounding Box -[<881><926><916><952>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<349><390><402><461>] is on the above from Bounding Box -[<881><926><916><952>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000462_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0075", + "Question Type": "Single Choice", + "Text": "From the perspective of the widest rectangular gray roof building inthe upper right corner of the intersection, where is the longest rectangulargray roof building on the left side of the parking lot?", + "CoT": [ + "Step 1: Bounding Box -[<736><211><811><338>] is the widest rectangular gray roof building in theupper right corner of the intersection.", + "Step 2: Bounding Box -[<736><211><811><338>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<814><188><857><358>] is the longest rectangular gray roof building on theleft side of the parking lot.", + "Step 4: Bounding Box -[<814><188><857><358>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<736><211><811><338>] on the below from Bounding Box -[<814><188><857><358>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000473_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0076", + "Question Type": "Single Choice", + "Text": "Where is the building with irregularly shaped brown roof from theperspective of the building with brown roof and close to the road?", + "CoT": [ + "Step 1: Bounding Box -[<278><0><324><25>] is a building with irregularly-shaped brown roof.", + "Step 2: Bounding Box -[<278><0><324><25>] is located in the upper left corner of the picture.", + "Step 3: There are many buildings in the upper right corner of the picture.The surrounding buildings are very similar to Bounding Box -[<891><434><959><489>].", + "Step 4: Bounding Box -[<891><434><959><489>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<278><0><324><25>] is on the left from Bounding Box -[<891><434><959><489>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000474_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0077", + "Question Type": "Single Choice", + "Text": "Where is the only fan-shaped building in the image located relativeto the largest circular structure?", + "CoT": [ + "Step 1: Bounding Box -[<984><117><1024><183>] is the only fan-shaped building.", + "Step 2: Bounding Box -[<984><117><1024><183>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<373><27><449><96>] is the largest circular building.", + "Step 4: Bounding Box -[<373><27><449><96>] is located in the middle of the top of the picture.", + "Step 5: Bounding Box -[<984><117><1024><183>] is on the right from Bounding Box -[<373><27><449><96>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000275_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0078", + "Question Type": "Single Choice", + "Text": "Where is the largest T-shaped building located relative to thelongest rectangular structure in the diagram?", + "CoT": [ + "Step 1: Bounding Box -[<780><68><871><136>] is the largest T-shaped building in the picture. ", + "Step 2: Bounding Box -[<780><68><871><136>] is located in the upper right corner of the picture.", + "Step 3: Bounding Box -[<840><598><859><798>] is the longest rectangular building in the picture.", + "Step 4: Bounding Box -[<840><598><859><798>] is located in the lower right corner of the picture.", + "Step 5: Bounding Box -[<780><68><871><136>] is above from Bounding Box -[<840><598><859><798>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0079", + "Question Type": "Single Choice", + "Text": "Where is the largest irregularly-shaped white building from theperspective of buildings that are relatively far away from the road?", + "CoT": [ + "Step 1: Bounding Box -[<7><700><331><955>] It is the largest irregular-shaped white building.", + "Step 2: Bounding Box -[<7><700><331><955>] is located in the bottom left corner of the picture.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<7><700><331><955>] is the largest of them.", + "Step 4: Bounding Box -[<959><866><1024><967>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<7><700><331><955>] is on the left from Bounding Box -[<959><866><1024><967>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000435_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0080", + "Question Type": "Single Choice", + "Text": "Where is the building with the brown four-cornered roof from theperspective of the building with the smallest area and not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<139><974><160><1002>] is the brown square roofed building.", + "Step 2: Bounding Box -[<154><607><173><622>] is located in the bottom left corner of the picture.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<154><607><173><622>] is the smallest of them.", + "Step 4: Bounding Box -[<139><974><160><1002>] is located in the bottom left corner of the picture.", + "Step 5: Bounding Box -[<154><607><173><622>] is on the above from Bounding Box -[<139><974><160><1002>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000265_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0081", + "Question Type": "Single Choice", + "Text": "Where is the smallest building with a brown four-cornered roof fromthe perspective of the building with the largest area and closest to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<696><902><709><917>] is the smallest brown square roofed building.", + "Step 2: Bounding Box -[<696><902><709><917>] is located in the bottom right corner of thepicture.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<696><902><709><917>] is the smallest of them.", + "Step 4: Bounding Box -[<928><259><939><268>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<696><902><709><917>] is on the below from Bounding Box -[<928><259><939><268>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0082", + "Question Type": "Single Choice", + "Text": "Where is the smallest white four-cornered roofed building from theperspective of the building with the smallest area and closest to the road?", + "CoT": [ + "Step 1: Bounding Box -[<981><400><1024><443>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<531><841><542><861>] is located in the bottom right corner of thepicture.", + "Step 3: There are many buildings that are adjacent to the road, and BoundingBox 6 is the smallest of them.", + "Step 4: Bounding Box -[<981><400><1024><443>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<531><841><542><861>] is on the below from Bounding Box -[<981><400><1024><443>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000167_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0083", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the largest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<397><725><411><741>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<397><725><411><741>] is located in the bottom left corner of the picture.", + "Step 3: There are many buildings that are adjacent to the road, and BoundingBox 6 is the smallest of them.", + "Step 4: Bounding Box -[<52><912><109><977>] is located in the bottom left corner of the picture.", + "Step 5: Bounding Box -[<397><725><411><741>] is on the right from Bounding Box -[<52><912><109><977>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000133_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0084", + "Question Type": "Single Choice", + "Text": "Where is the white four-cornered roof building from the perspectiveof the building adjacent to the middle road?", + "CoT": [ + "Step 1: Bounding Box -[<229><104><336><207>] is the white four-cornered roof building", + "Step 2: Bounding Box -[<229><104><336><207>] is located in the upper left corner of the picture.", + "Step 3: There are many buildings that are adjacent to the road, and BoundingBox 6 is the largest of them.", + "Step 4: Bounding Box -[<412><143><470><196>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<229><104><336><207>] is on the below from Bounding Box -[<412><143><470><196>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000039_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0085", + "Question Type": "Single Choice", + "Text": "Where is the building with the brown rectangular roof from theperspective of buildings that are not adjacent to road?", + "CoT": [ + "Step 1: Bounding Box -[<499><63><525><88>] is the building that not located along the street.", + "Step 2: Bounding Box -[<499><63><525><88>] is located in the upper side of the picture.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<830><819><857><842>] is the smallest of them.", + "Step 4: Bounding Box -[<830><819><857><842>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<830><819><857><842>] is on the below from Bounding Box -[<499><63><525><88>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000373_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0086", + "Question Type": "Single Choice", + "Text": "Where is the smallest irregular brown building from the perspectiveof the building with the smallest area and not adjacent to the road?", + "CoT": [ + "Step 1: Bounding Box -[<404><491><415><502>] is the smallest irregularly-shaped brown building", + "Step 2: Bounding Box -[<404><491><415><502>] is located on the right side away from the road.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<404><491><415><502>] is the smallest of them.", + "Step 4: Bounding Box -[<285><838><301><858>] is located on the left side far away from the road.", + "Step 5: Bounding Box -[<404><491><415><502>] is on the above from Bounding Box -[<285><838><301><858>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000289_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0087", + "Question Type": "Single Choice", + "Text": "Where is the smallest brown rectangular building from the perspectiveof the building with the largest area and closest to the road?", + "CoT": [ + "Step 1: Bounding Box -[<100><243><129><265>] is the smallest brown rectangular building.", + "Step 2: Bounding Box -[<100><243><129><265>] is the building located on the left side of the entirepicture.", + "Step 3: There are many buildings that are adjacent to the road, and BoundingBox 6 is the smallest of them.", + "Step 4: Bounding Box -[<357><309><602><415>] is located in the center of the picture.", + "Step 5: Bounding Box -[<100><243><129><265>] on the left from Bounding Box -[<357><309><602><415>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000501_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0088", + "Question Type": "Single Choice", + "Text": "Where is the smallest irregular brown building from the perspectiveof the building with the smallest area and not adjacent to the road?", + "CoT": [ + "Step 1: Bounding Box -[<675><239><701><258>] is the smallest irregularly-shaped brown building.", + "Step 2: Bounding Box -[<675><239><701><258>] is located in the upper right corner of the picture.", + "Step 3: There are many buildings that are not adjacent to the road, andBounding Box -[<382><493><412><515>] is the smallest of them.", + "Step 4: Bounding Box -[<382><493><412><515>] is located in the center of the picture.", + "Step 5: Bounding Box -[<675><239><701><258>] is on the above from Bounding Box -[<382><493><412><515>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000461_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0089", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<430><223><446><245>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<430><223><446><245>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<461><251><479><271>] is the smallest of them.", + "Step 4: Bounding Box -[<461><251><479><271>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<430><223><446><245>] on the above from Bounding Box -[<461><251><479><271>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000430_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0090", + "Question Type": "Single Choice", + "Text": "Where is the smallest brown square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<925><974><944><1004>] is the smallest brown square roofed building.", + "Step 2: Bounding Box -[<925><974><944><1004>] is located in the bottom right corner of thepicture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<925><974><944><1004>] is the smallest of them.", + "Step 4: Bounding Box -[<845><968><898><1024>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<925><974><944><1004>] on the right from Bounding Box -[<845><968><898><1024>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000400_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0091", + "Question Type": "Single Choice", + "Text": "Where is the smallest brown square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<504><40><529><66>] is the smallest brown square roofed building.", + "Step 2: Bounding Box -[<504><40><529><66>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<504><40><529><66>] is the smallest of them.", + "Step 4: Bounding Box -[<417><61><443><88>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<504><40><529><66>] on the right from Bounding Box -[<417><61><443><88>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000389_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0092", + "Question Type": "Single Choice", + "Text": "Where is the smallest brown square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<2><0><25><36>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<2><0><25><36>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<2><0><25><36>] is the smallest of them.", + "Step 4: Bounding Box -[<79><1><114><36>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<2><0><25><36>] on the left from Bounding Box -[<79><1><114><36>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000381_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0093", + "Question Type": "Single Choice", + "Text": "Where is the smallest brown square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<322><5><343><29>] is the smallest brown square roofed building.", + "Step 2: Bounding Box -[<322><5><343><29>] is located in the upper left corner of the picture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<322><5><343><29>] is the smallest of them.", + "Step 4: Bounding Box -[<369><0><417><30>] is located in the upper left corner of the picture.", + "Step 5: Bounding Box -[<322><5><343><29>] on the left from Bounding Box -[<369><0><417><30>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000369_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0094", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<569><644><586><662>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<569><644><586><662>] is located in the bottom right corner of thepicture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<514><609><534><628>] is the smallest of them.", + "Step 4: Bounding Box -[<514><609><534><628>] is located in the bottom right corner of thepicture.", + "Step 5: Bounding Box -[<569><644><586><662>] on the below from Bounding Box -[<514><609><534><628>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000346_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0095", + "Question Type": "Single Choice", + "Text": "From the perspective of the largest building in the entire map,where is the T-shaped building located?", + "CoT": [ + "Step 1: Bounding Box -[<1><148><186><364>] is located on the left side of the road and is thelargest building in the entire picture.", + "Step 2: Bounding Box -[<1><148><186><364>] is located in the upper left corner of the picture.", + "Step 3: There are some buildings located in the lower right corner of theintersection of two roads, in the shape of a letter't '.", + "Step 4: Bounding Box -[<759><947><953><1022>] is located in the lower right corner of the picture.", + "Step 5: Bounding Box -[<1><148><186><364>] is on the below from Bounding Box -[<759><947><953><1022>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000145_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0096", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<696><902><709><917>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<696><902><709><917>] is located in the bottom right corner of thepicture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<928><259><939><268>] is the smallest of them.", + "Step 4: Bounding Box -[<928><259><939><268>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<696><902><709><917>] on the below from Bounding Box -[<928><259><939><268>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0097", + "Question Type": "Single Choice", + "Text": "Where is the smallest white square roofed building from theperspective of the building with the smallest area that is not adjacent to theroad?", + "CoT": [ + "Step 1: Bounding Box -[<696><902><709><917>] is the smallest white square roofed building.", + "Step 2: Bounding Box -[<696><902><709><917>] is located in the bottom right corner of thepicture.", + "Step 3: There are three buildings that are not adjacent to the road, andBounding Box -[<928><259><939><268>] is the smallest of them.", + "Step 4: Bounding Box -[<928><259><939><268>] is located in the upper right corner of the picture.", + "Step 5: Bounding Box -[<696><902><709><917>] on the below from Bounding Box -[<928><259><939><268>]'s perspective." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + }, + { + "Question_id": "Spatial relationships under complex conditions/0098", + "Question Type": "Single Choice", + "Text": "Where is the smallest building from the perspective of the smallestbuildings that do not face the street with a white roof?", + "CoT": [ + "Step 1: Bounding box -[<696><902><709><917>] is an irregular white building with a roof on the leftside of the picture, and there are no other buildings around.", + "Step 2:Box 6 is located at the left edge of the picture.", + "Step 3:There are three buildings on the left side of the picture, not facingthe street, arranged up and down. Among them, the boundary box 7 is the one inthe middle.", + "Step 4: Bounding box -[<928><259><939><268>] is located at the left edge of the picture.", + "Step 5: Bounding Box -[<696><902><709><917>] is on the below from Bounding Box -[<928><259><939><268>]'s above." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Spatial relationships under complex conditions", + "Answer Choices": [ + "(A) Below", + "(B) Left", + "(C) Right", + "(D) Above", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ] + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Visual_grounding_of_damaged_individual_buildings.json b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Visual_grounding_of_damaged_individual_buildings.json new file mode 100644 index 0000000000000000000000000000000000000000..e5f2041e1940b68820646ebcd6c4c86296f6f8fa --- /dev/null +++ b/jsons/Pedosphere/Surface_Disaster_Assessment/Reasoning/Visual_grounding_of_damaged_individual_buildings.json @@ -0,0 +1,3062 @@ +[ + { + "Question_id": "Visual grounding of damaged individual buildings/0000", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The walls and roof of this building have huge cracks, located in the bottom left corner of the picture, surrounded by green plants.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 88major-damage buildings and 7 destroyed buildings and 5 unclassifiedbuildings.", + "Step 2: This building is located in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<296><783><341><838>] has a rectangular green roof.", + "Step 4: The roof and walls of Bounding Box -[<296><783><341><838>] have all cracked open.", + "Step 5: Bounding Box -[<296><783><341><838>] is destroyed.", + "Step 6: Bounding Box -[<296><783><341><838>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<296><783><341><838>]", + "(B) Bounding Box -[<226><441><268><536>]", + "(C) Bounding Box -[<213><603><283><673>]", + "(D) Bounding Box -[<763><801><813><886>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000361_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0001", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The walls and roof of this building have obvious cracks. It islocated in the lower left corner of the picture and is the smallest triangularbuilding near the main road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 139major-damaged buildings and 10 destroyed buildings.", + "Step 2: There are some buildings located on the left side of thepicture.", + "Step 3: Bounding Box -[<1><703><11><751>] has a triangular green roof.", + "Step 4: The roof and walls of Bounding Box -[<1><703><11><751>] has obvious cracks.", + "Step 5: Bounding Box -[<1><703><11><751>] is major-damage.", + "Step 6: Bounding Box -[<1><703><11><751>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<1><703><11><751>]", + "(B) Bounding Box 9", + "(C) Bounding Box 10", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000365_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0002", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is no-damaged building. It is located at the bottomright of the picture.It has a triangular green roof", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 156undamaged buildings.", + "Step 2: There are some buildings located in the bottom left corner of theentire picture.", + "Step 3: Bounding Box -[<220><995><330><1024>] have a triangular green roof.", + "Step 4: The roof and walls of Bounding Box -[<220><995><330><1024>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<220><995><330><1024>] is no-damaged.", + "Step 6: Bounding Box -[<220><995><330><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<220><995><330><1024>]", + "(B) Bounding Box -[<350><961><390><1003>]", + "(C) Bounding Box -[<480><991><542><1019>]", + "(D) Bounding Box -[<612><927><648><985>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000366_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0003", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture. there is a semi-circular green roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 79undamaged buildings.", + "Step 2: Bounding Box -[<829><747><954><887>] located in the bottom right corner of the image.", + "Step 3: Bounding Box -[<829><747><954><887>] above is a very wide highway and it have a semi-circular green roof.", + "Step 4: The roof and walls of Bounding Box -[<829><747><954><887>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<829><747><954><887>] is no-damaged.", + "Step 6: Bounding Box -[<829><747><954><887>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<829><747><954><887>]", + "(B) Bounding Box -[<601><598><686><680>]", + "(C) Bounding Box -[<816><568><861><640>]", + "(D) Bounding Box -[<706><553><746><600>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000367_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0004", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.above it is a road, which is the longest white rectangular building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 134undamaged buildings.", + "Step 2: There are some buildings located in the bottom right corner of thepicture, above it is a road.", + "Step 3: Bounding Box -[<650><656><692><1024>] located on the right side of the parking lot, withthe longest white rectangular roof.", + "Step 4: The roof and walls of Bounding Box -[<650><656><692><1024>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<650><656><692><1024>] is no-damaged.", + "Step 6: Bounding Box -[<650><656><692><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<650><656><692><1024>]", + "(B) Bounding Box -[<774><636><823><672>]", + "(C) Bounding Box -[<866><642><888><664>]", + "(D) Bounding Box -[<959><626><988><664>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000379_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0005", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is undamaged. It is located in the center of thepicture, with parking lots to its left and below. It is the largestrectangular building around the parking lot.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 2: This building is located in the center of the picture,.", + "Step 3: Bounding Box -[<507><491><755><691>] is left and lower sides are both parking lots, makingit the largest rectangular white roofed building around the parking lot.", + "Step 4: The roof and walls of Bounding Box -[<507><491><755><691>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<507><491><755><691>] is no-damaged.", + "Step 6: Bounding Box -[<507><491><755><691>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<507><491><755><691>]", + "(B) Bounding Box -[<469><722><519><782>]", + "(C) Bounding Box -[<575><734><623><750>]", + "(D) Bounding Box -[<721><720><761><754>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000380_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0006", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomleft of the picture. This building is the largest cross shaped structure.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 63undamaged buildings.", + "Step 2: There are 7 buildings located at the bottom left of the picture.", + "Step 3: Bounding Box -[<149><724><446><862>] is the largest cross shaped structure located belowthe parking lot.", + "Step 4: The roof and walls of Bounding Box -[<149><724><446><862>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<149><724><446><862>] is no-damaged.", + "Step 6: Bounding Box -[<149><724><446><862>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<149><724><446><862>]", + "(B) Bounding Box -[<573><784><603><878>]", + "(C) Bounding Box -[<527><620><589><688>]", + "(D) Bounding Box -[<485><496><555><552>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000396_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0007", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building.It is located in the middleof the left side of the picture. It is located at the very bottom of theentire parking lot.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 41undamaged buildings.", + "Step 2: there are some buildings located in the middle of the left side ofthe picture.", + "Step 3: Bounding Box -[<526><715><609><765>] is the rectangular building located at the very bottomof the parking lot.", + "Step 4: The roof and walls of Bounding Box -[<35><459><119><491>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<35><459><119><491>] is no-damaged.", + "Step 6: Bounding Box -[<35><459><119><491>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<526><715><609><765>]", + "(B) Bounding Box -[<35><459><119><491>]", + "(C) Bounding Box -[<433><264><538><356>]", + "(D) Bounding Box -[<690><814><825><956>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000374_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0008", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is undamaged. It is located in the bottom left corner of the picture. It is the longest rectangular building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 104undamaged buildings.", + "Step 2: There is are some buildings located in the bottom left corner ofthe picture.", + "Step 3: Bounding Box -[<0><746><419><770>] is the longest rectangular building.", + "Step 4: The roof and walls of Bounding Box -[<0><746><419><770>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<0><746><419><770>] is no-damaged.", + "Step 6: Bounding Box -[<0><746><419><770>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><746><419><770>]", + "(B) Bounding Box -[<445><346><478><418>]", + "(C) Bounding Box -[<457><503><487><594>]", + "(D) Bounding Box -[<467><701><508><790>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000413_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0009", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is a major-damage building. It is located in themiddle of the picture. It is located above the river and is surrounded by aring of square buildings.", + "CoT": [ + "Step 1:There is a square building in the middle of the picture.", + "Step 2: Bounding box -[<297><210><317><393>] is the building with the largest ratio of length towidth above the river.", + "Step 3:Bounding box -[<297><210><317><393>] is the square building with the largest ratio of lengthto width above the river.", + "Step 4: The roof and walls of bounding box 8 are more damaged, with morecracks, tilts, or damage.", + "Step 5: Bounding Box -[<297><210><317><393>] is major-damage.", + "Step 6: Bounding Box -[<297><210><317><393>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<297><210><317><393>]", + "(B) Bounding Box -[<131><45><218><91>]", + "(C) Bounding Box -[<133><134><229><180>]", + "(D) Bounding Box -[<98><215><165><253>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000434_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0010", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is minor damaged building.It is located at thebottom right of the picture.It is located in the upper right corner of thecrossroads, beneath the largest building in the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 87undamaged buildings and 2 minor damaged buildings.", + "Step 2: There are some buildings located at the lower right corner of thepicture.", + "Step 3: Bounding Box -[<814><685><974><957>] is located in the upper right corner of theintersection, below the largest building in the picture.", + "Step 4: Bounding Box -[<814><685><974><957>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 5: Bounding Box -[<814><685><974><957>] is minor-damage.", + "Step 6: Bounding Box -[<814><685><974><957>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<76><680><188><832>]", + "(B) Bounding Box -[<814><685><974><957>]", + "(C) Bounding Box -[<273><958><311><1017>]", + "(D) Bounding Box -[<89><912><201><985>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000443_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0011", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is major-damage. It is located at the bottom left ofthe picture. It is located at the bottom left of the image and the bottomright of the river channel. It is a white roof.", + "CoT": [ + "Step 1:There are 99 major-damage buildings and 4 destroyed buildings.", + "Step 2:In the lower left of the image, the river channel and the lower rightbuildings circle the river.", + "Step 3:Bounding box -[<357><879><419><946>] is a white roof located at the bottom right of theriver channel at the bottom left of the image.", + "Step 4:The roof and walls of bounding box 8 are severely damaged, with manycracks, tilts, or damage.", + "Step 5: Bounding Box -[<357><879><419><946>] is major-damage.", + "Step 6: Bounding Box -[<357><879><419><946>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<357><879><419><946>]", + "(B) Bounding Box -[<455><662><530><730>]", + "(C) Bounding Box -[<551><841><594><890>]", + "(D) Bounding Box -[<200><906><249><960>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000463_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0012", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 7minor-damaged buildings and 87 major-damaged buildings.", + "Step 2: There are many buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<555><930><634><1005>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<555><930><634><1005>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<555><930><634><1005>] is no-damaged.", + "Step 6: Bounding Box -[<555><930><634><1005>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<518><826><543><852>]", + "(B) Bounding Box -[<555><930><634><1005>]", + "(C) Bounding Box -[<598><790><618><813>]", + "(D) Bounding Box -[<586><837><598><859>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000471_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0013", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is fully destroyed. It is located in the bottomright corner of the picture. It is the last structure in the row of similarbuildings below the road, counted from top to bottom.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged building, 5 minor damaged buildings, 9 major damaged buildings, 16fully destroyed buildings and 4 unclassified buildings.", + "Step 2: There are some buildings in the lower right corner of the picture.", + "Step 3: Bounding Box -[<765><973><783><992>] is the last structure in the row of similar buildingsbelow the road, counted from top to bottom.", + "Step 4: Bounding Box -[<765><973><783><992>] has completely collapsed with no remaining structuralintegrity, leaving only rubble and debris.", + "Step 5: Bounding Box -[<765><973><783><992>] is fully destroyed.", + "Step 6: Bounding Box -[<765><973><783><992>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<610><460><678><530>]", + "(B) Bounding Box -[<123><393><192><458>]", + "(C) Bounding Box -[<765><973><783><992>]", + "(D) Bounding Box -[<458><693><551><724>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000198_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0014", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is major damaged. It is located in the lower rightcorner of the image. Its shape is L-shaped and it surrounds a squarebuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 29undamaged buildings, 11 major damaged buildings and 7 minor damagedbuildings.", + "Step 2: There are two buildings in the lower right corner of the image.", + "Step 3: Bounding Box -[<833><754><1024><1024>] is L-shaped and encloses a square building.", + "Step 4: Bounding Box -[<833><754><1024><1024>] has severe structural collapse, extensive wallbreaches, and partial roof failure.", + "Step 5: Bounding Box -[<833><754><1024><1024>] is major damaged.", + "Step 6: Bounding Box -[<833><754><1024><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<833><754><1024><1024>]", + "(B) Bounding Box -[<553><297><650><396>]", + "(C) Bounding Box -[<331><1><391><173>]", + "(D) Bounding Box -[<637><28><688><127>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000455_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0015", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 3destroyed buildings,5 unclassified buildings,6 minor damaged buildings and 179major damaged buildings.", + "Step 2: There are six buildings located at the bottom left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<25><951><65><992>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<25><951><65><992>] are intact with many cracks,tilting or damage.", + "Step 5: Bounding Box -[<25><951><65><992>] is major damaged.", + "Step 6: Bounding Box -[<25><951><65><992>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<25><951><65><992>]", + "(B) Bounding Box -[<34><890><85><942>]", + "(C) Bounding Box -[<94><882><129><928>]", + "(D) Bounding Box -[<89><972><126><995>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000347_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0016", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located in the right of the large building in the intersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 51undamaged buildings and 2 minor damaged buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<863><881><955><953>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<863><881><955><953>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<863><881><955><953>] is no-damaged.", + "Step 6: Bounding Box -[<863><881><955><953>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<610><851><840><934>]", + "(B) Bounding Box -[<992><996><1018><1018>]", + "(C) Bounding Box -[<863><881><955><953>]", + "(D) Bounding Box -[<613><1003><629><1018>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000375_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0017", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is destroyed building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the destroyed building in the upper right corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 48minor damaged buildings and 10 destroyed buildings.", + "Step 2: There are 2 buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<930><739><977><780>] is the building which located below the destroyedbuilding in the upper corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<930><739><977><780>] are intact with cracks, tiltingor damage.", + "Step 5: Bounding Box -[<930><739><977><780>] is destroyed.", + "Step 6: Bounding Box -[<930><739><977><780>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<739><781><777><832>]", + "(B) Bounding Box -[<963><824><1000><864>]", + "(C) Bounding Box -[<930><739><977><780>]", + "(D) Bounding Box -[<828><801><875><827>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000462_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0018", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is fully destroyed. It is located in the lower leftportion of the image. It is the rightmost structure among the four buildingsadjacent to the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 9 fullydestroyed buildings.", + "Step 2: There are some buildings located in the lower left corner of thepicture.", + "Step 3: Bounding Box -[<44><804><60><818>] is the rightmost structure among the four buildingsadjacent to the road.", + "Step 4: Bounding Box -[<44><804><60><818>] has completely collapsed with no remaining structuralintegrity, leaving only rubble and debris.", + "Step 5: Bounding Box -[<44><804><60><818>] is Fully destroyed.", + "Step 6: Bounding Box -[<44><804><60><818>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<44><804><60><818>]", + "(B) Bounding Box -[<102><774><144><825>]", + "(C) Bounding Box -[<132><659><190><721>]", + "(D) Bounding Box -[<288><677><401><738>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000310_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0019", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is minor damaged building. It is located at thelower left of the picture. It is an N-shaped building far from the coast. ", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 279minor damaged buildings, 32 major damaged buildings, 18 fully destroyedbuildings and 6 unclassified buildings.", + "Step 2: There are some buildings in the lower left corner of the picture.", + "Step 3: Bounding Box -[<258><845><386><989>] is an N-shaped building far from the coast.", + "Step 4: Bounding Box -[<258><845><386><989>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 5: Bounding Box -[<258><845><386><989>] is Minor damaged.", + "Step 6: Bounding Box -[<258><845><386><989>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<258><845><386><989>]", + "(B) Bounding Box -[<199><787><243><823>]", + "(C) Bounding Box -[<198><737><250><755>]", + "(D) Bounding Box -[<206><624><246><650>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000372_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0020", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a slightly damaged building. It is located in theupper right corner of the picture. It is located in the top right corner ofthe road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings, 3 unclassified buildings, 4 minor—damage buildings and 1major-damage building.", + "Step 2: There are seven buildings in the upper right corner of the road in the upper right corner of the picture.", + "Step 3:Bounding box -[<844><0><877><31>] is the rightmost building located in the upper-rightcorner of the highway.", + "Step 4:The roof and walls of bounding box 8 have a small amount of damage anda small amount of cracks, tilts, or damage.", + "Step 5: Bounding Box -[<844><0><877><31>] is minor—damage.", + "Step 6: Bounding Box -[<844><0><877><31>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<844><0><877><31>]", + "(B) Bounding Box -[<713><9><763><73>]", + "(C) Bounding Box -[<932><689><964><724>]", + "(D) Bounding Box -[<884><712><922><758>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000009_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0021", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is undamaged and is located on the right side ofthe picture. It is the biggest building in the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings, 21 minor-damage buildings, 3 major-damage buildings, 1destroyed building and 3 unclassified buildings.", + "Step 2: There are fifteen buildings above the right side of the road at thebottom of the picture.", + "Step 3: Bounding box -[<771><292><850><344>] is the largest among the fifteen buildings locatedabove the right side of the road at the bottom of the picture.", + "Step 4: The roof and walls of Bounding Box -[<771><292><850><344>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<771><292><850><344>] is no-damaged.", + "Step 6: Bounding Box -[<771><292><850><344>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<771><292><850><344>]", + "(B) Bounding Box -[<701><536><743><592>]", + "(C) Bounding Box -[<358><852><436><909>]", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000016_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0022", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom left corner of the picture.It is located below the largest building in the bottom left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 35undamaged buildings,3 destroyed buildings,10 minor-damage and 5 major damagedbuildings.", + "Step 2: There are four buildings located at the bottom left corner of theintersection in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<183><935><200><945>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<183><935><200><945>] are intact with cracks, tiltingor damage.", + "Step 5: Bounding Box -[<183><935><200><945>] is major damaged.", + "Step 6: Bounding Box -[<183><935><200><945>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<131><879><181><918>]", + "(B) Bounding Box -[<183><935><200><945>]", + "(C) Bounding Box -[<219><942><236><957>]", + "(D) Bounding Box -[<58><876><124><905>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000035_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0023", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is major damaged. It is located in the middle of thebottom of the picture. It is the leftmost of the five buildings at the lowerright corner of the crossroads.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings, 8 minor damaged buildings, 4 major damaged buildings and2 fully destroyed buildings.", + "Step 2: There are some buildings located in the middle of the lower part ofthe picture.", + "Step 3: Bounding Box -[<384><975><430><1024>] is the leftmost of the five buildings at the lowerright corner of the crossroads.", + "Step 4: Bounding Box -[<384><975><430><1024>] has severe structural collapse, extensive wallbreaches, and partial roof failure.", + "Step 5: Bounding Box -[<384><975><430><1024>] is Major damaged.", + "Step 6: Bounding Box -[<384><975><430><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<579><731><662><794>]", + "(B) Bounding Box -[<384><975><430><1024>]", + "(C) Bounding Box -[<557><874><604><912>]", + "(D) Bounding Box -[<694><974><728><1024>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000044_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0024", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is minor damaged building.The building is located in the upper right corner of the picture. It is located on the right side of theroad and is trapezoidal. There are three similar buildings beneath it.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged building and 7 minor damaged buildings.", + "Step 2: There are some buildings in the upper right corner of the picture.", + "Step 3: Bounding Box -[<999><167><1024><208>] is located on the right side of the road, and thereare three similar buildings beneath it.", + "Step 4: Bounding Box -[<999><167><1024><208>] has slight structural cracks and partial exteriorwear, but remains mostly intact.", + "Step 5: Bounding Box -[<999><167><1024><208>] is minor damaged.", + "Step 6: Bounding Box -[<999><167><1024><208>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<709><173><795><220>]", + "(B) Bounding Box -[<532><184><629><223>]", + "(C) Bounding Box -[<999><167><1024><208>]", + "(D) Bounding Box -[<719><288><787><326>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000130_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0025", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is undamaged. It is located in the bottom rightcorner of the picture. It is located below the largest building below the arcjunction.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 69undamaged buildings, 1 unclassified building, 11 slightly damaged buildings,and 1 severely damaged building.", + "Step 2: There are 10 buildings under the curved road in the lower rightcorner of the picture.", + "Step 3: Bounding box -[<865><805><946><929>] is a building that sits below the largest buildingbelow the arc junction.", + "Step 4: The roof and walls of Bounding Box -[<865><805><946><929>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<865><805><946><929>] is no-damaged.", + "Step 6: Bounding Box -[<865><805><946><929>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<865><805><946><929>]", + "(B) Bounding Box -[<355><642><396><704>]", + "(C) Bounding Box -[<3><379><60><435>]", + "(D) Bounding Box -[<149><508><200><585>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000147_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0026", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located on the upperright of the picture. It is located on top of the largest building in theupper right corner of the image", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 2: There are four buildings located at the upper right corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<168><1010><221><1024>] is a on top of the rectangular building with thelargest area in the upper right corner of the graph.", + "Step 4: The roof and walls of Bounding Box -[<168><1010><221><1024>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<168><1010><221><1024>] is no-damaged.", + "Step 6: Bounding Box -[<168><1010><221><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<168><1010><221><1024>]", + "(B) Bounding Box -[<189><813><223><856>]", + "(C) Bounding Box -[<275><804><400><887>]", + "(D) Bounding Box -[<272><416><305><487>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000418_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0027", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is major-damaged building.a top left of the entirepicture It is located below the largest building in the upper left corner ofthe intersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><273><26><319>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<0><273><26><319>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<0><273><26><319>] is major-damaged.", + "Step 6: Bounding Box -[<0><273><26><319>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><273><26><319>]", + "(B) Bounding Box -[<316><177><358><225>]", + "(C) Bounding Box -[<200><122><247><167>]", + "(D) Bounding Box -[<266><356><316><403>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000502_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0028", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomof the picture.It is in the middle and lower part of the picture.To the rightof it is a rectangular building close to each other.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings ,2 minor-damaged buildings and 1 unclassified buildings.", + "Step 2: The building is located in the lower middle part of the graph.", + "Step 3: Above Bounding Box -[<667><974><690><994>], there is a square building and a rectangularbuilding on the right.", + "Step 4: The roof and walls of Bounding Box -[<667><974><690><994>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<667><974><690><994>] is no-damaged.", + "Step 6: Bounding Box -[<667><974><690><994>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<667><974><690><994>]", + "(B) Bounding Box -[<676><926><699><953>]", + "(C) Bounding Box -[<662><850><704><865>]", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000365_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0029", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located in the bottomleft of the picture.It is located on the left side of the river in the lowerleft corner and is the smallest building in the area.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><909><14><947>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<0><909><14><947>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<0><909><14><947>] is no-damaged.", + "Step 6: Bounding Box -[<0><909><14><947>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><909><14><947>]", + "(B) Bounding Box -[<18><790><68><846>]", + "(C) Bounding Box -[<154><792><209><849>]", + "(D) Bounding Box -[<373><822><419><869>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000003_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0030", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building.It is located in the bottom right corner of the picture. There are nobuildings on its right and below, located diagonally on the right side of thegraphic.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20minor-damaged buildings ，67 no-damaged buildings,.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<971><990><1022><1024>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<971><990><1022><1024>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<971><990><1022><1024>] is no-damaged.", + "Step 6: Bounding Box -[<971><990><1022><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<971><990><1022><1024>]", + "(B) Bounding Box -[<925><884><976><937>]", + "(C) Bounding Box -[<816><860><861><913>]", + "(D) Bounding Box -[<809><757><843><798>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000072_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0031", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 59undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<200><135><232><180>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<200><135><232><180>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<200><135><232><180>] is no-damaged.", + "Step 6: Bounding Box -[<200><135><232><180>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<200><135><232><180>]", + "(B) Bounding Box -[<159><45><209><81>]", + "(C) Bounding Box -[<142><135><179><148>]", + "(D) Bounding Box -[<30><80><93><116>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000152_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0032", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is undamaged. It is located in the lower left corner of the picture. It is located in the smaller building surrounded by thelargest one beneath the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 21undamaged buildings, 2 major-damage buildings and 2 minor-damage buildings.", + "Step 2: There are some buildings in the lower left corner of the road in thepicture.", + "Step 3:Bounding Box -[<353><659><413><683>]No. is the smaller building within the enclosure of thelargest building located beneath the road.", + "Step 4: The roof and walls of Bounding Box -[<353><659><413><683>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<353><659><413><683>] is no-damaged.", + "Step 6: Bounding Box -[<353><659><413><683>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<353><659><413><683>]", + "(B) Bounding Box -[<773><77><845><151>]", + "(C) Bounding Box -[<911><139><987><217>]", + "(D) Bounding Box -[<767><521><825><587>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000183_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0033", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building,The building is located in the lower left corner of the picture, in the middle of an intersection on theleft, and there is no building below it.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 50undamaged buildings,23 minor damaged buildings ,7 major damaged buildings ,6fully destroyed buildings and 2 unclassified buildings.", + "Step 2: There are three buildings located at the bottom left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<65><999><90><1020>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<65><999><90><1020>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<65><999><90><1020>] is no-damaged.", + "Step 6: Bounding Box -[<65><999><90><1020>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<65><999><90><1020>]", + "(B) Bounding Box -[<158><926><184><951>]", + "(C) Bounding Box -[<308><707><335><747>]", + "(D) Bounding Box -[<405><638><430><679>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000253_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0034", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located in the middleof the picture. It is located at the lower left corner of the T-shapedintersection and is the largest L-shaped building in area.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 65undamaged buildings, 42 minor damaged buildings and 6 major damagedbuildings.", + "Step 2: There are some buildings located in the center of the picture.", + "Step 3: Bounding Box -[<463><385><700><466>] is a building located at the lower left corner of theT-shaped intersection, which is the largest L-shaped building in area.", + "Step 4: The roof and walls of Bounding Box -[<463><385><700><466>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<463><385><700><466>] is no-damaged.", + "Step 6: Bounding Box -[<463><385><700><466>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<406><835><630><859>]", + "(B) Bounding Box -[<336><395><369><528>]", + "(C) Bounding Box -[<313><808><346><832>]", + "(D) Bounding Box -[<463><385><700><466>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000181_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0035", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The walls and roof of this building were completely destroyed. Itis located in the bottom right corner of the picture. There are no otherbuildings around.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 4minor-damaged buildings and 1 unclassified buildings and 5 destroyedbuildings.", + "Step 2: There are is a buildinge located in the bottom right corner of theimage.", + "Step 3: Bounding Box -[<953><626><966><652>] has a gray white rectangular roof.", + "Step 4: The roof and walls of Bounding Box -[<953><626><966><652>] were completely destroyed.", + "Step 5: Bounding Box -[<953><626><966><652>] is no-damaged.", + "Step 6: Bounding Box -[<953><626><966><652>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<953><626><966><652>]", + "(B) Bounding Box -[<825><688><852><730>]", + "(C) Bounding Box -[<920><707><954><758>]", + "(D) Bounding Box -[<857><800><926><862>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000190_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0036", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are obvious cracks on the walls and roof of this building.It is located in the upper left corner of the picture. It is located belowthe road. It is the largest green trapezoid.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 8major-damaged buildings and 1 unclassified buildings and 10 destroyedbuildings and 4 minor-damage buildings.", + "Step 2: there are some buildings located in the bottom left corner of thepicture.", + "Step 3: Bounding Box -[<0><402><29><466>] is the trapezoidal building with the largest greenroof.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<0><402><29><466>].", + "Step 5: Bounding Box -[<0><402><29><466>] is major-damaged.", + "Step 6: Bounding Box -[<0><402><29><466>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><402><29><466>]", + "(B) Bounding Box -[<246><258><298><309>]", + "(C) Bounding Box -[<395><316><431><407>]", + "(D) Bounding Box -[<528><496><560><595>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000221_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0037", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: There are slight cracks on the walls and roof of this building.It is located in the bottom right corner of the picture. It is located at theintersection and is the largest rectangular building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 10undamaged buildings and 9 unclassified buildings and 67 minor-damge buildingsand 12 major-damage buildings and 3 destryed buildings.", + "Step 2: There are some buildings located in the bottom right corner of theimage.", + "Step 3: Bounding Box -[<641><867><753><959>] is the largest rectangular building located at theintersection.", + "Step 4: There are slight cracks on the walls and roof of Bounding Box -[<641><867><753><959>].", + "Step 5: Bounding Box -[<641><867><753><959>] is minor-damaged.", + "Step 6: Bounding Box -[<641><867><753><959>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<641><867><753><959>]", + "(B) Bounding Box 9", + "(C) Bounding Box 10", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000278_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0038", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are slight cracks on the roof and walls of this building. Itis located in the bottom right corner of the picture. It is the largestL-shaped white roofed building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 43undamaged buildings and 1 unclassified buildings and10 minor-damagebuildings.", + "Step 2: There are some buildings located in the upper left corner of theimage.", + "Step 3: Bounding Box -[<609><960><684><1024>] is the largest L-shaped white roofed building.", + "Step 4: There are slight cracks on the roof and walls of Bounding Box -[<609><960><684><1024>].", + "Step 5: Bounding Box -[<609><960><684><1024>] is minor-damaged.", + "Step 6: Bounding Box -[<609><960><684><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<609><960><684><1024>]", + "(B) Bounding Box -[<834><742><887><789>]", + "(C) Bounding Box -[<919><846><947><903>]", + "(D) Bounding Box -[<874><962><924><1002>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000000_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0039", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is undamaged. It is located in the upper rightcorner of the picture, with a parking lot on its left and a white roofedbuilding similar to it on its right.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 77undamaged buildings and 1 unclassified buildings and 4 major-damage buildingsand 18 minor-damage buidlings and 2 destroyed buildings.", + "Step 2: There are some buildings located at the upper right corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<774><910><794><927>] is located on the right side of the parking lot, thereis a rectangular white roof with a similar building on its right side.", + "Step 4: The roof and walls of Bounding Box -[<774><910><794><927>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<774><910><794><927>] is no-damaged.", + "Step 6: Bounding Box -[<774><910><794><927>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<774><910><794><927>]", + "(B) Bounding Box -[<699><948><716><962>]", + "(C) Bounding Box -[<579><923><595><935>]", + "(D) Bounding Box -[<29><832><58><885>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0040", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are obvious cracks on the walls and roof of this building.It is located in the upper right corner of the picture, on the right side ofthe parking lot and the left side of the highway. It has a rectangular whiteroof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 12undamaged buildings and 1 unclassified buildings and 4 major-damage buildingsand 18 minor-damage buildings and 1 destroyed buildings.", + "Step 2: There are some buildings located at the upper right corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<707><13><832><68>] is the largest rectangular white roofed building islocated on the left side of the parking lot.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<707><13><832><68>].", + "Step 5: Bounding Box -[<707><13><832><68>] is major-damaged.", + "Step 6: Bounding Box -[<707><13><832><68>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<707><13><832><68>]", + "(B) Bounding Box -[<350><189><430><247>]", + "(C) Bounding Box -[<482><289><546><409>]", + "(D) Bounding Box -[<596><481><678><553>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000034_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0041", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are obvious cracks on the walls and roof of this building.It is located in the upper left corner of the picture, with a reddish brownsquare roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 44undamaged buildings and 9 minor-damage buildings and 4 major-damage buildings.", + "Step 2: There are some buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><112><56><169>] the largest square building with a reddish brown roof.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<0><112><56><169>].", + "Step 5: Bounding Box -[<0><112><56><169>] is major-damaged.", + "Step 6: Bounding Box -[<0><112><56><169>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><112><56><169>]", + "(B) Bounding Box -[<413><530><519><660>]", + "(C) Bounding Box -[<629><660><723><737>]", + "(D) Bounding Box -[<819><817><923><887>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000056_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0042", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is undamaged. It is located in the upper rightcorner of the picture. It is located on a green open space between twointersections and is the largest rectangular white roofed building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 54undamaged buildings and 14 minor-damage buildings and 6 major-damage buildingsand 1 destroyed buildings.", + "Step 2: There is a building located at the upper right corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<814><190><942><330>] is the largest rectangular white roofed buildinglocated on a green open space between two intersections.", + "Step 4: The roof and walls of Bounding Box -[<814><190><942><330>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<814><190><942><330>] is no-damaged.", + "Step 6: Bounding Box -[<814><190><942><330>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<814><190><942><330>]", + "(B) Bounding Box -[<794><490><894><601>]", + "(C) Bounding Box -[<669><326><756><395>]", + "(D) Bounding Box -[<681><115><742><178>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000142_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0043", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: There are obvious cracks on the walls and roof of this building.It is located in the bottom left corner of the picture. It is the largestrectangular building with a gray roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 70undamaged buildings and 10 major-damage buildings and 22 minor-damagebuildings.", + "Step 2: There are some buildings located in the bottom left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><881><231><1019>] is the largest rectangular gray roof building islocated on the left side of the highway.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<0><881><231><1019>].", + "Step 5: Bounding Box -[<0><881><231><1019>] is major-damaged.", + "Step 6: Bounding Box -[<0><881><231><1019>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><881><231><1019>]", + "(B) Bounding Box -[<388><846><506><959>]", + "(C) Bounding Box -[<603><781><668><821>]", + "(D) Bounding Box -[<796><694><853><756>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000146_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0044", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are obvious cracks on the walls and roof of this building.It is located in the bottom right corner of the picture. It is the largestrectangular building with a gray roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 11undamaged buildings and 1 unclassified buildings and 23 destroyed buildingsand 21 minor-damage buildings and 10 major-damage buildings.", + "Step 2: There are some buildings located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<617><871><765><980>] is the largest rectangular building with a gray roofis located on the left side of the highway on the right.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<617><871><765><980>].", + "Step 5: Bounding Box -[<617><871><765><980>] is major-damaged.", + "Step 6: Bounding Box -[<617><871><765><980>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<617><871><765><980>]", + "(B) Bounding Box -[<368><700><457><790>]", + "(C) Bounding Box -[<522><656><607><740>]", + "(D) Bounding Box -[<663><670><715><756>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000165_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0045", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is undamaged. It is located in the bottom rightcorner of the picture, in the bottom left corner of the intersection, and isthe largest rectangular building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 66undamaged buildings and 5 major-damage buildings and 69 minor-damagebuildings and 4 destroyed buildings.", + "Step 2: There are some buidings located in the bottom right corner of theimage.", + "Step 3: Bounding Box -[<558><598><781><682>] is the largest rectangular building in the bottom left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<558><598><781><682>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<558><598><781><682>] is no-damaged.", + "Step 6: Bounding Box -[<558><598><781><682>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<558><598><781><682>]", + "(B) Bounding Box -[<443><501><485><577>]", + "(C) Bounding Box -[<617><528><671><555>]", + "(D) Bounding Box -[<755><564><805><585>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000266_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0046", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located in the topright corner of the picture, with narrow paths on the left and bottom, and isthe longest rectangular shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings and 3 major damaged buildings and 4 minor damagedbuildings and 2 unclassified buildings.", + "Step 2: There are building in the upper right corner of the picture.", + "Step 3: Bounding Box -[<963><445><982><483>] is a building in the top right corner of the picture,with narrow paths and the longest rectangular shape on the left and bottom.", + "Step 4: The roof and walls of Bounding Box -[<963><445><982><483>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<963><445><982><483>] is no-damaged.", + "Step 6: Bounding Box -[<963><445><982><483>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<963><445><982><483>]", + "(B) Bounding Box -[<782><324><876><414>]", + "(C) Bounding Box -[<536><382><604><451>]", + "(D) Bounding Box -[<901><79><1024><138>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000261_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0047", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is minor damaged building. The building is locatedin the middle of the picture near the narrow road and has a T-shaped shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged buildings and 7 major damaged buildings and 14 minor damagedbuildingsand 4 destroyed buildings.", + "Step 2: There are buildings near the narrow road in the middle of thepicture.", + "Step 3: Bounding Box -[<352><514><410><556>] is located in the middle of the figure near the narrowroad and has a T-shaped shape.", + "Step 4: The roof and walls of Bounding Box -[<352><514><410><556>] are intact slight cracks.", + "Step 5: Bounding Box -[<352><514><410><556>] is Minor damaged.", + "Step 6: Bounding Box -[<352><514><410><556>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<352><514><410><556>]", + "(B) Bounding Box -[<218><534><247><571>]", + "(C) Bounding Box -[<543><658><605><694>]", + "(D) Bounding Box -[<693><754><737><801>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000200_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0048", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is damaged building.The building is located in thelower left corner of the picture on the right side of the river and presents atriangular shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 14major damaged buildings and 2 minor damaged buildings and 108 destroyedbuildings.", + "Step 2: There are building located in the lower left corner of the picture onthe right side of the river.", + "Step 3: Bounding Box -[<89><1003><116><1024>] is located in the lower left corner of the picture onthe right side of the river and presents a triangular shape.", + "Step 4: Bounding Box -[<89><1003><116><1024>] has completely collapsed, leaving only a few ruins onthe walls.", + "Step 5: Bounding Box -[<89><1003><116><1024>] is Fully destroyed.", + "Step 6: Bounding Box -[<89><1003><116><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<89><1003><116><1024>]", + "(B) Bounding Box -[<122><919><161><949>]", + "(C) Bounding Box -[<217><817><248><844>]", + "(D) Bounding Box -[<62><854><83><876>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000385_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0049", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is major damaged building.The building is located in the upper left corner of the diagram and presents the largest n-type shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 33minor damaged buildings and 10 major damaged buildings and 54 undamagedbuildings and 2 destroyed buildings.", + "Step 2: There are building in the upper left corner of the picture.", + "Step 3: Bounding Box -[<2><87><55><172>] is a building in the upper left corner of the pictureand it presents the largest n-type shape.", + "Step 4: The roof and walls of Bounding Box -[<2><87><55><172>] are obvious cracks.", + "Step 5: Bounding Box -[<2><87><55><172>] is major damaged.", + "Step 6: Bounding Box -[<2><87><55><172>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<2><87><55><172>]", + "(B) Bounding Box -[<710><538><810><615>]", + "(C) Bounding Box -[<373><651><440><711>]", + "(D) Bounding Box -[<383><728><427><767>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000051_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0050", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is located to the right in the middle of thepicture, close to a road, and presents an L-shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 37undamaged buildings and 15 minor damage buildings and 2 destroyed buildingsand 2 unclassified buildings.", + "Step 2: There are building in the middle right of the picture.", + "Step 3: Bounding Box -[<824><507><849><537>] is a building on the right side of the middle in thepicture, and the building is L-shaped near the path on the right.", + "Step 4: The roof and walls of Bounding Box -[<824><507><849><537>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<824><507><849><537>] is no-damaged.", + "Step 6: Bounding Box -[<824><507><849><537>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<824><507><849><537>]", + "(B) Bounding Box -[<717><460><743><485>]", + "(C) Bounding Box -[<656><400><674><431>]", + "(D) Bounding Box -[<547><555><595><588>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000335_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0051", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building Major damaged building.is located in the lower rightcorner of the picture near the road and presents a T-shaped shape.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 2undamaged buildings and 4 minor damaged buildings and 6 major damagedbuildings and 1 destroyed building.", + "Step 2: There are building in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<750><866><837><927>] is located in the lower left corner of the picturenear the road and presents a T-shaped shape.", + "Step 4: The roof and walls of Bounding Box -[<750><866><837><927>] are obvious cracks.", + "Step 5: Bounding Box -[<750><866><837><927>] is Major damaged.", + "Step 6: Bounding Box -[<750><866><837><927>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<750><866><837><927>]", + "(B) Bounding Box -[<137><635><171><689>]", + "(C) Bounding Box -[<793><959><843><1007>]", + "(D) Bounding Box -[<747><257><839><315>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000124_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0052", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building in the middle of the diagram is the rightmost andsmallest square.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 6 majordamaged buildings and 8 minor damaged buildings and 17 destroyed buildings and2 unclassified buildings.", + "Step 2: There are building on the far right in the picture.", + "Step 3: Bounding Box -[<970><557><984><574>] is the rightmost and smallest square in the middle ofthe picture.", + "Step 4: The roof and walls of Bounding Box -[<970><557><984><574>] are slight cracks.", + "Step 5: Bounding Box -[<970><557><984><574>] is Minor damaged.", + "Step 6: Bounding Box -[<970><557><984><574>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<970><557><984><574>]", + "(B) Bounding Box -[<830><538><854><561>]", + "(C) Bounding Box -[<678><428><710><463>]", + "(D) Bounding Box -[<859><413><891><445>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000231_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0053", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is located in the lower left part of the picture andis farthest from the narrowest road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 34 no-damaged buildings and 14 major-damaged buildings.", + "Step 2: There are some buildings in the lower left part of the picture.", + "Step 3: In the lower left part of the picture, there is a building that isfarthest from the narrowest path.", + "Step 4: The roof and walls of Bounding Box -[<111><596><129><624>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<111><596><129><624>] is No-damaged.", + "Step 6: Bounding Box -[<111><596><129><624>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<172><595><193><617>]", + "(B) Bounding Box -[<518><0><618><26>]", + "(C) Bounding Box -[<937><182><995><242>]", + "(D) Bounding Box -[<111><596><129><624>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000338_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0054", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: From the perspective of the first building in the order of leftto right above the circular road on the left island, where is the building atthe bottom of the rightmost path.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 9 no-damaged buildings and 1 major damaged building and 132 minor damagedbuildings.", + "Step 2: There is a building on the island in the top left corner of thepicture.", + "Step 3: There is a building on the island in the top left corner of thepicture, and the shape of the building is M-shaped.", + "Step 4: The roof and upright walls without any gaps.", + "Step 5: Bounding Box -[<26><298><139><379>] is no-damaged.", + "Step 6: Bounding Box -[<26><298><139><379>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<153><693><226><787>]", + "(B) Bounding Box -[<301><565><369><658>]", + "(C) Bounding Box -[<296><706><350><778>]", + "(D) Bounding Box -[<26><298><139><379>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000433_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0055", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 257undamaged buildings and.", + "Step 2: There are buildings under the road in the picture.", + "Step 3: Bounding Box -[<559><635><640><683>] is located under the road with three small paths, andthe closest one to the third path presents a trapezoidal shape.", + "Step 4: The building has a complete roof and upright walls without anygaps.", + "Step 5: Bounding Box -[<559><635><640><683>] is no-damaged.", + "Step 6: Bounding Box -[<559><635><640><683>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<606><579><628><619>]", + "(B) Bounding Box -[<559><635><640><683>]", + "(C) Bounding Box 10", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000452_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0056", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 114major damaged buildings and 60 minor damaged buildings and 2 unclassifiedbuildings and 1 destroyed building.", + "Step 2: There are building in the top right corner of the picture.", + "Step 3: Bounding Box -[<996><242><1024><280>] is located in the upper right corner and has atrapezoidal shape.", + "Step 4: The roof and walls of Bounding Box -[<996><242><1024><280>] are obvious cracks.", + "Step 5: Bounding Box -[<996><242><1024><280>] is Major damaged.", + "Step 6: Bounding Box -[<996><242><1024><280>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<996><242><1024><280>]", + "(B) Bounding Box -[<573><282><623><314>]", + "(C) Bounding Box -[<379><28><443><115>]", + "(D) Bounding Box -[<637><257><685><323>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000491_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0057", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is undamaged. It is located in the center of thepicture. It is located in the upper left corner of the intersection and has arectangular red roof.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 2: There is a building located in the center of the image.", + "Step 3: Bounding Box -[<444><209><594><361>] has a rectangular building with a red roof.", + "Step 4: The roof and walls of Bounding Box -[<444><209><594><361>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<444><209><594><361>] is no-damaged.", + "Step 6: Bounding Box -[<444><209><594><361>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<444><209><594><361>]", + "(B) Bounding Box -[<722><307><808><411>]", + "(C) Bounding Box -[<748><511><810><613>]", + "(D) Bounding Box -[<484><469><614><531>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000469_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0058", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is undamaged. It is located in the bottom rightcorner of the picture. It is the largest rectangular white roofed building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 2undamaged buildings and 1 unclassified buildings and 33 minor-damagebuildings.", + "Step 2: There are 2 buildings located in the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<788><360><922><725>] is the largest rectangular white roofed building.", + "Step 4: The roof and walls of Bounding Box -[<788><360><922><725>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<788><360><922><725>] is no-damaged.", + "Step 6: Bounding Box -[<788><360><922><725>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<788><360><922><725>]", + "(B) Bounding Box -[<569><511><649><587>]", + "(C) Bounding Box -[<695><743><751><847>]", + "(D) Bounding Box -[<875><787><933><879>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000478_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0059", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The walls and roof of this building have slight cracks. It islocated in the center of the picture. It is the largest L-shaped white roofedbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 86undamaged buildings and 18 major-damage buildings and 6minor-damagebuildings.", + "Step 2: There are some buildings located in the center of the picture.", + "Step 3: Bounding Box -[<427><316><685><566>] is the largest L-shaped white roofed building.", + "Step 4: The roof and walls of Bounding Box -[<427><316><685><566>] have slight cracks.", + "Step 5: Bounding Box -[<427><316><685><566>] is minor-damaged.", + "Step 6: Bounding Box -[<427><316><685><566>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<427><316><685><566>]", + "(B) Bounding Box -[<767><308><815><400>]", + "(C) Bounding Box -[<851><100><907><180>]", + "(D) Bounding Box -[<807><258><847><302>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000492_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0060", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is undamaged. It is located in the upper left cornerof the picture. There is an identical building on its left and a road on itsright.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 35undamaged buildings.", + "Step 2: There are some buildings located in the upper left corner of thepicture.", + "Step 3: Bounding Box -[<100><0><216><143>] is the longest rectangular grey roof building. Thereis an identical building on the left and a road on the right.", + "Step 4: The roof and walls of Bounding Box -[<100><0><216><143>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<100><0><216><143>] is no-damaged.", + "Step 6: Bounding Box -[<100><0><216><143>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<100><0><216><143>]", + "(B) Bounding Box -[<287><166><307><214>]", + "(C) Bounding Box -[<331><236><389><291>]", + "(D) Bounding Box -[<462><314><566><381>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000514_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0061", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building.It is located in the bottomleft corner of the picture. It is the largest building with a purple red roofin the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 93undamaged buildings.", + "Step 2: There are some buildings in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<396><754><579><943>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<396><754><579><943>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<396><754><579><943>] is no-damaged.", + "Step 6: Bounding Box -[<396><754><579><943>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<396><754><579><943>]", + "(B) Bounding Box -[<185><374><274><469>]", + "(C) Bounding Box -[<457><251><559><342>]", + "(D) Bounding Box -[<602><421><654><511>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000397_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0062", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is major-damaged building.It is located in thebottom right corner of the picture. It is on the left side of the secondlargest building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 29destroyed buildings and 7 major damaged buildings.", + "Step 2: There is a building located directly below the picture.", + "Step 3: Bounding Box -[<481><848><508><904>] is the building has a white roof on the left side ofthe second largest building.", + "Step 4: The roof and walls of Bounding Box -[<481><848><508><904>] has a severely damaged door andwindow,and a hole has been opened in the roof.", + "Step 5: Bounding Box -[<481><848><508><904>] is -damaged.", + "Step 6: Bounding Box -[<481><848><508><904>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<481><848><508><904>]", + "(B) Bounding Box -[<613><737><629><771>]", + "(C) Bounding Box -[<717><733><746><765>]", + "(D) Bounding Box -[<267><543><339><567>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000493_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0063", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building.The building is no-damagedbuilding. It is located in the upper right corner of the picture.It is locatedin the upper right corner of the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 40undamaged buildings 、4 unclassified buildings、31 minor damaged buildings、4major damaged buildings and 1 destroyed buildings.", + "Step 2: There are some buildings located in the upper right corner of thepicture.", + "Step 3: Bounding Box -[<819><55><848><85>] is the building which located in front of a road andthere are no buildings in front of it. To its right, there is a smallerrectangular shaped building.", + "Step 4: The roof and walls of Bounding Box -[<819><55><848><85>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<819><55><848><85>] is no-damaged.", + "Step 6: Bounding Box -[<819><55><848><85>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<819><55><848><85>]", + "(B) Bounding Box -[<555><185><587><225>]", + "(C) Bounding Box -[<976><51><1011><72>]", + "(D) Bounding Box -[<967><128><1001><163>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000129_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0064", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located in the bottomleft corner of the picture, at the far left of the largest N-shapedbuilding.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 23undamaged buildings、3 major damaged buildings、6 minor damaged buildings and 2unclassified buildings.", + "Step 2: There are some buildings located in the bottom left corner of thepicture.", + "Step 3: Bounding Box -[<66><773><102><834>] is the building which located at the bottom left ofthe largest rectangular shaped building and to the left of the largestN-shaped building.", + "Step 4: The roof and walls of Bounding Box -[<66><773><102><834>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<66><773><102><834>] is no-damaged.", + "Step 6: Bounding Box -[<66><773><102><834>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<66><773><102><834>]", + "(B) Bounding Box -[<34><860><49><875>]", + "(C) Bounding Box -[<29><941><63><973>]", + "(D) Bounding Box -[<3><974><32><1004>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000364_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0065", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<528><346><719><437>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<528><346><719><437>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<528><346><719><437>] is no-damaged.", + "Step 6: Bounding Box -[<528><346><719><437>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<528><346><719><437>]", + "(B) Bounding Box -[<864><200><910><234>]", + "(C) Bounding Box -[<485><177><546><240>]", + "(D) Bounding Box -[<858><165><889><190>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000008_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0066", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<683><457><735><500>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<683><457><735><500>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<683><457><735><500>] is no-damaged.", + "Step 6: Bounding Box -[<683><457><735><500>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<683><457><735><500>]", + "(B) Bounding Box -[<872><373><921><413>]", + "(C) Bounding Box -[<738><307><755><324>]", + "(D) Bounding Box -[<957><365><987><395>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000058_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0067", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<402><576><470><681>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<402><576><470><681>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<402><576><470><681>] is no-damaged.", + "Step 6: Bounding Box -[<402><576><470><681>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<402><576><470><681>]", + "(B) Bounding Box -[<352><595><388><623>]", + "(C) Bounding Box -[<521><606><564><676>]", + "(D) Bounding Box -[<540><550><584><579>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000202_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0068", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomleft of the picture.It is located in the bottom side of the intersection. Itis located in the right of largest building in the bottom left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 44undamaged buildings,12 major damaged buildings,4 destroyed buildings,22 minordamaged buildings and 13 unclassified buildings.", + "Step 2: There are six buildings located at the bottom side of theintersection in the bottom side of the picture.", + "Step 3: Bounding Box -[<142><809><186><857>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<142><809><186><857>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<142><809><186><857>] is no-damaged.", + "Step 6: Bounding Box -[<142><809><186><857>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<76><809><137><879>]", + "(B) Bounding Box -[<142><809><186><857>]", + "(C) Bounding Box -[<151><660><168><689>]", + "(D) Bounding Box -[<101><667><126><690>]", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000184_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0069", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:There are slight cracks on the walls and roof of this building. Itis located in the bottom right corner of the picture. It is located below thehighway and is the largest building in the entire picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 35undamaged buildings and 18 major-damage buildings and 17 minor-damagebuildings.", + "Step 2: There are some buildings located in the bottom right corner of theimage.", + "Step 3: Bounding Box -[<852><865><1023><1023>] is the largest building is located beneath the highway.", + "Step 4: There are slight cracks on the walls and roof of Bounding Box -[<852><865><1023><1023>].", + "Step 5: Bounding Box -[<852><865><1023><1023>] is minor-damaged.", + "Step 6: Bounding Box -[<852><865><1023><1023>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<852><865><1023><1023>]", + "(B) Bounding Box 9", + "(C) Bounding Box 10", + "(D) Bounding Box 11", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000405_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0070", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. The building is located in the bottom left corner and closest to the left road in the diagram, and itsshape is rectangular.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 36undamaged buildings and 1 destroyed building and 11 minor damaged buildingsand 2 major damaged buidings.", + "Step 2: There are building in the bottom left corner of the picture.", + "Step 3: Bounding Box -[<267><977><341><1010>] is in the bottom left corner of the picture, there isa building located at the bottom left corner, close to the left side of theroad, and its shape is rectangular.", + "Step 4: The roof and walls of Bounding Box -[<267><977><341><1010>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<267><977><341><1010>] is no-damaged.", + "Step 6: Bounding Box -[<267><977><341><1010>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<267><977><341><1010>]", + "(B) Bounding Box -[<251><609><279><673>]", + "(C) Bounding Box -[<219><696><275><776>]", + "(D) Bounding Box -[<239><824><271><870>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000454_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0071", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building.It is located at the bottomright of the picture.It is located below the largest building in the upperleft corner of the intersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 185undamaged buildings.", + "Step 2: There are many buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<749><342><769><362>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<749><342><769><362>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<749><342><769><362>] is minor-damaged.", + "Step 6: Bounding Box -[<749><342><769><362>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<924><493><933><507>]", + "(B) Bounding Box -[<971><494><988><516>]", + "(C) Bounding Box -[<861><474><881><497>]", + "(D) Bounding Box -[<749><342><769><362>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000462_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0072", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The walls and roof of this building have obvious cracks. It islocated in the upper left corner of the picture. It is located above theintersection and is the largest white roofed building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 71undamaged buildings and 5 unclassified buildings and 12 minor-damage buildingsand 4 major buildings and 1 destroyed buildings.", + "Step 2: There are some buildings located in the upper left corner of thepicture .", + "Step 3: Bounding Box -[<269><6><536><143>] is the largest white roofed building located abovethe intersection.", + "Step 4: There are obvious cracks on the walls and roof of Bounding Box -[<269><6><536><143>].", + "Step 5: Bounding Box -[<269><6><536><143>] is major-damaged.", + "Step 6: Bounding Box -[<269><6><536><143>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<269><6><536><143>]", + "(B) Bounding Box -[<366><213><431><303>]", + "(C) Bounding Box -[<371><363><429><411>]", + "(D) Bounding Box -[<564><371><601><418>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000473_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0073", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located at the upperleft corner of the picture. It is a building situated on the left side of theadjacent main road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 127undamaged buildings.", + "Step 2: There are many buildings in the upper right corner of the picture.", + "Step 3: Bounding Box -[<29><832><58><885>] is located at the top left corner of the picture. Itis a building situated on the left side of the adjacent main road.", + "Step 4: The roof and walls of Bounding Box -[<29><832><58><885>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<29><832><58><885>] is minor-damaged.", + "Step 6: Bounding Box -[<29><832><58><885>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<774><910><794><927>]", + "(B) Bounding Box -[<699><948><716><962>]", + "(C) Bounding Box -[<579><923><595><935>]", + "(D) Bounding Box -[<29><832><58><885>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0074", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located in the upperright corner of the picture. It is located in the largest building in thepicture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 14undamaged buildings, 2 minor damaged buildings and 1 major damaged building.", + "Step 2: There are some buildings located in the upper right corner of thepicture.", + "Step 3: Bounding Box -[<497><118><705><425>] is the biggest building in the picture.", + "Step 4: The roof and walls of Bounding Box -[<497><118><705><425>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<497><118><705><425>] is No-damaged.", + "Step 6: Bounding Box -[<497><118><705><425>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<497><118><705><425>]", + "(B) Bounding Box -[<368><351><407><442>]", + "(C) Bounding Box -[<803><309><925><372>]", + "(D) Bounding Box -[<372><206><388><222>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000275_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0075", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. The building is located in the upper right corner of the picture. It is located in a parking lot. It isthe building with the largest area in the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 55undamaged buildings, 14 minor damaged buildings and 9 major damagedbuildings.", + "Step 2: There are some buildings located in the upper right corner of thepicture.", + "Step 3: Bounding Box -[<818><197><886><332>] is located in a parking lot and is the largestbuilding in the picture.", + "Step 4: The roof and walls of Bounding Box -[<818><197><886><332>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<818><197><886><332>] is no-damaged.", + "Step 6: Bounding Box -[<818><197><886><332>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<818><197><886><332>]", + "(B) Bounding Box -[<650><381><730><426>]", + "(C) Bounding Box -[<654><190><720><243>]", + "(D) Bounding Box -[<686><530><801><584>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000461_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0076", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located at the lowerpart of the center of the picture. It is beneath the largest building on theroad above.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 5undamaged buildings.", + "Step 2: There are many buildings located at the lower part of the center ofthe picture.", + "Step 3: Bounding Box -[<507><671><553><736>] is beneath the largest building on the upper road.", + "Step 4: The roof and walls of Bounding Box -[<507><671><553><736>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<507><671><553><736>] is minor-damaged.", + "Step 6: Bounding Box -[<507><671><553><736>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<687><661><706><677>]", + "(B) Bounding Box -[<670><702><700><723>]", + "(C) Bounding Box -[<719><746><758><769>]", + "(D) Bounding Box -[<507><671><553><736>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000265_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0077", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located at the centerof the picture. It is on the right side of the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 10undamaged buildings.", + "Step 2: There are many buildings located at the center of the picture.", + "Step 3: Bounding Box -[<325><498><385><532>] is an inverted-angled building located on the rightside of the road.", + "Step 4: The roof and walls of Bounding Box -[<325><498><385><532>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<325><498><385><532>] is minor-damaged.", + "Step 6: Bounding Box -[<325><498><385><532>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<287><865><313><878>]", + "(B) Bounding Box -[<340><840><370><858>]", + "(C) Bounding Box -[<302><885><331><901>]", + "(D) Bounding Box -[<325><498><385><532>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000204_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0078", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located in the lowerright corner of the picture. It is on the left side of the widest road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 43undamaged buildings.", + "Step 2: There are many buildings in the lower right corner of the picture.", + "Step 3: Bounding Box -[<774><927><799><959>] is a building located on the left side away from thewidest road.", + "Step 4: The roof and walls of Bounding Box -[<774><927><799><959>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<774><927><799><959>] is minor-damaged.", + "Step 6: Bounding Box -[<774><927><799><959>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<910><810><936><837>]", + "(B) Bounding Box -[<923><717><947><744>]", + "(C) Bounding Box -[<999><736><1014><763>]", + "(D) Bounding Box -[<774><927><799><959>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000167_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0079", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located at the bottomof the picture. It is situated in the lower left corner of the crossroads, onthe side close to the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 94undamaged buildings.", + "Step 2: There are many buildings located beneath the picture.", + "Step 3: Bounding Box -[<434><855><469><915>] is located at the lower left corner of thecrossroads, on the side close to the road.", + "Step 4: The roof and walls of Bounding Box -[<434><855><469><915>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<434><855><469><915>] is minor-damaged.", + "Step 6: Bounding Box -[<434><855><469><915>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<243><743><281><783>]", + "(B) Bounding Box -[<289><834><338><864>]", + "(C) Bounding Box -[<296><894><348><938>]", + "(D) Bounding Box -[<434><855><469><915>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000133_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0080", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located in the upperright corner of the picture. It is above the largest building on the rightside of the middle road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 16undamaged buildings.", + "Step 2: There are many buildings in the upper right corner of the picture.", + "Step 3: Bounding Box -[<817><191><953><251>] is a rectangular building located above the largestone on the right side of the middle road.", + "Step 4: The roof and walls of Bounding Box -[<817><191><953><251>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<817><191><953><251>] is minor-damaged.", + "Step 6: Bounding Box -[<817><191><953><251>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<647><454><704><491>]", + "(B) Bounding Box -[<686><553><729><590>]", + "(C) Bounding Box -[<861><541><885><567>]", + "(D) Bounding Box -[<817><191><953><251>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000039_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0081", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom-right corner is (x_max,y_max).Description:The building is a major damaged one. It is located at the bottomright corner of the picture. It is beneath the largest building at the bottomright corner of the road.", + "CoT": [ + "Step 1:Image is a photo taken after the disaster occurred. There are 42undamaged buildings.", + "Step 2:There are many buildings located at the bottom right corner of theentire picture.", + "Step 3:Bounding Box -[<977><876><999><902>]is the building located beneath the largest one atthe lower right corner of the road.", + "Step 4:The roof and walls of Bounding Box -[<977><876><999><902>]suffered severe damage,andthere are many cracks on the walls.", + "Step 5:Bounding Box -[<977><876><999><902>]is major-damaged.", + "Step 6:Bounding Box -[<977><876><999><902>]is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<846><869><863><886>]", + "(B) Bounding Box -[<818><923><846><931>]", + "(C) Bounding Box -[<895><891><901><911>]", + "(D) Bounding Box -[<977><876><999><902>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000373_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0082", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is a slightly damaged one. It is on the left side ofthe picture. It is above the smallest building on the right side of theroad.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 1undamaged buildings.", + "Step 2: There are many buildings are located on the left side of thepicture.", + "Step 3: Bounding Box -[<267><335><290><359>] is located above the smallest building which issituated on the right side of the winding road.", + "Step 4: The roof and walls of Bounding Box -[<267><335><290><359>] have suffered minor damages,and there are some cracks on the walls.", + "Step 5: Bounding Box -[<267><335><290><359>] is Minor-damaged.", + "Step 6: Bounding Box -[<267><335><290><359>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<341><302><353><315>]", + "(B) Bounding Box -[<394><318><430><341>]", + "(C) Bounding Box -[<482><296><528><328>]", + "(D) Bounding Box -[<267><335><290><359>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-matthew_00000289_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0083", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This building is a major-damaged one. It is located at the centerof the picture. It is the smallest building located beneath the road far awayfrom the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 17minor-damaged buildings.", + "Step 2: There are many buildings are located at the center of the picture.", + "Step 3: Bounding Box -[<306><577><342><611>] is the smallest building located beneath the roadthat is far away from the road.", + "Step 4: The roof and walls of Bounding Box -[<306><577><342><611>] are severely damaged. There arenumerous cracks on the walls.", + "Step 5: Bounding Box -[<306><577><342><611>] is major-damaged.", + "Step 6: Bounding Box -[<306><577><342><611>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<580><549><612><580>]", + "(B) Bounding Box -[<565><631><604><647>]", + "(C) Bounding Box -[<505><677><542><691>]", + "(D) Bounding Box -[<306><577><342><611>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000501_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0084", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is a slightly damaged one. It is located at the leftside of the picture. It is beneath the largest building on the left side ofthe road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 112undamaged buildings.", + "Step 2: There are many buildings are located on the left side of thepicture.", + "Step 3: Bounding Box -[<0><701><55><792>] is the building which is located beneath the largestbuilding on the left side of the road.", + "Step 4: The roof and walls of Bounding Box -[<0><701><55><792>] have suffered slight damages,and there are tiny cracks on the walls.", + "Step 5: Bounding Box -[<0><701><55><792>] is minor-damaged.", + "Step 6: Bounding Box -[<0><701><55><792>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<198><740><241><757>]", + "(B) Bounding Box -[<188><784><218><792>]", + "(C) Bounding Box -[<0><701><55><792>]", + "(D) Bounding Box -[<165><626><190><644>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000461_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0085", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the upperright of the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 89undamaged buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<822><34><857><53>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<822><34><857><53>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<822><34><857><53>] is no-damaged.", + "Step 6: Bounding Box -[<822><34><857><53>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<822><34><857><53>]", + "(B) Bounding Box -[<862><100><902><115>]", + "(C) Bounding Box -[<985><79><1024><151>]", + "(D) Bounding Box -[<873><178><940><194>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000430_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0086", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the upperright of the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 52undamaged buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<778><58><809><74>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<778><58><809><74>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<778><58><809><74>] is no-damaged.", + "Step 6: Bounding Box -[<778><58><809><74>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<778><58><809><74>]", + "(B) Bounding Box -[<868><81><885><97>]", + "(C) Bounding Box -[<968><0><1024><41>]", + "(D) Bounding Box -[<701><49><752><81>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000400_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0087", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 56undamaged buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<386><462><426><515>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<526><405><566><428>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<386><462><426><515>] is no-damaged.", + "Step 6: Bounding Box -[<386><462><426><515>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<526><405><566><428>]", + "(B) Bounding Box -[<621><432><675><459>]", + "(C) Bounding Box -[<386><462><426><515>]", + "(D) Bounding Box -[<512><447><566><471>]", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000389_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0088", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<611><214><650><236>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<611><214><650><236>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<611><214><650><236>] is no-damaged.", + "Step 6: Bounding Box -[<611><214><650><236>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<611><214><650><236>]", + "(B) Bounding Box -[<652><190><688><207>]", + "(C) Bounding Box -[<592><117><634><139>]", + "(D) Bounding Box -[<566><161><628><189>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000381_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0089", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<973><46><1006><73>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<973><46><1006><73>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<973><46><1006><73>] is no-damaged.", + "Step 6: Bounding Box -[<973><46><1006><73>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<973><46><1006><73>]", + "(B) Bounding Box -[<911><102><929><124>]", + "(C) Bounding Box -[<908><139><931><166>]", + "(D) Bounding Box -[<905><195><935><230>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000369_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0090", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomleft corner of the picture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 28undamaged buildings and 2 unclassified buildings.", + "Step 2: There are six buildings located at the bottom left corner of theentire image.", + "Step 3: Bounding Box -[<277><576><320><683>] is the building which located left the largestbuilding.", + "Step 4: The roof and walls of Bounding Box -[<113><613><153><634>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<277><576><320><683>] is no-damaged.", + "Step 6: Bounding Box -[<277><576><320><683>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<113><613><153><634>]", + "(B) Bounding Box -[<103><657><154><683>]", + "(C) Bounding Box -[<111><537><159><567>]", + "(D) Bounding Box -[<277><576><320><683>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000346_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0091", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of the picture.It is located below the largest building in the upper left corner of theintersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 11undamaged buildings and 3 unclassified buildings.", + "Step 2: There are six buildings located at the upper left corner of theintersection in the lower right corner of the picture.", + "Step 3: Bounding Box -[<0><947><242><1024>] is the building which located below the largestbuilding in the upper left corner of the intersection.", + "Step 4: The roof and walls of Bounding Box -[<0><947><242><1024>] are intact without cracks,tilting or damage.", + "Step 5: Bounding Box -[<0><947><242><1024>] is no-damaged.", + "Step 6: Bounding Box -[<0><947><242><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<0><947><242><1024>]", + "(B) Bounding Box -[<431><562><482><607>]", + "(C) Bounding Box -[<244><776><293><877>]", + "(D) Bounding Box -[<337><746><363><767>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000145_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0093", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is no-damaged building. It is located at the bottomright of the picture.It is located in the bottom right corner of thepicture.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 13undamaged buildings and 5 minjor-damage buildings.", + "Step 2: There is building a located in the bottom right corner of the entirepicture.", + "Step 3: Bounding Box -[<961><231><1024><410>] is located on the right side of the entire river, itis the largest building in the entire picture.", + "Step 4: Bounding Box -[<961><231><1024><410>] has no obvious cracks on the walls and roof.", + "Step 5: Bounding Box -[<961><231><1024><410>] is no-damaged.", + "Step 6: Bounding Box -[<961><231><1024><410>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<961><231><1024><410>]", + "(B) Bounding Box -[<960><70><1013><133>]", + "(C) Bounding Box -[<783><298><828><370>]", + "(D) Bounding Box -[<863><193><913><283>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-harvey_00000344_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0094", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:The building is a minor damaged one. It is located at the lowerpart of the center of the picture. It is situated at the bottom of the roadwhich is far away from the road.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 20undamaged buildings.", + "Step 2: There are many buildings located at the center of the picture.", + "Step 3: Bounding Box -[<29><832><58><885>] is the building located at the position below thecenter of the picture. It is situated beneath a road that is far away from theroad.", + "Step 4: The roof and walls of Bounding Box -[<29><832><58><885>] have suffered minor damages.There are some cracks on the walls.", + "Step 5: Bounding Box -[<29><832><58><885>] is minor-damaged.", + "Step 6: Bounding Box -[<29><832><58><885>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<774><910><794><927>]", + "(B) Bounding Box -[<699><948><716><962>]", + "(C) Bounding Box -[<579><923><595><935>]", + "(D) Bounding Box -[<29><832><58><885>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-florence_00000118_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0095", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: The building is minor-damage building. It is located at the upperright of the picture.It is located in the top side of the river.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 112undamaged buildings , 6 minor damaned buildings and 7 major damagedbuildings.", + "Step 2: There are dozens buildings located at the upper right corner of thepicture.", + "Step 3: There are four buildings above the river.", + "Step 4: The roof and walls of Bounding Box -[<29><832><58><885>] have a few cracks, but theoverall integrity of the building.", + "Step 5: Bounding Box -[<29><832><58><885>] is minor-damage.", + "Step 6: Bounding Box -[<29><832><58><885>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<774><910><794><927>]", + "(B) Bounding Box -[<699><948><716><962>]", + "(C) Bounding Box -[<579><923><595><935>]", + "(D) Bounding Box -[<29><832><58><885>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000509_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0096", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: ", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 141undamaged buildings 20 minor-damage buildings ,4 major-damage buildings and 1unclassified building.", + "Step 2: There are dozens buildings located at the upper right corner of thepicture.", + "Step 3: Bounding Box -[<774><910><794><927>] is the building with a H shape.", + "Step 4: The roof and walls of Bounding Box -[<774><910><794><927>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<774><910><794><927>] is major-damaged.", + "Step 6: Bounding Box -[<774><910><794><927>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<774><910><794><927>]", + "(B) Bounding Box -[<699><948><716><962>]", + "(C) Bounding Box -[<579><923><595><935>]", + "(D) Bounding Box -[<29><832><58><885>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000511_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0097", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This slightly damaged building is located on the left side of theU-shaped intersection in the middle of the picture, with one building aboveand one below it.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 134undamaged buildings ,4 minor-damage buildings.", + "Step 2: There are dozens buildings located at the middle corner of thepicture.", + "Step 3: Bounding Box -[<720><997><753><1024>] is the building which is located on the left side ofthe U-shaped intersection in the middle of the picture, with one buildingabove and one below it.", + "Step 4: The roof and walls of Bounding Box -[<720><997><753><1024>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<720><997><753><1024>] is minor-damaged.", + "Step 6: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000512_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0098", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This severely damaged building is located in the bottom rightcorner of the picture, on the left side of the bridge.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 28undamaged buildings 1 minor-damage buildings ,1 major-damage buildings.", + "Step 2: There are 6 buildings located at the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<720><997><753><1024>] is on the left side of the bridge.", + "Step 4: The roof and walls of Bounding Box -[<720><997><753><1024>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<720><997><753><1024>] is major-damaged.", + "Step 6: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000514_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0099", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This severely damaged building is located in the bottom rightcorner of the picture, directly above the lake.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 115undamaged buildings 29 minor-damage buildings ,15 major-damage buildings and 3destroyed buildings.", + "Step 2: There are 8 buildings located at the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<847><975><875><999>] is on the left side of the bridge.", + "Step 4: The roof and walls of Bounding Box -[<847><975><875><999>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<847><975><875><999>] is major-damaged.", + "Step 6: Bounding Box -[<847><975><875><999>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000515_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0100", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description: This severely damaged building is located at the bottom of thepicture, with a parking lot to the left of the building.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 65undamaged buildings,13 minor-damage buildings ,1 major-damage buildings and 3destroyed buildings.", + "Step 2: There are 12 buildings located at the bottom right corner of thepicture.", + "Step 3: There is a parking lot on the left side of Bounding Box -[<847><975><875><999>].", + "Step 4: The roof and walls of Bounding Box -[<847><975><875><999>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<847><975><875><999>] is major-damaged.", + "Step 6: Bounding Box -[<847><975><875><999>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000516_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0101", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This building is located in the lower right corner of the picture,with a forest on the right. This building is adjacent to the highway.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred.There are 158undamaged buildings,4 minor-damage buildings.", + "Step 2: There are 12 buildings located at the bottom right corner of thepicture.", + "Step 3: Bounding Box -[<720><997><753><1024>] is located below the road and to the left of theforest.", + "Step 4: The roof and walls of Bounding Box -[<720><997><753><1024>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<720><997><753><1024>] is major-damaged.", + "Step 6: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000517_post_disaster.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Visual grounding of damaged individual buildings/0102", + "Question_Type": "Grounding", + "Text": "Given a 1024 x 1024 pixels satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom-right corner is (x_max, y_max).Description:This severely damaged building is located in the upper left cornerof the picture and in the upper left corner of the intersection.", + "CoT": [ + "Step 1: Image is a photo taken after the disaster occurred. There are 130undamaged buildings,21 minor-damage buildings,9 major-damage buildings and 5destroyed buildings.", + "Step 2: There are 24 buildings located at the upper left corner of thepicture.", + "Step 3: Bounding Box -[<720><997><753><1024>] is located in the upper left corner of theintersection.", + "Step 4: The roof and walls of Bounding Box -[<720><997><753><1024>] are tilted with obviouscracks.", + "Step 5: Bounding Box -[<720><997><753><1024>] is major-damaged.", + "Step 6: Bounding Box -[<720><997><753><1024>] is the described building." + ], + "Dataset": "XView", + "L1-task": "Pedosphere", + "L2-task": "Surface Disaster Assessment", + "L3-task": "Reasoning", + "L4-task": "Visual grounding of damaged individual buildings", + "Answer Choices": [ + "(A) Bounding Box -[<720><997><753><1024>]", + "(B) Bounding Box -[<121><105><167><124>]", + "(C) Bounding Box -[<626><720><660><747>]", + "(D) Bounding Box -[<847><975><875><999>]", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/diaster/XView/hurricane-michael_00000519_post_disaster.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Perception/Fine-grained_object_type_recognition.json b/jsons/Pedosphere/Urban_Development/Perception/Fine-grained_object_type_recognition.json new file mode 100644 index 0000000000000000000000000000000000000000..ce9a58288863c463dab7cf643c66dfdf5ccd6441 --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Perception/Fine-grained_object_type_recognition.json @@ -0,0 +1,11310 @@ +[ + { + "Question_id": "Fine-grained object type recognition/0000", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x600. Bounding box: -[<382><54><491><162>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15700_18900_116.3457_39.8897_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0001", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<198><485><225><522>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_3100_11.5633_48.1726_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0002", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<117><112><265><173>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_16600_14400_116.3538_39.9222_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0003", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<246><178><307><245>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_21100_6700_116.3955_39.9779_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0004", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<71><263><167><323>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_15300_116.4297_39.9161_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0005", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<31><250><121><281>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_18900_116.4299_39.8901_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0006", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<61><184><141><289>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8500_12600_116.2779_39.9347_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0007 ", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<509><453><560><536>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_4500_116.3877_39.9942_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0008", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<57><116><94><212>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26100_18000_116.4430_39.8967_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0009", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<405><243><571><276>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26100_18400_116.4430_39.8938_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0010", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<3><538><64><579>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26500_14800_116.4465_39.9198_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0011", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<138><105><159><165>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27400_11700_116.4548_39.9421_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0012", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><271><72><307>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_10800_116.2930_39.9301_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0013", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<374><115><527><141>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28300_11700_116.4632_39.9422_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0014", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<105><25><153><95>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) arched_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_1300_116.3008_39.9730_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0015", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<202><525><293><543>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_2700_116.3009_39.9667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0016", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<419><335><514><366>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6300_19800_116.2578_39.8827_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0017", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<253><134><391><179>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_3100_116.3009_39.9649_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0018", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<477><510><495><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5400_116.3010_39.9545_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0019", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<153><421><284><458>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped-roof-v2 ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_5400_116.3033_39.9545_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0020", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<202><146><256><187>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10300_6700_116.4007_39.9843_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0021", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<15><105><90><159>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_900_116.3031_39.9748_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0022", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<157><161><252><245>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_12100_116.3066_39.9244_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0023", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<194><168><273><283>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_1300_116.4058_40.0087_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0024", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<140><527><292><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof-complex", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_12100_116.3118_39.9244_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0025", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<160><58><219><125>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_2200_116.4058_40.0046_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0026", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><295><152><331>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_10800_116.3141_39.9303_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0027", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<291><267><346><334>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_3600_116.4058_39.9983_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0028", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<263><535><314><550>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_11700_116.3141_39.9262_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0029", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<329><407><464><450>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_4000_116.4059_39.9965_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0030", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<125><425><166><523>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_9000_116.3140_39.9384_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0031", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<435><171><464><301>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_12100_116.4091_39.9601_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0032", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<154><143><244><201>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13900_11.5897_48.1866_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0033", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<18><142><88><228>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_12600_11.6052_48.1957_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0034", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<334><450><367><482>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_11700_11.6056_48.2021_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0035", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<489><524><521><576>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) hipped_roof_v2", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_12100_11.6054_48.1993_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0036", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<218><331><297><426>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_9000_116.4166_39.9741_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0037", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<191><62><394><396>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_10800_15700_11.5940_48.1153_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0038", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 6000.Bounding box: -[<357><112><516><136>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13500_10300_116.4196_39.9682_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0039", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<45><62><155><151>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_21100_11.5968_48.1347_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0040", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<23><258><157><295>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13900_9900_116.4219_39.9700_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0041", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<293><107><332><150>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_11700_11.6070_48.1330_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0042", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<252><354><293><391>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_12100_11.6096_48.1311_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0043", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<319><94><350><125>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_16600_11.6059_48.1109_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0044", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<87><79><205><159>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_4000_116.3531_39.9962_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0045", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<232><0><481><52>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_2700_11.5331_48.1751_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0046", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<156><256><203><291>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_4900_11.5326_48.1652_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0047", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<150><520><287><553>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3600_8500_116.3615_39.9760_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0048", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<154><308><184><337>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_16200_11.6086_48.1127_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0049", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<338><388><370><418>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof_v1", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_4500_11.5327_48.1670_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0050", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><337><76><379>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_9000_11.6136_48.1449_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0051", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<266><106><427><133>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_1800_116.3718_40.0063_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0052", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<192><335><236><367>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_9000_11.6163_48.1449_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0053", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<185><36><227><144>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_10800_116.3880_39.9658_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0054", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<384><463><485><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_7200_11.6201_48.1529_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0055", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<272><61><304><91>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_2700_11.5452_48.1748_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0056", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<202><63><275><95>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9400_4500_116.3953_39.9942_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0057", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<332><187><349><212>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_7600_11.6227_48.1510_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0058", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<493><270><570><335>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_13900_116.3353_39.9164_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0059", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><521><72><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_9400_11.6223_48.1430_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0060", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<118><260><150><283>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_3100_11.5451_48.1730_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0061", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<288><253><322><268>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_1800_11.5488_48.1788_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0062", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<493><472><538><517>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_2700_11.5425_48.1749_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0063", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<543><57><581><92>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_4900_11.5447_48.1649_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0064", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<60><559><85><585>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_2200_11.5487_48.1770_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0065", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<49><0><65><16>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_3100_11.5424_48.1731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0066", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<28><443><48><480>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_2200_11.5514_48.1769_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0067", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<243><0><339><79>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_6700_11.5504_48.1567_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0068", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<299><320><340><364>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_15300_11.5545_48.1179_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0069", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<328><333><385><385>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_11700_11.5553_48.1341_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0070", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<445><313><514><398>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_6700_11.6081_48.1554_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0071", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><100><21><143>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_5400_116.3297_39.9547_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0072", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<156><188><182><220>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_3100_11.5606_48.1727_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0073", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<348><203><372><263>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_31000_13000_11.6481_48.1918_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0074", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<152><273><271><308>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24700_13000_11.5804_48.1933_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0075", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<164><189><255><224>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_2700_116.3325_39.9669_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0076", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<345><177><435><240>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_1300_116.3324_39.9732_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0077", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<120><373><215><541>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_9000_11.5593_48.1462_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0078", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<104><120><168><173>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_2200_116.3324_39.9691_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0079", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<449><118><527><185>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_9000_116.3327_39.9385_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0080", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<66><155><131><207>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_9400_11.5652_48.1442_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0081", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<332><79><396><114>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_9400_116.3328_39.9367_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0082", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<537><294><600><420>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_9000_11.5680_48.1460_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0083", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<535><221><573><316>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14800_10300_11.4748_48.2151_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0084", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><0><46><59>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_14800_11.5700_48.1198_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0085", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<10><235><82><287>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15700_8100_11.4853_48.2307_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0086", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<348><293><402><349>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_8500_11.5715_48.1482_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0087", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<310><170><341><207>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22500_13000_11.5567_48.1939_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0088", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<208><213><239><231>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_4000_11.5752_48.1683_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0089", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<361><350><386><403>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22900_12600_11.5611_48.1966_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0090", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<109><141><193><235>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) mansard_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_9400_11.5713_48.1441_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0091", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<354><344><424><364>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23800_13000_11.5707_48.1936_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0092", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<109><76><163><213>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_4500_11.5750_48.1661_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0093", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<132><142><186><187>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13500_11.5856_48.1896_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0094", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<363><83><413><120>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_12100_11.5767_48.1318_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0095", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<52><119><98><258>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_12100_11.5957_48.1995_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0096", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><322><42><388>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_11700_11.5828_48.1335_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0097", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<520><346><540><398>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_12600_11.6095_48.1956_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0098", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<379><109><419><152>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_4500_11.5300_48.1671_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0099", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<348><469><383><509>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_10300_11.6158_48.2120_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0100", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<219><47><316><103>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28800_21600_11.6213_48.1305_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0101", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<149><547><191><582>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8100_12600_116.2741_39.9347_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0102", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<453><369><527><439>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_12100_11.5975_48.1314_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0103", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><387><68><443>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_9900_27000_116.2920_39.8310_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0104", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<436><268><469><313>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_15700_11.6121_48.1148_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0105", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<209><575><280><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_4900_116.4270_39.9926_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0106", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<82><218><112><255>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2200_4500_11.5388_48.1669_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0107", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><11><70><157>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_1300_11.5852_48.1802_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0108", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<271><281><370><411>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_4500_11.5421_48.1668_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0109", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<322><263><370><321>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_14800_11.5459_48.1204_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0110", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><101><32><130>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) office ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_6700_116.4165_39.9844_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0111", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<251><312><292><352>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_6300_11.5478_48.1586_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0112", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<428><258><554><296>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) multi_family_house", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13500_9900_116.4196_39.9700_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0113", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<325><536><425><588>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_14800_11.5486_48.1203_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0114", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<49><437><117><468>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_5400_116.4247_39.9903_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0115", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<17><151><64><207>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) pinnacle_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_9000_11.5499_48.1464_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0116", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<63><80><129><103>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_7600_116.3510_39.9800_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0117", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<316><265><369><362>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_10300_11.5529_48.1405_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0118", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<394><181><437><258>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_5400_116.3561_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0119", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<250><318><284><356>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_15300_11.5518_48.1180_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0120", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><182><36><257>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_5400_116.3585_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0121", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<258><232><281><269>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_14800_11.5580_48.1201_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0122", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<93><133><130><195>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_6300_116.4141_39.9862_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0123", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<453><286><499><351>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_6700_11.5685_48.1563_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0124", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<93><133><130><195>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_6300_116.4141_39.9862_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0125", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<217><471><276><542>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) mansard_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_6700_11.5745_48.1562_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0126", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<59><403><140><523>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_2200_11.5789_48.1763_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0127", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<116><262><166><303>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hippid_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_15300_11.5787_48.1174_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0128", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<482><517><522><575>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_2200_11.5816_48.1763_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0129", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<358><143><416><209>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_8100_11.5803_48.1498_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0130", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<256><449><351><508>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_2700_11.5304_48.1752_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0131", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<542><310><600><368>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_15300_11.5847_48.1173_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0132", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<387><324><482><418>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_4500_11.5871_48.1658_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0133", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<194><363><299><448>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) mansard_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_5800_11.5868_48.1600_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0134", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<301><434><349><527>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) arched_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_10300_27000_116.2958_39.8310_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0135", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<298><554><358><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) hipped_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_11700_17500_116.3082_39.8995_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0136", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<85><435><144><471>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) mansard_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_30600_18900_116.4851_39.8904_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0137", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<510><376><533><419>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8100_13000_116.2741_39.9318_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0138", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><82><208><159>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_4900_116.4246_39.9926_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0139", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<234><458><383><498>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_9900_116.2983_39.9342_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0140", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<470><239><547><290>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_5400_116.3139_39.9546_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0141", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<421><0><464><27>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_5400_116.3273_39.9547_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0142", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<163><321><280><360>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_900_7200_116.2800_39.9463_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0143", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<252><50><297><70>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_10800_116.3299_39.9304_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0144", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box:-[<0><477><15><535>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) arched_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_5800_116.3297_39.9529_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0145", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<68><211><82><227>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_1800_116.3324_39.9709_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0146", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<358><545><389><565>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) arched_roof", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_900_116.3324_39.9750_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0147", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<529><337><554><357>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row_roof_shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14400_9900_11.4707_48.2181_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0148", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<121><0><145><50>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22900_13000_11.5610_48.1938_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0149", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box:-[<0><194><21><260>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) police_station ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23400_13000_11.5664_48.1937_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0150", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<44><165><63><206>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_11700_11.5959_48.2023_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0151", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<168><378><183><390>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) mansard_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_20700_11.5926_48.1376_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0152", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<514><591><540><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_9000_11.6162_48.2213_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0153", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<489><311><521><347>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_1800_11.6032_48.1776_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0154", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<108><137><144><163>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_9400_11.6136_48.1432_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0155", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<104><40><136><68>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_4900_11.5360_48.1651_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0156", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<21><310><97><350>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) shed_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_14400_11.5487_48.1221_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0157", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<534><309><600><333>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_4500_11.5569_48.1665_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0158", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<452><414><467><448>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_9400_11.5592_48.1444_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0159", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<476><0><526><36>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_12100_11.5706_48.1320_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0160", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<64><252><77><307>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) mansard_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_15700_11.5759_48.1157_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0161", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<107><586><143><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_15300_11.5726_48.1175_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0162", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<434><373><459><401>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_11700_11.5707_48.1338_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0163", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<572><185><587><222>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_6300_11.5659_48.1582_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0164", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<586><540><600><569>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) mansard_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_2700_11.5607_48.1745_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0165", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<348><359><467><403>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_9400_11.5471_48.1446_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0166", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<77><36><162><127>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_4500_11.5448_48.1667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0167", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<50><277><84><362>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_14800_11.5398_48.1205_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0168", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<264><492><283><532>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_15700_11.6208_48.1146_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0169", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<252><470><267><491>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_9000_11.6197_48.1448_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0170", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<99><0><145><54>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_15300_11.6149_48.1166_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0171", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<288><0><360><40>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_1800_11.6059_48.1775_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0172", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<192><461><384><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_10800_15300_11.5941_48.1170_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0173", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<494><223><508><244>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_10300_11.6201_48.2119_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0174", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<241><279><281><311>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_11700_11.6099_48.2020_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0175", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><331><76><357>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_5800_116.3667_39.9882_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0176", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><339><66><401>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_5400_116.3690_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0177", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<564><486><600><523>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_1300_116.3718_40.0085_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0178", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><380><71><459>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_2200_116.3718_40.0045_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0179", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<556><518><600><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5800_116.3720_39.9882_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0180", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><0><53><51>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) arched_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_900_116.3718_40.0103_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0181", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><0><50><28>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_1800_116.3741_40.0063_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0182", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<467><61><595><133>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof_complex", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_5400_116.3743_39.9901_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0183", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<394><520><468><590>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_5800_116.3743_39.9883_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0184", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><451><78><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_900_116.3741_40.0103_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0185", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<570><561><600><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_4500_116.3901_39.9942_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0186", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<104><0><267><20>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9400_4900_116.3953_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0187", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box:-[<382><158><406><175>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15300_19300_116.3420_39.8868_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0188", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<242><63><301><99>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_21100_6300_116.3954_39.9808_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0189", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<345><305><414><322>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_19300_116.4299_39.8872_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0190", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<576><213><600><231>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28800_14800_116.4680_39.9199_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0191", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<177><122><295><151>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_29200_19800_116.4721_39.8838_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0192", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<100><172><188><284>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_1800_116.4034_40.0064_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0193", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<271><51><389><100>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_4000_116.4035_39.9965_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0194", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<359><308><600><597>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_1800_116.4058_40.0064_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0195", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<143><159><278><183>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_11700_116.4091_39.9619_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0196", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<34><212><132><262>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12100_4900_116.4112_39.9925_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0197 ", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<277><287><533><318>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_9000_116.4142_39.9740_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0198", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<311><76><536><113>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_4900_116.4164_39.9925_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0199", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<339><39><396><92>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_7200_116.3480_39.9818_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0200", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<474><319><534><398>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13900_10300_116.4219_39.9682_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0201", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<221><85><270><117>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_11700_116.4272_39.9619_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0202", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><0><152><31>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_7200_116.3509_39.9818_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0203", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<185><0><375><34>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_7200_116.3533_39.9818_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0204", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<72><66><290><93>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_11200_116.3564_39.9638_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0205", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<97><262><208><339>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_5800_116.3561_39.9882_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0206", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<559><315><588><346>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_5800_116.3585_39.9882_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0207", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<131><187><260><222>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_1800_116.3665_40.0062_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0208", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<473><503><497><550>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4900_116.3667_39.9923_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0209", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<5><240><48><361>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_1800_116.3689_40.0062_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0210", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<550><555><597><584>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_4900_116.3877_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0211", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<100><522><276><593>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_7600_116.3457_39.9800_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0212", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<333><469><409><542>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9900_6300_116.3983_39.9861_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0213", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><184><103><247>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_900_116.3347_39.9750_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0214", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<27><180><110><219>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11700_9400_116.3433_39.9367_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0215", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<32><320><106><398>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_1300_7600_116.2824_39.9445_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0216", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<490><518><600><552>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_11200_116.2931_39.9283_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0217", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<44><44><224><116>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_3100_116.2927_39.9648_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0218", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<18><457><128><543>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_7600_116.2929_39.9445_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0219", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<334><66><419><150>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_900_116.3113_39.9748_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0220", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<131><357><259><412>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_9400_116.3117_39.9366_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0221", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<291><192><341><280>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_11200_116.3141_39.9285_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0222", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><0><63><20>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_12100_116.3142_39.9244_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0223", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<583><19><600><68>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_1300_116.3137_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0224", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<160><521><290><552>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_900_116.3137_39.9749_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0225", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<166><66><186><119>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_9400_116.3140_39.9366_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0226", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<317><157><420><241>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_9400_11.6161_48.2184_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0227", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<143><568><171><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_29200_22000_11.6254_48.1275_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0228", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<418><235><460><283>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_15300_11.5968_48.1170_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0229", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<40><485><86><534>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_4500_11.5361_48.1669_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0230", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<328><21><381><100>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_14400_11.5460_48.1222_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0231", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<33><451><45><468>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_6700_11.5477_48.1568_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0232", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<95><432><144><480>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_6300_11.5505_48.1585_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0233", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<138><122><169><148>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_14400_11.5520_48.1220_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0234", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<110><0><150><43>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_15700_11.5544_48.1161_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0235", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<415><206><487><351>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_4900_11.5602_48.1646_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0236", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<94><26><162><84>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_9000_11.5619_48.1461_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0237", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<503><487><556><528>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_9000_11.5653_48.1460_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0238", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<389><203><516><282>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_12100_11.5673_48.1320_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0239", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<406><280><460><350>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_14400_11.5701_48.1216_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0240", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<401><283><449><344>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_4900_11.5723_48.1643_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0241", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<306><288><363><339>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_5800_11.5781_48.1601_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0242", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<206><179><233><279>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_5800_11.5808_48.1601_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0243", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<46><128><89><162>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_4900_11.5299_48.1653_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0244", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><374><42><450>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_6300_11.5867_48.1577_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0245", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<157><148><191><204>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_11700_17100_116.3081_39.9024_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0246", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<74><268><117><293>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_30600_19300_116.4851_39.8875_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0247", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<393><370><562><476>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof_complex", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12100_17500_116.3119_39.8996_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0248", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<18><356><77><442>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8500_13000_116.2779_39.9318_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0249", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<59><140><157><161>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_9900_27400_116.2921_39.8281_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0250", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<227><73><358><352>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_5400_116.3479_39.9899_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0251", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<433><286><453><326>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_5800_116.3479_39.9881_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0252", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<589><536><600><596>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_4500_116.4270_39.9944_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0253", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<201><374><302><447>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_5800_116.3509_39.9881_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0254", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<161><82><185><111>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_5400_116.3532_39.9899_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0255", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<306><171><392><237>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_1300_116.3665_40.0085_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0256", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<21><201><55><229>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_9900_116.3511_39.9697_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0257", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<426><455><525><595>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_31000_18900_116.4889_39.8904_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0258", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<213><167><249><193>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_6700_11.5866_48.1559_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0259", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<5><454><47><490>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_15700_11.5786_48.1156_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0260", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<463><587><538><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_13500_116.3353_39.9182_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0261", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<186><0><308><115>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_12100_9000_116.3456_39.9386_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0262", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><1><68><40>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13500_5800_116.3537_39.9530_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0263", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<21><502><41><531>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_3100_116.2903_39.9648_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0264", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><92><185><208>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_6700_116.2928_39.9486_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0265", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<345><0><439><41>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_1800_116.2979_39.9707_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0266", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<178><40><233><82>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_9000_116.3035_39.9383_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0267", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<170><87><190><112>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_9400_116.3035_39.9365_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0268", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><541><56><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_11700_116.3065_39.9262_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0269", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><541><56><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_11700_116.3065_39.9262_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0270", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<327><132><509><210>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5800_12100_116.3089_39.9244_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0271", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<265><249><352><349>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15300_18900_116.3420_39.8897_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0272", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<11><488><38><549>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6300_116.3917_39.9807_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0273", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<540><343><575><399>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27000_12100_116.4510_39.9392_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0274", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<162><371><276><515>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_29200_20200_116.4721_39.8809_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0275", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<431><510><538><571>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_1300_116.4034_40.0087_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0276", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<79><336><118><376>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_4900_116.4088_39.9925_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0277", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<351><461><476><561>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12100_11700_116.4114_39.9619_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0278", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<125><576><177><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_4500_116.4164_39.9943_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0279", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<307><383><407><495>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_6300_116.4165_39.9862_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0280", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<493><291><539><390>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_9400_116.4166_39.9723_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0281", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<191><178><291><204>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_7600_116.3533_39.9800_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0282", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<147><158><219><231>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4000_8100_116.3639_39.9778_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0283", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<258><353><302><408>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4500_116.3666_39.9941_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0284", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<167><149><223><194>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_7200_116.3457_39.9818_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0285", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<7><528><34><548>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0286", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<392><97><428><132>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_9000_116.3351_39.9385_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0287", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<192><466><240><498>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13900_5400_116.3560_39.9548_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0288", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<496><401><581><467>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_7200_116.2905_39.9463_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0289", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<293><234><363><301>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_2700_116.2927_39.9666_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0290", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<22><94><125><194>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_6300_116.2928_39.9504_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0291", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<548><413><600><464>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_3100_116.2956_39.9648_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0292", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<145><212><194><239>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_3100_116.2979_39.9649_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0293", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><120><64><170>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_11200_116.3012_39.9284_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0294", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<160><49><202><79>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_6300_116.3010_39.9505_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0295", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<327><477><384><505>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_6700_116.3010_39.9487_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0296", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<111><323><209><462>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_9000_116.3011_39.9383_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0297", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><236><10><345>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_900_116.3008_39.9748_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0298", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<271><349><468><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_9400_116.3012_39.9365_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0299", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<174><54><320><193>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_10800_116.3036_39.9302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0300", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><400><34><448>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_11200_116.3036_39.9284_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0301", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<500><384><543><430>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_1300_116.3031_39.9730_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0302", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<509><427><568><513>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_2700_116.3032_39.9667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0303", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><0><62><31>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_3100_116.3032_39.9649_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0304", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<320><3><432><37>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_5800_116.3033_39.9527_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0305", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<329><351><481><399>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6300_116.3034_39.9505_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0306", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<45><458><155><542>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_20700_11.5969_48.1375_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0307", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<39><405><48><422>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_13000_11.6094_48.1927_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0308", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<118><48><160><119>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_29200_21600_11.6256_48.1304_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0309", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<323><117><352><152>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_11700_11.5976_48.1332_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0310", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<282><278><328><312>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_15700_11.5967_48.1152_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0311", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<306><308><384><395>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_11700_11.6097_48.1329_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0312", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<108><86><170><123>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_15700_11.6148_48.1148_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0313", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<154><246><182><282>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_9400_11.6162_48.1431_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0314", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<20><217><67><266>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_15300_11.6182_48.1165_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0315", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<117><74><162><99>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_15700_11.6182_48.1147_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0316", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<129><271><225><355>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_7600_11.6200_48.1511_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0317", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<192><42><224><85>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_9400_11.6196_48.1430_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0318", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><46><29><110>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_15300_11.6209_48.1164_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0319", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<216><123><237><136>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1800_11.5515_48.1787_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0320", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<231><156><309><264>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_9400_11.5498_48.1446_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0321", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<351><84><425><112>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_4500_11.5603_48.1664_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0322", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<47><86><157><174>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_4500_11.5663_48.1663_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0323", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<163><125><235><160>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_6700_11.5658_48.1564_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0324", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<66><155><131><207>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_11700_11.5674_48.1338_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0325", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<99><60><133><106>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_4500_11.5690_48.1662_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0326", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<456><275><535><357>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_6300_11.5686_48.1581_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0327", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><0><59><27>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_6300_11.5746_48.1580_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0328", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<496><262><556><307>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_8100_11.5742_48.1499_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0329", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<255><193><322><258>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_1800_11.5790_48.1781_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0330", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<171><13><205><132>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_5400_11.5782_48.1619_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0331", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<90><108><130><154>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_5400_11.5809_48.1619_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0332", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<40><140><190><264>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_8500_11.5802_48.1480_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0333", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<27><20><74><60>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_3100_11.5303_48.1734_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0334", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<554><497><600><562>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_10800_116.3118_39.9302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0335", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><28><20><109>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_11200_116.3118_39.9284_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0336", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<314><176><359><206>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_11700_116.3118_39.9262_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0337", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<548><208><600><234>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_9000_116.3117_39.9384_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0338", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<128><408><228><438>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_900_116.3219_39.9749_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0339", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<151><0><263><113>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_11200_116.3276_39.9285_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0340", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<405><420><438><473>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_900_7600_116.2800_39.9445_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0341", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<551><406><600><490>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_11200_116.3299_39.9285_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0342", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<92><1><209><82>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_13900_116.3330_39.9164_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0343", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<197><12><231><49>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_13000_21100_11.4517_48.1378_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0344", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<300><0><384><124>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14400_10300_11.4705_48.2152_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0345", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<350><426><368><458>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_13000_12600_116.3200_39.9349_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0346", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<371><326><404><371>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26500_18000_116.4467_39.8967_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0347", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<240><341><258><355>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27400_16600_116.4550_39.9068_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0348", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<270><554><324><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10300_6300_116.4007_39.9861_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0349", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><198><67><222>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_4500_116.4088_39.9943_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0350", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<146><124><270><289>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9000_4900_116.3930_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0351", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<388><383><413><395>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9900_11700_116.3985_39.9618_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0352", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<344><530><363><571>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_1800_116.2955_39.9707_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0353", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<79><438><104><461>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13900_11.5854_48.1867_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0354", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<307><403><347><480>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_12100_11.6000_48.1994_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0355", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<264><486><288><511>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_12100_11.6097_48.1992_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0356", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<54><517><75><549>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28800_22000_11.6211_48.1276_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0357", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<480><343><528><397>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_2200_11.6031_48.1758_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0358", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<61><88><136><195>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_7200_11.6228_48.1528_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0359", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<238><159><259><176>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_900_11.5853_48.1820_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0360", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><13><40><80>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_1300_11.5879_48.1802_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0361", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<21><384><31><400>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_31000_19300_116.4889_39.8875_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0362", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><383><76><419>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_5800_116.3532_39.9881_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0363", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<278><574><362><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_10300_116.3534_39.9679_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0364", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<488><453><534><518>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_14800_11.5546_48.1202_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0365", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<219><400><253><491>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_2700_11.5634_48.1744_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0366", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<311><554><357><596>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_8100_11.5715_48.1499_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0367", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<406><142><444><183>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_3600_11.5752_48.1701_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0368", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<222><526><247><556>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_15300_11.5760_48.1175_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0369", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<306><398><361><454>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_1800_11.5817_48.1781_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0370", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<129><504><147><547>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_10300_27400_116.2958_39.8281_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0371", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<167><546><239><599>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_9000_116.3902_39.9739_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0372", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<567><297><598><330>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12100_17100_116.3119_39.9025_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0373", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<570><535><597><586>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_3600_116.3666_39.9981_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0374", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<222><107><271><153>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_4500_116.4246_39.9944_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0375", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><102><70><140>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_900_116.3665_40.0103_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0376", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><151><49><187>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_3600_116.3689_39.9981_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0377", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<324><446><488><493>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_900_116.3688_40.0103_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0378", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<449><289><511><338>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_9000_116.3879_39.9739_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0379", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<4><112><40><141>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_5800_116.3379_39.9529_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0380", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<282><190><316><237>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_2200_116.3377_39.9691_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0381", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<259><244><379><312>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_2200_116.3401_39.9692_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0382", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<80><346><115><416>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_5400_116.3509_39.9899_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0383", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<571><487><600><519>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_9900_116.3534_39.9697_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0384", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<352><114><365><140>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof_v2", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7200_4500_116.3824_39.9942_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0385", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<327><8><337><20>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_9400_116.3879_39.9721_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0386", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<481><19><504><31>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_1300_116.3688_40.0085_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0387", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><254><48><334>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) arched_roof", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_5800_116.3456_39.9881_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0388", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<169><57><199><111>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_9400_116.3903_39.9721_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0389", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<210><219><258><282>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_4000_116.3690_39.9963_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0390", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<328><91><342><116>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7600_4500_116.3848_39.9942_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0391", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><445><189><549>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_1800_116.3400_39.9710_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0392", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<239><0><362><18>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_9400_116.2906_39.9364_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0393", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<156><121><202><144>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_10300_116.2983_39.9324_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0394", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<444><434><474><453>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_3100_116.3348_39.9651_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0395", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<228><273><365><326>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_5400_116.3379_39.9547_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0396", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<403><130><492><187>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_10300_116.2959_39.9324_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0397", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><289><48><343>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_5400_116.3115_39.9546_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0398", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><181><8><203>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_9000_116.2930_39.9382_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0399", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<396><372><496><415>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_9400_116.2930_39.9364_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0400", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<438><352><469><372>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_9000_116.2906_39.9382_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0401", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<88><250><125><271>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_1800_116.3377_39.9709_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0402", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><537><21><559>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7600_4900_116.3848_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0403", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<359><538><422><566>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7200_4900_116.3825_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0404", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<391><0><511><17>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4000_116.3666_39.9963_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0405", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<512><253><591><327>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15300_8500_11.4808_48.2279_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0406", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<196><67><268><91>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_18400_21600_11.5096_48.1330_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0407", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<515><553><552><576>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22500_12600_11.5568_48.1967_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0408", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<277><261><339><284>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23800_12600_11.5708_48.1964_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0409", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<188><111><214><157>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13500_11.5899_48.1895_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0410", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<222><82><241><102>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_11700_11.6002_48.2022_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0411", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<477><453><596><489>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7600_9900_116.3193_39.9343_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0412", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<338><138><414><218>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7600_10300_116.3193_39.9325_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0413", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<412><58><512><95>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_2200_116.3219_39.9690_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0414", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<415><163><568><385>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1800_116.3219_39.9708_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0415", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<355><46><446><76>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1800_116.3242_39.9709_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0416", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><422><65><497>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_12600_11.5762_48.1963_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0417", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<125><549><148><583>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_13000_11.5761_48.1934_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0418", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><185><11><195>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_12600_11.5859_48.1961_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0419", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<212><537><261><551>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13000_11.5857_48.1932_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0420", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<261><63><382><87>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_12600_11.5902_48.1960_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0421", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<1><399><48><455>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13000_11.5900_48.1931_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0422", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<186><270><210><315>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_30600_13000_11.6438_48.1919_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0423", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<129><537><175><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_31000_12600_11.6483_48.1947_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0424", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<127><257><148><267>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_16200_11.5966_48.1129_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0425", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<450><242><493><253>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_2200_116.3243_39.9691_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0426", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<407><183><430><201>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_1300_11.6033_48.1798_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0427", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<353><218><403><263>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_9400_11.6015_48.1434_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0428", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<127><283><187><368>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_6300_11.6082_48.1572_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0429", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<358><283><382><307>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_1300_11.6060_48.1798_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0430", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<547><114><599><158>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) multiple_eave_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_6700_11.6108_48.1554_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0431", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<197><148><284><242>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof_v2", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_5800_116.3139_39.9528_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0432", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<396><31><458><80>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_16600_11.5965_48.1111_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0433", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<544><584><577><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_1800_11.5575_48.1786_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0434", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<381><266><427><305>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_16200_11.5785_48.1134_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0435", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<128><527><151><574>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_3100_11.5364_48.1732_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0436", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<528><260><573><295>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_6700_11.6142_48.1553_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0437", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<585><237><600><255>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_1300_116.3113_39.9730_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0438", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<415><119><434><140>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2200_14400_11.5366_48.1224_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0439", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<168><124><196><173>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_2700_116.2979_39.9667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0440", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<536><356><600><389>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5400_116.3719_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0441", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><129><90><299>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_900_11.6034_48.1816_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0442", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<36><118><77><155>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_6300_11.6143_48.1571_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0443", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<37><36><67><75>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1300_11.5516_48.1810_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0444", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<254><46><293><86>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_11200_11.5648_48.1362_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0445", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<481><447><523><466>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6700_19800_116.2616_39.8827_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0446", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<107><394><184><482>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14400_11.5641_48.1218_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0447", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<436><468><501><550>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_3600_116.4035_39.9983_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0448", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<347><404><365><465>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_10800_116.3012_39.9302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0449", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><246><12><265>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_2200_11.5574_48.1768_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0450", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<88><457><126><501>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14800_11.5640_48.1200_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0451", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<73><430><149><509>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_16600_11.5757_48.1116_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0452", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<16><337><146><365>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1300_116.3219_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0453", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<73><244><99><297>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12600_13000_116.3163_39.9320_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0454", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<129><85><153><169>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6700_116.3034_39.9487_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0455", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<50><166><72><179>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1300_116.3242_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0456", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<5><0><65><14>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5800_116.3010_39.9527_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0457", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><433><15><457>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_10800_116.3903_39.9658_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0458", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<295><558><379><576>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6700_116.3917_39.9779_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0459", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<274><188><396><281>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7200_9900_116.3170_39.9343_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0460", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<432><15><473><48>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) apartment block", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_9900_11.5557_48.1422_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0461", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<0><548><21><569>]", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Answer Choices": [ + "(A) administration", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_13500_116.3329_39.9182_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0462", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<75><306><90><328>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) row roof shed", + "(B) gable_roof", + "(C) flat_roof", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9000_11.6205_48.2212_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0463", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<115><187><150><212>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9400_11.6204_48.2183_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0464", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<226><112><321><159>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_4500_11.5542_48.1665_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0465", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<110><206><275><261>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_15700_11.5819_48.1155_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0466", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<463><107><487><135>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_12600_21100_11.4475_48.1379_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0467", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<0><530><14><570>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9900_11.6202_48.2148_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0468", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<391><207><427><262>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_18000_22000_11.5051_48.1302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0469", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<0><37><58><109>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_3100_11.5330_48.1733_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0470", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<226><531><267><576>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) other", + "(B) gable_roof", + "(C) row roof shed", + "(D) flat_roof ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_4900_11.5541_48.1647_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0471", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<414><344><454><386>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_12100_11.5827_48.1317_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0472", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<81><344><128><396>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof_v2", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_2200_11.6058_48.1757_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0473", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<29><247><71><290>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) other", + "(C) gable_roof", + "(D) hippde_roof_v2 ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_4900_11.5420_48.1650_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0474", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<247><94><358><157>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_13000_11.6051_48.1928_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0475", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<103><245><195><273>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_5800_116.3273_39.9529_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0476", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<164><356><316><424>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_1300_116.3741_40.0085_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0477", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<567><369><593><380>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_5400_116.4270_39.9903_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0478", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<518><98><575><170>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13500_7200_116.3537_39.9467_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0479", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<537><483><573><537>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_7600_116.2905_39.9445_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0480", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<109><156><134><183>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_2200_116.3665_40.0044_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0481", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<556><400><566><416>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_4900_116.3901_39.9924_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0482", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<259><200><329><243>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_16200_14800_116.3501_39.9193_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0483", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box:-[<501><5><537><93>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_3600_116.3531_39.9980_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0484", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<64><156><121><191>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_10300_116.3511_39.9679_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0485", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<69><116><109><170>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_9900_116.2959_39.9342_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0486", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<157><67><222><90>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24700_12600_11.5805_48.1962_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0487", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<2><348><26><403>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24700_21100_11.5774_48.1351_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0488", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<410><237><432><307>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_30600_12600_11.6440_48.1948_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0489", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<0><0><32><22>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_9000_11.6042_48.1452_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0490", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial images given thebounding boxes for referring objects. Bounding box in the format (xmin, ymin,xmax, ymax), where the top left corner is (x_min, y_min) and the bottom-rightcorner is (x_max, y_max). The resolution of satellite image is 600 x 600.Bounding box: -[<200><135><235><160>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_6300_11.6169_48.1570_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0491", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<254><505><281><552>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9900_15300_11.5880_48.1172_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0492", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<269><183><337><213>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_2700_116.3348_39.9669_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0493", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<491><404><520><426>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_5400_116.3402_39.9547_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0494", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<555><582><600><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_5800_116.3402_39.9529_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0495", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<264><452><312><475>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24700_20700_11.5776_48.1380_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0496", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<458><487><498><516>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_9000_11.6016_48.1452_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0497", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<180><145><212><185>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) hipped_roof_v2", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_9400_11.6042_48.1434_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0498", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<172><207><221><277>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_6300_11.6203_48.1569_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0499", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<38><247><93><310>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9900_15700_11.5880_48.1154_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0500", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<207><203><240><227>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_21100_11.5731_48.1352_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0501", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<358><344><385><371>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_20700_11.5733_48.1381_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0502", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<292><23><308><46>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_10800_16600_11.5938_48.1112_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0503", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<544><63><569><87>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_6700_11.6169_48.1552_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0504", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<1><257><53><312>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_6300_11.6230_48.1569_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0505", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<113><439><168><470>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_2700_11.5365_48.1750_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0506", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<283><211><315><232>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2200_14800_11.5365_48.1206_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0507", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<569><0><600><89>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_9000_11.5532_48.1463_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0508", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<1><200><83><249>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_10800_11.5649_48.1380_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0509", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<85><202><129><238>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) hipped_roof_v2", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_3100_116.3325_39.9651_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0510", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<49><3><65><19>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_900_11.6061_48.1816_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0511", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<423><84><465><207>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_14800_11.5338_48.1206_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0512", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<186><353><233><401>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) hipped_roof_v1", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_11700_11.5526_48.1342_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Fine-grained object type recognition/0513", + "Question_type": "Single Choice", + "Text": "Recognize the category of objects from satellite and aerial imagesgiven the bounding boxes for referring objects. Bounding box in the format(xmin, ymin, xmax, ymax), where the top left corner is (x_min, y_min) and thebottom-right corner is (x_max, y_max). The resolution of satellite image is600 x 600. Bounding box: -[<362><521><401><600>]", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Fine-grained object type recognition", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) flat_roof", + "(B) gable_roof", + "(C) row roof shed", + "(D) other ", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_5400_116.3456_39.9899_RGB.tif" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Perception/Overall_counting.json b/jsons/Pedosphere/Urban_Development/Perception/Overall_counting.json new file mode 100644 index 0000000000000000000000000000000000000000..b0f9828065b14ac1546d1a158138288fe3faa3fd --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Perception/Overall_counting.json @@ -0,0 +1,11046 @@ +[ + { + "Question_id": "Overall counting/0000", + "Question_type": "Single Choice", + "Text": "How many gable_roof are there in the whole picture? 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", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 79", + "(B) 78", + "(C) 77 ", + "(D) 76", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_2700_116.2979_39.9667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0484", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 54", + "(B) 55", + "(C) 56", + "(D) 57", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5400_116.3719_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0485", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 119", + "(B) 115", + "(C) 116", + "(D) 117", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_6300_11.6143_48.1571_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0486", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 554", + "(B) 555", + "(C) 556", + "(D) 557", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1300_11.5516_48.1810_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0487", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 124", + "(B) 125", + "(C) 126", + "(D) 127", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_11200_11.5648_48.1362_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0488", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 67", + "(B) 68", + "(C) 69", + "(D) 70", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6700_19800_116.2616_39.8827_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0489", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14400_11.5641_48.1218_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0490", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 34", + "(B) 35", + "(C) 36", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_3600_116.4035_39.9983_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0491", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_10800_116.3012_39.9302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0492", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 30", + "(B) 29", + "(C) 28", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_2200_11.5574_48.1768_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0493", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 24", + "(B) 25", + "(C) 26", + "(D) 27", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14800_11.5640_48.1200_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0494", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 73", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_16600_11.5757_48.1116_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0495", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 63", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1300_116.3219_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0496", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 141", + "(B) 145", + "(C) 146", + "(D) 147", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12600_13000_116.3163_39.9320_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0497", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 75", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6700_116.3034_39.9487_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0498", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 86", + "(B) 85", + "(C) 84", + "(D) 83", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1300_116.3242_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0499", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 44", + "(B) 45", + "(C) 46", + "(D) 47", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5800_116.3010_39.9527_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0500", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 74", + "(B) 75", + "(C) 76", + "(D) 77", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_10800_116.3903_39.9658_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall counting/0501", + "Question_type": "Single Choice", + "Text": "How many buildings are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Overall counting", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 34", + "(B) 35", + "(C) 36", + "(D) 37", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6700_116.3917_39.9779_RGB.tif" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Perception/Visual_grounding.json b/jsons/Pedosphere/Urban_Development/Perception/Visual_grounding.json new file mode 100644 index 0000000000000000000000000000000000000000..5070ddd6a3be43503bcf28db981b0e963b24e055 --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Perception/Visual_grounding.json @@ -0,0 +1,7652 @@ +[ + { + "Question_id": "Visual grounding/0000", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road, blue roof, C-shaped.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<451><15><470><43>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15700_18900_116.3457_39.8897_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0001", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the crossroads, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<456><515><600><562>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_1800_116.3741_40.0063_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0002", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the left side of the highway, without aroof and has a trapezoidal shape", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<20><342><86><367>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_3100_11.5633_48.1726_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0003", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is the largest shade of grey in the picture,with an irregular square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<382><25><470><165>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_16600_14800_116.3538_39.9193_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0004", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<5><164><29><236>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10300_6700_116.4007_39.9843_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0005", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the building type C, with a brown roofand a rectangle shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<377><438><479><576>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_16600_14400_116.3538_39.9222_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0006", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located to the left of the sports field and has an off-white roof and aY-shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<27><517><83><571>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26500_18400_116.4467_39.8938_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0007", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<246><178><307><245>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_21100_6700_116.3955_39.9779_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0008", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the image and has a gray-blue roof and a long strip shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<29><508><155><531>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27900_12100_116.4595_39.9393_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0009", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<71><263><167><323>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_15300_116.4297_39.9161_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0010", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the road, blue roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<333><251><380><327>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28800_20200_116.4683_39.8809_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0011", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is on the left side of the road, with a grey roof and a long strip shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<42><263><75><399>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10300_11700_116.4009_39.9618_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0012", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<31><250><121><281>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_18900_116.4299_39.8901_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0013", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building, on the left of the picture, is slender and has a blue roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<4><391><64><404>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_900_116.4034_40.0105_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0014", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building isoctagonal with a black roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<204><103><288><192>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_6700_116.4142_39.9844_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0015", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof and arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<513><96><600><131>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8500_12600_116.2779_39.9347_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0016", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road and its roof is white.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<222><0><497><71>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_4500_116.3877_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0017", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<36><262><104><296>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26100_18000_116.4430_39.8967_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0018", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the road. Its roof is white and in a long stripshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<215><356><229><414>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9000_4500_116.3930_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0019", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<311><127><395><154>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26100_18400_116.4430_39.8938_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0020", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the road. Its roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<77><503><157><534>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9900_6700_116.3983_39.9843_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0021", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<3><538><64><579>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26500_14800_116.4465_39.9198_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0022", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower left of the road. It is trapezoidal and has a whiteroof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<176><528><227><588>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_12100_9400_116.3456_39.9367_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0023", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the road and has a square roof and a white roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><419><76><498>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13500_7600_116.3538_39.9449_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0024", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<173><102><196><120>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27400_11700_116.4548_39.9421_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0025", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. It has a brown roof and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<498><0><600><66>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_11200_116.2907_39.9283_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0026", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the picture. It has a brown roof and is shaped like arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<99><391><234><467>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_10800_116.2930_39.9301_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0027", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<375><206><530><241>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28300_11700_116.4632_39.9422_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0028", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road and has a grey roof in a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<64><194><136><278>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_1300_116.3008_39.9730_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0029", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located slightly above the middle of the picture. It has a grey roof and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<315><179><472><217>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_2700_116.3009_39.9667_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0030", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<293><341><358><371>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6300_19800_116.2578_39.8827_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0031", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is on the left side of the road. It has a grey roof and is rectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<44><293><90><439>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_3100_116.3009_39.9649_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0032", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the upper left corner of the road, with a U-shapedstructure and a grey roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<150><98><304><255>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5400_116.3010_39.9545_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0033", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is on the right side of the road. It has a grey roof and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<101><510><128><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_5400_116.3033_39.9545_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0034", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located at the bottom of the picture and has a grey and \"U\"-shaped roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<176><492><337><568>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_900_116.3031_39.9748_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0035", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located above the road and has a grey and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><240><131><274>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_12100_116.3066_39.9244_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0036", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<501><190><578><301>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_1300_116.4058_40.0087_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0037", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located above the road and has a grey and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<317><306><552><344>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_12100_116.3118_39.9244_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0038", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<31><87><80><146>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_2200_116.4058_40.0046_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0039", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located beneath the road and has a white and rectangularroof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<297><282><349><321>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_10800_116.3141_39.9303_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0040", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<262><195><351><239>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_3600_116.4058_39.9983_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0041", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the sports field and has a grey and rectangularroof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<455><167><488><293>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_11700_116.3141_39.9262_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0042", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<138><401><276><459>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_4000_116.4059_39.9965_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0043", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the road and has a white and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<145><207><344><235>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_9000_116.3140_39.9384_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0044", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<343><113><451><146>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_12100_116.4091_39.9601_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0045", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:This building is located upper side of the road and has a gray C-shaped roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<248><166><341><250>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13900_11.5897_48.1866_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0046", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:This building is located upper side of the road and has a gray C-shaped roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<248><166><341><250>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13900_11.5897_48.1866_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0047", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This building is located in the lower left corner of the intersection and is a rectangularstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<433><344><459><371>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_11700_11.6056_48.2021_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0048", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle of a triangular intersection, with a brown roof and a T--shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<255><417><316><485>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_12100_11.6054_48.1993_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0049", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<218><331><297><426>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_9000_116.4166_39.9741_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0050", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the road and has a white and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<408><32><462><67>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_10800_15700_11.5940_48.1153_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0051", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<79><99><329><124>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13500_10300_116.4196_39.9682_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0052", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<23><258><157><295>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13900_9900_116.4219_39.9700_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0053", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the lower right side of the highway, with a brownroof and a trapezoidal shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<498><540><573><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_11700_11.6070_48.1330_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0054", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the left side of the road and has an invertedU-shaped and orange roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<91><156><167><242>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_12100_11.6096_48.1311_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0055", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<159><237><203><319>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_16600_11.6059_48.1109_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0056", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<94><0><165><41>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_4000_116.3531_39.9962_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0057", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a flat roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<184><333><362><391>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_2700_11.5331_48.1751_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0058", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description：This building is located in the center of the forest, with a brownroof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<306><262><353><349>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_4900_11.5326_48.1652_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0059", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<458><312><545><348>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3600_8500_116.3615_39.9760_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0060", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: The building is located in the upper right corner of the intersection and has a green roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<581><0><600><22>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_16200_11.6086_48.1127_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0061", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a green roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<30><348><121><438>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_4500_11.5327_48.1670_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0062", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the picture, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0063", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<71><125><246><153>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_1800_116.3718_40.0063_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0064", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of the forest. There is agreen roof and a T-shaped shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<107><8><164><87>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_9000_11.6163_48.1449_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0065", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<185><36><227><144>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_10800_116.3880_39.9658_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0066", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located upper the straight road, with a green roof and an L-shapedstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<459><90><530><193>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_7200_11.6201_48.1529_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0067", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the green belt, with a white roof and a circularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<344><190><373><218>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_2700_11.5452_48.1748_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0068", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<321><57><399><103>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9400_4500_116.3953_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0069", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the picture and has a flat roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<513><63><562><202>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_7600_11.6227_48.1510_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0070", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<494><121><567><183>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_13900_116.3353_39.9164_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0071", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located below the playground, with a gray green roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<13><144><101><237>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_9400_11.6223_48.1430_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0072", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the left side of the lake, with a whiteroof and a circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<313><137><361><195>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_3100_11.5451_48.1730_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0073", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located between two buildings, with a gray green roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<281><201><381><255>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_1800_11.5488_48.1788_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0074", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the picture, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<6><151><126><205>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_2700_11.5425_48.1749_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0075", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the picture and has a white flat roof. It is a rectangularbuilding.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<217><194><300><277>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_4900_11.5447_48.1649_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0076", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the bottom right of the road, with a white roof and rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<483><232><499><247>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_2200_11.5487_48.1770_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0077", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This building is located in the upper right corner of the stadium. It has a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<494><72><539><118>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_3100_11.5424_48.1731_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0078", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the left side of the park forest, witha gray roof and a circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<294><508><352><563>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_2200_11.5514_48.1769_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0079", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located upper the straight road, with a brown roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<132><84><195><148>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_6700_11.5504_48.1567_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0080", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the parking lot, witha white roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<195><244><251><317>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_15300_11.5545_48.1179_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0081", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<181><201><255><273>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_11700_11.5553_48.1341_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0082", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<530><366><567><415>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_6700_11.6081_48.1554_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0083", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<26><230><53><275>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_5400_116.3297_39.9547_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0084", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located directly above the Y-junction and has a grey roof and rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<415><338><485><382>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_3100_11.5606_48.1727_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0085", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<368><96><490><140>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_31000_13000_11.6481_48.1918_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0086", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<447><275><517><319>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24700_13000_11.5804_48.1933_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0087", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<504><171><599><219>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_2700_116.3325_39.9669_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0088", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a rounded roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<207><292><295><323>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7200_9900_116.3170_39.9343_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0089", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<418><283><466><311>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_1300_116.3324_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0090", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a brown roof and asemi-circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<493><387><516><406>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_9000_11.5593_48.1462_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0091", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<94><230><126><266>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_2200_116.3324_39.9691_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0092", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<350><78><397><108>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_9000_116.3327_39.9385_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0093", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the road, with a graygreen roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<410><111><471><189>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_9400_11.5652_48.1442_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0094", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<96><205><129><234>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_9400_116.3328_39.9367_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0095", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower right corner of the ring road, with a white roof and aV-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<184><326><287><434>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_9000_11.5680_48.1460_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0096", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<284><294><349><316>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14800_10300_11.4748_48.2151_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0097", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the left side of the road, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<341><301><400><347>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_14800_11.5700_48.1198_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0098", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<133><309><163><338>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15700_8100_11.4853_48.2307_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0099", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper corner of the entire image, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<240><0><339><145>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_8500_11.5715_48.1482_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0100", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<120><151><166><244>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22500_13000_11.5567_48.1939_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0101", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the left side of the intersection, with a whiteroof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<274><96><329><165>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_4000_11.5752_48.1683_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0102", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<243><260><313><291>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22900_12600_11.5611_48.1966_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0103", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road and has a black and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<316><67><390><129>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_9400_11.5713_48.1441_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0104", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<156><359><202><377>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23800_13000_11.5707_48.1936_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0105", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located below the tree lined road, with a brown roof and anL-shaped shape", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<241><267><316><325>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_4500_11.5750_48.1661_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0106", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<429><82><472><195>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13500_11.5856_48.1896_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0107", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the crossroads, with a brown roof and an L-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<110><357><171><395>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_12100_11.5767_48.1318_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0108", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<299><70><341><118>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_12100_11.5957_48.1995_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0109", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads and has a blue andirregular rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<281><4><353><90>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_11700_11.5828_48.1335_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0110", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<271><148><298><183>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_12600_11.6095_48.1956_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0111", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the right side of the road, with a green roof and asquare shape", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<430><349><521><440>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_4500_11.5300_48.1671_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0112", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<525><288><542><323>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_10300_11.6158_48.2120_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0113", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper corner of the crossroads, there is a green L-shapedroof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0114", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<366><26><426><58>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28800_21600_11.6213_48.1305_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0115", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located beneath the road and has a grey and \"cross\" shaped roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<307><493><347><537>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8100_12600_116.2741_39.9347_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0116", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<78><240><130><297>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_12100_11.5975_48.1314_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0117", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper of the road, the first building counted from left toright, with a green roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<87><16><169><102>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_9900_27000_116.2920_39.8310_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0118", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<172><171><245><220>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_15700_11.6121_48.1148_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0119", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located below the road, with a gray white roof and an L-shapedshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<485><119><560><218>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_4900_116.4270_39.9926_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0120", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><510><28><553>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2200_4500_11.5388_48.1669_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0121", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located upper the straight road, with a white roof and a U-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><383><117><485>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_1300_11.5852_48.1802_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0122", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<123><506><181><566>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_4500_11.5421_48.1668_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0123", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper side of the gym, with a gary roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<485><28><600><65>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_10800_116.2907_39.9301_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0124", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<537><161><595><212>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_14800_11.5459_48.1204_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0125", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right of the crossroads, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<343><560><587><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_6700_116.4165_39.9844_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0126", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<153><314><198><370>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_6300_11.5478_48.1586_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0127", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a grey roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<277><294><340><310>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13500_9900_116.4196_39.9700_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0128", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<243><75><383><119>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_14800_11.5486_48.1203_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0129", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center corner of the entire image,with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<29><41><183><88>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_5400_116.4247_39.9903_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0130", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, with a yellow roof in the shape of a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<489><231><549><292>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_9000_11.5499_48.1464_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0131", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<160><282><219><304>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_7600_116.3510_39.9800_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0132", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<85><212><256><256>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_10300_11.5529_48.1405_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0133", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<550><81><599><148>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_5400_116.3561_39.9900_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0134", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<528><351><562><417>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_15300_11.5518_48.1180_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0135", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<15><424><63><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_5400_116.3585_39.9900_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0136", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<84><20><168><94>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_14800_11.5580_48.1201_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0137", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom side of the river, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><75><92>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_6300_116.4141_39.9862_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0138", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<165><173><221><225>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_6700_11.5685_48.1563_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0139", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><75><92>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_6300_116.4141_39.9862_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0140", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<201><374><249><419>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_6700_11.5745_48.1562_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0141", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<262><373><381><501>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_2200_11.5789_48.1763_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0142", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<221><220><276><290>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_15300_11.5787_48.1174_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0143", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<462><267><500><359>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_2200_11.5816_48.1763_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0144", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<451><50><482><92>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_8100_11.5803_48.1498_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0145", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<374><434><466><512>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_2700_11.5304_48.1752_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0146", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<353><87><494><168>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_15300_11.5847_48.1173_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0147", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a hipped_roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<125><209><175><280>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_4500_11.5871_48.1658_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0148", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<73><312><111><346>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_5800_11.5868_48.1600_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0149", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a red roof in the shape of a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<500><116><526><156>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_10300_27000_116.2958_39.8310_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0150", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<424><450><487><475>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_11700_17500_116.3082_39.8995_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0151", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<93><332><173><364>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_30600_18900_116.4851_39.8904_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0152", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in Beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<522><161><544><192>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8100_13000_116.2741_39.9318_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0153", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a green roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<560><89><576><106>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_4900_116.4246_39.9926_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0154", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a brown roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<388><456><493><498>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_9900_116.2983_39.9342_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0155", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in beside the road, there is a yellow roof in the shape of arectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<495><22><539><86>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_5400_116.3139_39.9546_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0156", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is situated at the lower right of the river channel, featuring a white roof and acircular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<233><582><295><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15300_19300_116.3420_39.8868_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0157", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right side of the road, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_5400_116.3273_39.9547_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<534><521><579><566>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_5400_116.3273_39.9547_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0158", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the road, with a brown and blue roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_10800_116.3299_39.9304_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<86><0><257><179>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_10800_116.3276_39.9303_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0159", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner in the picture, with a white roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_10800_116.3299_39.9304_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<9><0><108><27>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_10800_116.3299_39.9304_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0160", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right side of the gym, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_5800_116.3297_39.9529_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<117><257><255><420>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_5800_116.3297_39.9529_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0161", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right side of the road, with a brown roof and.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_1800_116.3324_39.9709_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<84><96><171><181>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_1800_116.3324_39.9709_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0162", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located in the right side of the road,with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_900_116.3324_39.9750_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<395><183><500><249>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_900_116.3324_39.9750_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0163", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture, with a white roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14400_9900_11.4707_48.2181_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><81><57><152>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14400_9900_11.4707_48.2181_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0164", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the picture, with a brown roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14800_9900_11.4750_48.2180_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<17><519><102><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14800_9900_11.4750_48.2180_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0165", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the picture, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15700_8500_11.4851_48.2278_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><335><53><410>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15700_8500_11.4851_48.2278_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0166", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the up side of the road, with a roof and a circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22900_13000_11.5610_48.1938_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<10><341><31><358>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22900_13000_11.5610_48.1938_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0167", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the left side of the picture, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23400_13000_11.5664_48.1937_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<546><253><600><340>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23400_13000_11.5664_48.1937_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0168", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the road, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_11700_11.5959_48.2023_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<544><89><596><122>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_11700_11.5959_48.2023_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0169", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a brown roof and ashape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_20700_11.5926_48.1376_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<576><360><600><405>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26100_20700_11.5926_48.1376_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0170", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right side of the road, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_9000_11.6162_48.2213_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<341><528><363><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27900_9000_11.6162_48.2213_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0171", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the picture, with a brown roof and.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_11700_1800_11.6032_48.1776_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<379><519><507><587>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_1800_11.6032_48.1776_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0172", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the crossroads, with a brown roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_13500_9400_11.6136_48.1432_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<262><148><301><180>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_9400_11.6136_48.1432_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0173", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the road, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_1800_4900_11.5360_48.1651_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<104><3><140><38>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_4900_11.5360_48.1651_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0174", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the left side of the picture, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_4000_14400_11.5487_48.1221_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<94><374><127><411>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_14400_11.5487_48.1221_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0175", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the picture, with a black roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_4900_4500_11.5569_48.1665_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<541><490><600><581>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_4500_11.5569_48.1665_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0176", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the crossroads, with a brown roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_5400_9400_11.5592_48.1444_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><153><42><200>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_9400_11.5592_48.1444_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0177", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the crossroads, with a brown roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_7200_12100_11.5706_48.1320_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<3><70><33><133>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_12100_11.5706_48.1320_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0178", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the left corner of the road, with a green color and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Munich_SV1-03_L2A0001092311_8100_15700_11.5759_48.1157_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><430><15><470>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_15700_11.5759_48.1157_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0179", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<397><366><423><392>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_15300_11.5726_48.1175_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0180", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<432><435><480><481>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_11700_11.5707_48.1338_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0181", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<564><576><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_6300_11.5659_48.1582_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0182", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<381><356><407><379>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_2700_11.5607_48.1745_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0183", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the sroad, with a black roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<202><558><284><587>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_9400_11.5471_48.1446_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0184", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<168><221><211><275>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3100_4500_11.5448_48.1667_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0185", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectanular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0186", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<475><580><495><597>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_15700_11.6208_48.1146_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0187", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<53><222><107><244>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_9000_11.6197_48.1448_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0188", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the crossroads, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><557><17><588>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_15300_11.6149_48.1166_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0189", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<247><444><262><459>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_1800_11.6059_48.1775_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0190", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire iimage , with a brown roofand a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<414><521><443><557>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_10800_15300_11.5941_48.1170_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0191", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a grey roof and asemi-circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><130><13><170>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_10300_11.6201_48.2119_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0192", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<516><41><574><73>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_11700_11.6099_48.2020_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0193", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<458><35><532><100>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_5800_116.3667_39.9882_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0194", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<72><7><96><50>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_5400_116.3690_39.9900_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0195", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right of the road, with a brown roof and a semi-circularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<563><355><600><425>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_1300_116.3718_40.0085_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0196", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the left side of the road, with a grey roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<392><259><434><278>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_2200_116.3718_40.0045_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0197", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper side of the road, with a grey roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<566><291><582><311>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5800_116.3720_39.9882_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0198", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<577><447><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_900_116.3718_40.0103_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0199", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a grey roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<199><284><279><317>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_5400_116.3743_39.9901_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0200", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left of the road, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<155><516><277><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_5800_116.3743_39.9883_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0201", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom side of the road, with a grey roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<550><424><577><438>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_900_116.3741_40.0103_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0202", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<472><108><523><136>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_4500_116.3901_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0203", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><70><51><115>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9400_4900_116.3953_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0204", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the image and has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<430><349><505><430>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_21100_6300_116.3954_39.9808_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0205", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image and has a brown roof in asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<462><57><525><161>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_24700_19300_116.4299_39.8872_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0206", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<556><1><599><36>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28800_14800_116.4680_39.9199_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0207", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the middle corner of the image and has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<207><279><235><306>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_29200_19800_116.4721_39.8838_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0208", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located in the upper left corner of the image,with a blue roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<13><289><90><376>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_1800_116.4034_40.0064_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0209", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located in the lower left corner of the image,with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<114><400><186><470>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_4000_116.4035_39.9965_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0210", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<60><165><144><257>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11200_1800_116.4058_40.0064_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0211", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<572><0><600><118>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_11700_116.4091_39.9619_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0212", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<31><106><130><153>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12100_4900_116.4112_39.9925_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0213", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a green roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<11><25><76><86>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_9000_116.4142_39.9740_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0214", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<349><160><539><200>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_4900_116.4164_39.9925_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0215", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a brown roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<504><68><591><104>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_7200_116.3480_39.9818_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0216", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle corner of the image, with a gray roof, L-shaped.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<156><147><325><274>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13900_10300_116.4219_39.9682_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0217", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a green roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<119><98><196><145>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_11700_116.4272_39.9619_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0218", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<466><35><600><182>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_7200_116.3509_39.9818_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0219", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a white roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<126><353><177><442>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_7200_116.3533_39.9818_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0220", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a red roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><67><40><91>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_11200_116.3564_39.9638_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0221", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the image, and it has a gray roof. .", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<11><34><242><82>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2700_5800_116.3561_39.9882_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0222", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a white roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<14><24><67><207>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_5800_116.3585_39.9882_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0223", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<545><54><599><94>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_1800_116.3665_40.0062_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0224", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<44><483><115><595>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4900_116.3667_39.9923_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0225", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner below the image, with a gray roof, square.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<314><425><437><473>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_1800_116.3689_40.0062_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0226", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<78><94><127><177>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_4900_116.3877_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0227", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<455><467><600><513>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_7600_116.3457_39.9800_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0228", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the image, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<53><195><86><283>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9900_6300_116.3983_39.9861_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0229", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the image, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<486><507><600><530>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_900_116.3347_39.9750_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0230", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<26><100><230><141>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11700_9400_116.3433_39.9367_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0231", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<28><498><106><584>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_1300_7600_116.2824_39.9445_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0232", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the lower right corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<404><549><475><591>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_11200_116.2931_39.9283_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0233", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<517><122><591><204>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_3100_116.2927_39.9648_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0234", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a gray roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<27><374><149><457>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_7600_116.2929_39.9445_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0235", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<471><65><550><131>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_900_116.3113_39.9748_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0236", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<31><19><68><83>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_9400_116.3117_39.9366_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0237", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<362><0><441><71>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_11200_116.3141_39.9285_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0238", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<34><506><150><542>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_12100_116.3142_39.9244_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0239", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, and it has a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<3><7><111><68>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_1300_116.3137_39.9731_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0240", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle right corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<433><212><507><287>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_900_116.3137_39.9749_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0241", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: TThe building is located in the lower right corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<410><527><492><585>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_9400_116.3140_39.9366_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0242", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0243", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the lower left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<93><549><124><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_29200_22000_11.6254_48.1275_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0244", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a ba-colored roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<8><428><63><469>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_15300_11.5968_48.1170_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0245", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<522><186><600><348>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_4500_11.5361_48.1669_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0246", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<235><429><267><487>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_14400_11.5460_48.1222_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0247", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<62><23><116><141>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_3600_6700_11.5477_48.1568_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0248", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper corner of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<314><0><422><60>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_6300_11.5505_48.1585_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0249", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a black roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<89><87><129><122>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_14400_11.5520_48.1220_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0250", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image, with a brown roof .", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<229><49><375><156>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_15700_11.5544_48.1161_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0251", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a brown roof .", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><69><32>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_4900_11.5602_48.1646_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0252", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<62><92><132><157>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_9000_11.5619_48.1461_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0253", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the middle of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<318><297><386><365>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_9000_11.5653_48.1460_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0254", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<194><269><252><327>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_12100_11.5673_48.1320_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0255", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a brown roof .", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<155><56><207><117>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_14400_11.5701_48.1216_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0256", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<150><460><195><540>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_4900_11.5723_48.1643_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0257", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<492><223><600><268>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_5800_11.5781_48.1601_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0258", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the image, with a brown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<193><45><241><91>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_5800_11.5808_48.1601_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0259", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<198><67><243><115>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_4900_11.5299_48.1653_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0260", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><499><42><595>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_6300_11.5867_48.1577_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0261", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the middle of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<322><205><388><222>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_11700_17100_116.3081_39.9024_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0262", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<90><43><135><68>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_30600_19300_116.4851_39.8875_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0263", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:The building is located in the upper left corner of the road,with a brown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12100_17500_116.3119_39.8996_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<25><374><85><394>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12100_17500_116.3119_39.8996_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0264", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<249><153><376><177>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_8500_13000_116.2779_39.9318_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0265", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a white roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_9900_27400_116.2921_39.8281_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<561><149><600><212>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_9900_27400_116.2921_39.8281_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0266", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<34><372><274><440>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_5400_116.3479_39.9899_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0267", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<585><249><600><318>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_5800_116.3479_39.9881_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0268", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<241><144><492><347>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_4500_116.4270_39.9944_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0269", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0270", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<385><445><495><545>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_5400_116.3532_39.9899_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0271", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle of the image, with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<320><336><406><399>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_1300_116.3665_40.0085_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0272", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<71><0><116><60>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_9900_116.3511_39.9697_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0273", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><465><111><486>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_31000_18900_116.4889_39.8904_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0274", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<84><569><119><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_6700_11.5866_48.1559_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0275", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<515><506><577><549>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_15700_11.5786_48.1156_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0276", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<342><510><451><549>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_13500_116.3353_39.9182_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0277", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the road, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<177><134><291><243>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_12100_9000_116.3456_39.9386_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0278", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the crossroads, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<177><317><241><386>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13500_5800_116.3537_39.9530_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0279", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<51><83><74><101>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_3100_116.2903_39.9648_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0280", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<295><219><431><256>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_6700_116.2928_39.9486_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0281", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<157><487><223><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_1800_116.2979_39.9707_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0282", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><96><24><221>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_9000_116.3035_39.9383_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0283", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><575><29><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_9400_116.3035_39.9365_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0284", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<502><37><536><56>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_11700_116.3065_39.9262_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0285", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<502><37><536><56>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5400_11700_116.3065_39.9262_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0286", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<58><508><167><597>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_5800_12100_116.3089_39.9244_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0287", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><482><19><572>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_15300_18900_116.3420_39.8897_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0288", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the map, with a green roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<11><488><38><549>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6300_116.3917_39.9807_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0289", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: On the right sideof the road, with a white roof, the longest house.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<537><531><559><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27000_12100_116.4510_39.9392_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0290", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection and has a gray roof andis rectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<458><62><557><85>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_28800_14400_116.4680_39.9227_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0291", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle, with a gray roof, rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<122><319><315><354>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_29200_20200_116.4721_39.8809_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0292", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a brown roof and asemi-circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<354><298><432><387>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_1300_116.4034_40.0087_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0293", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection and has a green roofwith a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<436><214><526><255>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_4900_116.4088_39.9925_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0294", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<530><5><598><45>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12100_11700_116.4114_39.9619_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0295", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located directly above the map and has a green roof and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<135><41><204><123>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_12600_4500_116.4141_39.9943_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0296", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection and has a green roof inthe shape of a pentagonal shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<296><276><367><364>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_4500_116.4164_39.9943_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0297", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the subway and has a green roof in a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<346><216><457><332>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_6300_116.4165_39.9862_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0298", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the map and has a green roof and asemicircular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<421><558><556><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_13000_9400_116.4166_39.9723_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0299", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the intersection and has a green roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><457><42><566>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1300_7600_116.3480_39.9800_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0300", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This building is located in the lower right corner of the map, with a green roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<10><123><146><184>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_3600_116.3508_39.9980_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0301", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map, with a green roof, rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><104><45>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_7600_116.3533_39.9800_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0302", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a brown roof and a semi-rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<494><0><600><23>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_10800_116.3587_39.9656_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0303", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map, with a green roof, rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><26><43><79>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3600_8100_116.3615_39.9778_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0304", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof,rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<543><77><595><147>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4000_8100_116.3639_39.9778_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0305", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the map, with a green roof, rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<120><355><158><401>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4500_116.3666_39.9941_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0306", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the map and has a green roof and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<12><189><69><321>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_2200_116.3689_40.0044_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0307", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<532><21><600><60>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_4900_116.3690_39.9923_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0308", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<54><523><95><568>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0309", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><38><32><112>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_7200_116.3457_39.9818_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0310", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<54><523><95><568>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0311", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<44><106><131><195>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_9000_116.3351_39.9385_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0312", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<45><26><89><49>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_13900_5400_116.3560_39.9548_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0313", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<553><11><600><50>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_7200_116.2905_39.9463_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0314", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<519><524><588><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_2700_116.2927_39.9666_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0315", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<518><476><552><512>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_6300_116.2928_39.9504_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0316", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<533><542><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_3100_116.2956_39.9648_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0317", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the map and has a green roof in arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<549><447><588><564>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_3100_116.2979_39.9649_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0318", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map and has a green roof in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<136><121><270><167>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_11200_116.3012_39.9284_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0319", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<2><458><42><561>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_6300_116.3010_39.9505_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0320", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><59><44><158>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_6700_116.3010_39.9487_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0321", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<150><101><314><214>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_9000_116.3011_39.9383_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0322", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<544><95><595><126>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_900_116.3008_39.9748_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0323", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map and has a green roof in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<559><71><591><122>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_9400_116.3012_39.9365_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0324", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the map, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<550><59><597><132>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_10800_116.3036_39.9302_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0325", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<578><50><600><81>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_11200_116.3036_39.9284_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0326", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<470><2><535><112>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_1300_116.3031_39.9730_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0327", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<507><29><562><109>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_3100_116.3032_39.9649_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0328", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<468><0><570><48>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_5800_116.3033_39.9527_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0329", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<500><91><600><132>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6300_116.3034_39.9505_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0330", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<555><26><596><89>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_20700_11.5969_48.1375_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0331", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<550><69><572><90>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_13000_11.6094_48.1927_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0332", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<543><66><591><102>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_29200_21600_11.6256_48.1304_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0333", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<565><77><600><163>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_11700_11.5976_48.1332_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0334", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<364><5><399><33>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_15700_11.5967_48.1152_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0335", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the intersection with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<534><5><592><79>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_11700_11.6097_48.1329_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0336", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, in the shapeof a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<514><5><546><40>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_15700_11.6148_48.1148_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0337", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, in the shapeof a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<464><39><514><106>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13900_9400_11.6162_48.1431_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0338", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, in the shapeof a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<552><2><582><25>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_15300_11.6182_48.1165_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0339", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, in the shapeof a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<553><101><594><137>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_15700_11.6182_48.1147_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0340", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the sitting corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<59><530><169><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_7600_11.6200_48.1511_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0341", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the sitting corner of the map, with a green roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<534><521><599><588>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14400_9400_11.6196_48.1430_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0342", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a green roof, in the shapeof a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<523><0><588><25>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_15300_11.6209_48.1164_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0343", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<41><12><63><23>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1800_11.5515_48.1787_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0344", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<3><35><40><76>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_9400_11.5498_48.1446_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0345", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<112><51><143><72>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5400_4500_11.5603_48.1664_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0346", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<30><9><77><41>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_4500_11.5663_48.1663_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0347", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><183><28><221>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_6700_11.5658_48.1564_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0348", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<125><4><221><68>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_11700_11.5674_48.1338_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0349", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<108><16><143><63>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_4500_11.5690_48.1662_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0350", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><33><33>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6700_6300_11.5686_48.1581_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0351", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><66><70><113>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_6300_11.5746_48.1580_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0352", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<53><27><99><72>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_8100_11.5742_48.1499_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0353", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<16><117><69><149>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_1800_11.5790_48.1781_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0354", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<73><65><123><130>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_5400_11.5782_48.1619_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0355", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left of the map, with a green roof, and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><48><38>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_5400_11.5809_48.1619_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0356", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the map, with a yellow roof, and is rectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<535><0><594><54>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_8500_11.5802_48.1480_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0357", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the map, with a yellow roof, and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<473><35><544><110>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_900_3100_11.5303_48.1734_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0358", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left side of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><81><8>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_10800_116.3118_39.9302_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0359", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<23><131><158><228>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_11200_116.3118_39.9284_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0360", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<524><465><544><599>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_11700_116.3118_39.9262_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0361", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the crossroads, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<377><570><502><595>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_9000_116.3117_39.9384_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0362", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><540><112><577>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_900_116.3219_39.9749_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0363", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the crossroads, with a brown roof and asemi-circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<156><381><188><393>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_11200_116.3276_39.9285_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0364", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the road, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<409><242><454><253>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_900_7600_116.2800_39.9445_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0365", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><564><6><586>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9400_11200_116.3299_39.9285_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0366", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0367", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<299><319><347><396>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_13000_21100_11.4517_48.1378_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0368", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<391><422><409><456>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_14400_10300_11.4705_48.2152_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0369", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located to the left of the playground and has a white, rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<301><290><315><322>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_13000_12600_116.3200_39.9349_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0370", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the intersection, and the roof is greenand rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<216><488><257><521>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_26500_18000_116.4467_39.8967_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0371", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the road and has a brown, rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<128><374><173><422>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_27400_16600_116.4550_39.9068_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0372", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the topleft corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: The building is located in the bottom left corner of the imageand has a green, rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<4><568><24><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10300_6300_116.4007_39.9861_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0373", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of the picture. There is a road above it andthe roof is brown .", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><134><49><198>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_11700_4500_116.4088_39.9943_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0374", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. Its roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<323><566><509><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_3100_11200_116.3587_39.9638_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0375", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower left of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<97><505><234><539>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9000_4900_116.3930_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0376", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower left of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<140><371><168><418>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_9900_11700_116.3985_39.9618_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0377", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This building is located at the lower right corner of the entire image. There is a playgroundon its left.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<565><489><595><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_1800_116.2955_39.9707_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0378", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<91><563><114><585>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13900_11.5854_48.1867_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0379", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located directly below the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<31><283><172><393>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_26500_12100_11.6000_48.1994_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0380", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the picture. The roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><25><241><417>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27400_12100_11.6097_48.1992_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0381", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower left of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<21><408><88><490>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28800_22000_11.6211_48.1276_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0382", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<486><8><576><73>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_2200_11.6031_48.1758_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0383", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the lower right corner of the picture. The roof isbrown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<510><466><563><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_14800_7200_11.6228_48.1528_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0384", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located at the lower right of the picture. The roof is brownand rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<441><552><463><593>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_900_11.5853_48.1820_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0385", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower right of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<494><337><597><473>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9400_1300_11.5879_48.1802_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0386", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<453><585><469><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_31000_19300_116.4889_39.8875_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0387", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<394><584><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_5800_116.3532_39.9881_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0388", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the up side of the road, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_10300_116.3534_39.9679_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0389", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the picture, with a white roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<128><301><165><336>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_14800_11.5546_48.1202_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0390", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the bottom left of the road and is a flat topped rectangularstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<130><342><168><396>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_5800_2700_11.5634_48.1744_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0391", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the upper right side of the road, with a white roof and atrapezoidal shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<495><344><538><390>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7200_8100_11.5715_48.1499_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0392", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the picture, on the left side of the road, with a white roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<330><538><371><599>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_7600_3600_11.5752_48.1701_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0393", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the picture, with an orange roof and a C-shaped shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<288><301><427><422>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_15300_11.5760_48.1175_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0394", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the bottom right of the picture, and to its left is a road in theshape of a rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<556><453><600><581>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_1800_11.5817_48.1781_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0395", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the picture, with a road to its left. It is a flat toppedbuilding with a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<145><305><354><368>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_10300_27400_116.2958_39.8281_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0396", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located at the lower left of the picture and has a white and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<107><463><133><529>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_9000_116.3902_39.9739_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0397", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<373><428><451><448>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12100_17100_116.3119_39.9025_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0398", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the road and has a white and square roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<90><301><131><346>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_3600_116.3666_39.9981_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0399", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road and has a white roof with a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<372><250><412><309>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_4500_116.4246_39.9944_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0400", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<542><453><600><493>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_900_116.3665_40.0103_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0401", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<479><32><551><77>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_3600_116.3689_39.9981_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0402", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located in the lower right corner of theintersection, with a gray white roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<142><456><293><496>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_900_116.3688_40.0103_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0403", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the road, with a graygreen roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<98><191><116><257>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_9000_116.3879_39.9739_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0404", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the parking lot andhas an irregularly shaped gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<197><224><274><287>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_5800_116.3379_39.9529_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0405", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located on the right side of the picture. It is the largestbuilding in the picture and has a white and rectangular roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<465><327><600><503>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_2200_116.3377_39.9691_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0406", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<490><487><578><523>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_2200_116.3401_39.9692_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0407", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the playground, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<316><154><354><227>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_1800_5400_116.3509_39.9899_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0408", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower right corner of the straight road, with a white roof andan L-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<254><556><287><584>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_9900_116.3534_39.9697_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0409", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the crossroads, with a blue roof and anL-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<91><62><128><112>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7200_4500_116.3824_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0410", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located upper the farmland, with a white roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<407><414><521><455>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8100_9400_116.3879_39.9721_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0411", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the upper right side of the road, and its roof is in the shape of awhite rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<140><55><297><94>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_1300_116.3688_40.0085_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0412", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the T-shaped road, with a white roof anda square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<424><400><460><435>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_5800_116.3456_39.9881_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0413", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located to the left of a playground, has a green roof and is rectangular inshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<360><0><382><93>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_9400_116.3903_39.9721_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0414", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the right side of the playground. It has a white roof and isrectangular in shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<442><223><549><250>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4900_4000_116.3690_39.9963_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0415", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of a farmland. It has a white roof and isrectangular in shape. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><11><33>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7600_4500_116.3848_39.9942_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0416", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located to the left of a grey factory building, has a grey roof and is in theshape of a slender rectangle.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<17><89><45><422>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_11200_1800_116.3400_39.9710_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0417", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the lower right corner of the parking lot, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<448><362><475><382>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_9400_116.2906_39.9364_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0418", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: This building is the first one on the right side of the expressway. It has a grey roof and isin the shape of an irregular polygon.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<22><362><169><431>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_10300_116.2983_39.9324_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0419", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the road, with an orange roof and a T-shapedstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<17><204><140><278>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_3100_116.3348_39.9651_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0420", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the image with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><55><48><86>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_5400_116.3379_39.9547_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0421", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located above the picture and has a grey and rectangularroof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<178><59><379><93>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3600_10300_116.2959_39.9324_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0422", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the road, with a green roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_5400_116.3115_39.9546_RGB.tif", + "L1-task": "Pedosphere", + "Ground Truth": "{<444><549><486><572>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_5400_116.3115_39.9546_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0423", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is brownish grayand rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<475><76><600><117>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_9000_116.2930_39.9382_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0424", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<122><1><182><18>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_3100_9400_116.2930_39.9364_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0425", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<154><116><164><140>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_9000_116.2906_39.9382_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0426", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<57><59><74><70>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10800_1800_116.3377_39.9709_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0427", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<281><117><312><130>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7600_4900_116.3848_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0428", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<86><383><105><410>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_7200_4900_116.3825_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0429", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<132><0><168><16>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_4000_116.3666_39.9963_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0430", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<42><0><92><20>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_15300_8500_11.4808_48.2279_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0431", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><20><20><124>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_18400_21600_11.5096_48.1330_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0432", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda semi-circular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<349><583><405><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_22500_12600_11.5568_48.1967_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0433", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><403><50><493>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_23800_12600_11.5708_48.1964_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0434", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><515><24><596>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13500_11.5899_48.1895_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0435", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0436", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the right side of the road in the left side of the picture, with abrown roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<110><315><127><358>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7600_9900_116.3193_39.9343_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0437", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located at the bottom of the picture, with a gray roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<120><458><151><592>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_7600_10300_116.3193_39.9325_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0438", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located below the parking lot, with a brown roof and a concave shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<50><517><184><558>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_2200_116.3219_39.9690_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0439", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><509><29><540>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1800_116.3219_39.9708_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0440", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the middle of the image with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<282><154><425><378>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1800_116.3242_39.9709_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0441", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is white and greyand rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<403><506><486><599>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_12600_11.5762_48.1963_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0442", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the road and has a white roof with a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<299><296><371><337>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_24300_13000_11.5761_48.1934_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0443", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom of the picture, with a brown and black roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<94><471><314><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_12600_11.5859_48.1961_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0444", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the image with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<551><558><562><592>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25200_13000_11.5857_48.1932_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0445", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the open space in the square, with a black greenroof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><236><110><417>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_12600_11.5902_48.1960_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0446", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<399><30><516><153>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_25600_13000_11.5900_48.1931_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0447", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the picture and has a flat roof. It has a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<300><128><397><179>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_30600_13000_11.6438_48.1919_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0448", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<265><202><303><241>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_31000_12600_11.6483_48.1947_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0449", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom of the picture, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<282><554><301><596>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_16200_11.5966_48.1129_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0450", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the picture, with a brown roof and asquare shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><530><28><550>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_2200_116.3243_39.9691_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0451", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper right corner of the image with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<535><35><552><57>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_1300_11.6033_48.1798_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0452", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located upper the intersection, with a green roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<452><228><475><490>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_9400_11.6015_48.1434_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0453", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the picture. The roof is brown and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<521><464><574><511>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12600_6300_11.6082_48.1572_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0454", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the center of the entire image, with a brown roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<60><83><95><120>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_1300_11.6060_48.1798_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0455", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the elevated bridge, with a white roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<49><321><129><391>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13000_6700_11.6108_48.1554_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0456", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the playground, with a white roof and a U-shapedstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<133><502><284><577>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_5800_116.3139_39.9528_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0457", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located to the left of a row of rectangular buildings with a gray roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<261><238><322><456>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11200_16600_11.5965_48.1111_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0458", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is on the right side of the road and has a green roof. Its shape is flower-like.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<287><302><385><408>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_1800_11.5575_48.1786_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0459", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:=The building is on the right side of the crossroads. It has a green roof and its shape istriangular. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<106><528><265><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8500_16200_11.5785_48.1134_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0460", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the left side of the road, with a green roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><158><156><259>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1800_3100_11.5364_48.1732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0461", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the image with a gray roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><528><34><548>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1300_116.3348_39.9732_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0462", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the right side of the road. Its roof is flat and green, and itsshape is three-pronged. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<325><70><408><156>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6300_1300_116.3113_39.9730_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0463", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the image with a white roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<524><123><541><140>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2200_14400_11.5366_48.1224_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0464", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the highway, with a green roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<409><443><536><475>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_2700_116.2979_39.9667_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0465", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is ontop of a group of trees and has a roof. Its shape is circular. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<226><55><327><131>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5400_116.3719_39.9900_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0466", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower left corner of the picture, with a flat grey roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<71><430><117><475>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_900_11.6034_48.1816_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0467", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the lower right side of the road, with a herringbone roof and a rowof cars parked below it.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<327><415><359><445>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_6300_11.6143_48.1571_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0468", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the right side of the park's tree lined road, with a gray whitedance.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<554><566><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1300_11.5516_48.1810_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0469", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the left side of the highway, with a brown roof and an L-shapedshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<33><369><92><458>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_11200_11.5648_48.1362_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0470", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the lower right corner of the intersection and has a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<406><433><482><480>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6700_19800_116.2616_39.8827_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0471", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located beneath the pool, with a green roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<588><364><600><383>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14400_11.5641_48.1218_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0472", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located upper the crossroads, with a white roof and a square shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<449><17><509><78>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_3600_116.4035_39.9983_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0473", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the straight intersection, with a white roof and aU-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<334><538><401><599>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_10800_116.3012_39.9302_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0474", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom right corner of the entire image, with a brown roof anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<390><342><440><417>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_2200_11.5574_48.1768_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0475", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the bottom left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<218><484><258><524>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14800_11.5640_48.1200_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0476", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is white and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<456><0><562><60>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_16600_11.5757_48.1116_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0477", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located beneath the road. Its roof is grey and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<165><333><272><362>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1300_116.3219_39.9731_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0478", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the road and has a flat roof with a gray color anda rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<290><529><319><598>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12600_13000_116.3163_39.9320_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0479", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the picture. The roof is brownish red and rectangular.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<367><163><506><211>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6700_116.3034_39.9487_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0480", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<492><429><530><453>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1300_116.3242_39.9731_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0481", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<551><28><600><59>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5800_116.3010_39.9527_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0482", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><7><11><31>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_10800_116.3903_39.9658_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0483", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper right corner of the entire image, with a brown roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<527><153><600><258>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6700_116.3917_39.9779_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0484", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located right in the middle of the picture. It has a blackroof and is in the shape of a rectangle. It is the largest in area in theentire picture.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<7><205><490><523>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_9900_11.5557_48.1422_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0485", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located in the top left corner of the picture. Theroof is white and rectangular.", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Ground Truth": "{<0><0><59><14>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9900_13500_116.3329_39.9182_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0486", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of this picture, and it is the smallest building in that area,with a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<37><42><49><55>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9000_11.6205_48.2212_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0487", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located at the top of the image, with a semicircular roof thatis white in color.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<230><0><497><72>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9400_11.6204_48.2183_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0488", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the X-shaped road andis the smallest building.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<88><423><102><435>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_4500_11.5542_48.1665_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0489", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the upper left corner of the crossroads, with awhite roof and a triangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<26><0><96><12>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_15700_11.5819_48.1155_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0490", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the picture and is thesmallest flat roofed house in the surrounding area.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<524><0><555><25>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_12600_21100_11.4475_48.1379_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0491", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:The building is located on the right side of the picture, upperthe four white circles.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<508><277><525><291>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_28300_9900_11.6202_48.2148_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0492", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max).Description:This building is located in the upper right area of the pictureand is the smallest building. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<581><45><599><66>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_1300_3100_11.5330_48.1733_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0493", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building witha flat roof is located at the bottom of the picture and is also the firsthouse on the left side of the intersection.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<303><531><342><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4500_4900_11.5541_48.1647_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0494", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located between two rivers and has a green roof and atrapezoidal shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<274><0><433><113>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_9000_12100_11.5827_48.1317_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0495", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the picture. It is thelongest one and has a flat roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<1><44><143><135>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_12100_2200_11.6058_48.1757_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0496", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom and in the middle of the picture, and its color is pink.It is a small triangle with the smallest area. ", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<278><583><310><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_2700_4900_11.5420_48.1650_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0497", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located on the upper side of the bushes and to the right of the white open space. It has a grey roof and a U-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<308><212><374><289>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_GF2_L1A0000926980-MSS2_27000_13000_11.6051_48.1928_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0498", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the upper side of the playground, with a brown roof and a U-shapedstructure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<216><469><359><542>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_9000_5800_116.3273_39.9529_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0499", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the straight road, with a white roof and anL-shaped structure.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<173><48><306><299>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5800_1300_116.3741_40.0085_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0500", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the playground, with a white roof and arectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><174><34><315>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14800_5400_116.4270_39.9903_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0501", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located in the upper left corner of the playground, with a gray roof and acircular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<73><67><95><88>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_2700_7600_116.2905_39.9445_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0502", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the highway and has a rectangular white roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<572><41><600><75>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_4500_2200_116.3665_40.0044_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0503", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the highway and has the largest semi-circularwhite roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<0><0><397><524>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_4900_116.3901_39.9924_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0504", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located below the highway, with a white roof and a rectangular shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<83><280><263><391>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_5800_116.4247_39.9885_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0505", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located above the parking lot and has the longest rectangular green roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<41><103><80><319>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_14400_12100_116.4249_39.9601_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0506", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located below the intersection and has a triangular white roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<451><580><499><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_16200_14800_116.3501_39.9193_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0507", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the left side of the road and has a very long rectangular reddishbrown roof.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<197><74><276><111>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_10300_1800_116.3348_39.9709_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0508", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The building is located on the right side of the road, with a blue roof and a rectangularshape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<107><299><159><436>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_2200_3600_116.3531_39.9980_RGB.tif" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding/0509", + "Question_type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box of the object in the format (xmin, ymin, xmax, ymax), where the top-left corneris (x_min, y_min) and the bottom right corner is (x_max, y_max). Description:The building is located in the lower right corner of the picture, with abrownish green roof and a trapezoidal shape.", + "L2-task": "Urban Development", + "L3-task": "Perception", + "L4-task": "Visual grounding", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Ground Truth": "{<561><567><600><600>}", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_900_5400_116.3456_39.9899_RGB.tif" + ], + "Question Type": "Visual Grounding" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Reasoning/Counting_under_complex_conditions.json b/jsons/Pedosphere/Urban_Development/Reasoning/Counting_under_complex_conditions.json new file mode 100644 index 0000000000000000000000000000000000000000..38cb1caf0de275747d9d018db4236d3869d9ff6e --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Reasoning/Counting_under_complex_conditions.json @@ -0,0 +1,16590 @@ +[ + { + "Question_id": "Counting under complex conditions/0", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2100.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/1", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2101.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/2", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2168.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/3", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_217.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/4", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2246.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/5", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2568.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/6", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2642.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/7", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 45 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_705.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/8", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_765.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/9", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_809.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/10", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_377.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/11", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_446.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/12", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2151.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/13", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2071.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/14", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2170.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/15", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 35 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2215.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/16", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 38 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2292.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/17", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2323.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/18", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2611.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/19", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 38 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_706.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/20", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 45 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_753.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/21", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_815.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/22", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/23", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2198.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/24", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2300.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/25", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2587.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/26", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_704.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/27", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 21", + "(B) 22", + "(C) 23", + "(D) 24", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_750.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/28", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_811.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/29", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_990.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/30", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_396.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/31", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_511.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/32", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2072.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/33", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 4", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2203.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/34", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_778.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/35", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_988.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/36", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 1", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_378.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/37", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_507.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/38", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_513.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/39", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_523.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/40", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_565.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/41", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_598.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/42", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_996.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/43", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of below 18 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_380.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/44", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_504.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/45", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_570.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/46", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_601.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/47", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_604.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/48", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_531.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/49", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_550.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/50", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_528.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/51", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1214.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/52", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1950.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/53", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_218.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/54", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 30", + "(B) 31", + "(C) 32", + "(D) 33", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2286.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/55", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2365.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/56", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 18", + "(B) 19", + "(C) 20", + "(D) 21", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2612.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/57", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_717.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/58", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_819.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/59", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1040.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/60", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 14", + "(B) 15", + "(C) 16", + "(D) 17", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_503.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/61", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2167.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/62", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2257.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/63", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 20 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2614.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/64", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 60 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 3", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_814.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/65", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_789.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/66", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2113.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/67", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2634.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/68", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_703.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/69", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_728.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/70", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_740.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/71", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_777.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/72", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2395.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/73", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2332.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/74", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2251.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/75", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2210.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/76", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 60 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2186.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/77", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2162.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/78", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2150.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/79", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2096.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/80", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2087.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/81", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_121.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/82", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_125.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/83", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 32 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_134.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/84", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_146.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/85", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_156.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/86", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 7", + "(B) 8", + "(C) 9", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_174.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/87", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 33 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_175.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/88", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 4", + "(B) 5", + "(C) 6", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_178.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/89", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_196.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/90", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 12", + "(B) 13", + "(C) 14", + "(D) 15", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_210.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/91", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_26.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/92", + "Question_Type": "Single Choice", + "Text": "How many buildings have their heights exceeding 22 meters but fallingshort of 24 meters in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_107.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/93", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_104.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/94", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 14", + "(C) 13", + "(D) 12", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_136.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/95", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_193.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/96", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 57 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_37.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/97", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 57 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1075.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/98", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1202.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/99", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 57 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1296.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/100", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 54 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1328.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/101", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 38 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1439.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/102", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 5", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_122.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/103", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_126.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/104", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_127.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/105", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_128.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/106", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 18", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1152.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/107", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 16 ", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1305.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/108", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1316.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/109", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1321.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/110", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1325.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/111", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 7", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1341.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/112", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_106.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/113", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_181.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/114", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_20.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/115", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_39.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/116", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_42.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/117", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 8", + "(B) 9", + "(C) 10", + "(D) 11", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1006.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/118", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1133.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/119", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1163.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/120", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1187.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/121", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 25", + "(B) 26", + "(C) 27", + "(D) 28", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1203.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/122", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1235.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/123", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1297.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/124", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 55 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_41.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/125", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_211.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/126", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 22 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_45.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/127", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_96.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/128", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 35 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1050.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/129", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1063.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/130", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1095.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/131", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1121.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/132", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 8", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_646.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/133", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 55 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1151.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/134", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1159.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/135", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_648.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/136", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_651.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/137", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1160.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/138", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_654.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/139", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 26", + "(B) 27", + "(C) 27", + "(D) 29", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_36.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/140", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_671.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/141", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_40.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/142", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_681.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/143", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_79.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/144", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_682.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/145", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_95.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/146", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_683.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/147", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1117.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/148", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_685.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/149", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 3", + "(B) 4", + "(C) 5", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1201.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/150", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_686.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/151", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1294.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/152", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_687.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/153", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1310.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/154", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 20", + "(B) 21", + "(C) 22", + "(D) 23", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_690.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/155", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1326.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/156", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_704.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/157", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1389.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/158", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_706.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/159", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1493.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/160", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_708.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/161", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 20", + "(B) 14", + "(C) 21", + "(D) 39", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2046.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/162", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_710.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/163", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2051.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/164", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 52 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_712.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/165", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 45 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2052.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/166", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 2", + "(C) 4", + "(D) 6", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_717.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/167", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 20", + "(B) 10", + "(C) 9", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2068.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/168", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_721.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/169", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 56 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2070.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/170", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_723.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/171", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 5", + "(C) 6", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1336.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/172", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_742.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/173", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1537.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/174", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 8", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1603.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/175", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1633.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/176", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1634.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/177", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1635.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/178", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1636.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/179", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 14", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1638.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/180", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1645.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/181", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 6", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1647.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/182", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 22", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1648.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/183", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1569.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/184", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1618.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/185", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1639.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/186", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1971.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/187", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 32 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2020.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/188", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2023.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/189", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2037.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/190", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1977.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/191", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2022.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/192", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 7", + "(C) 8", + "(D) 9", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1697.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/193", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1823.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/194", + "Question_Type": "Single Choice", + "Text": "How many 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"raw/Pedosphere/BHbuilding/images/beijing_1941.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/196", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 51 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1952.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/197", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 58 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1978.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/198", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1815.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/199", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1708.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/200", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 1", + "(B) 2", + "(C) 3", + "(D) 4", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1660.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/201", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1298.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/202", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1304.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/203", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1320.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/204", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 2", + "(B) 3", + "(C) 4", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1324.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/205", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1343.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/206", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1441.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/207", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1528.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/208", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1545.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/209", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1552.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/210", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1562.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/211", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1586.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/212", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 10", + "(B) 11", + "(C) 12", + "(D) 13", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1631.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/213", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1637.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/214", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1643.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/215", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1672.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/216", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 5", + "(B) 6", + "(C) 7", + "(D) 8", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1721.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/217", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1798.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/218", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 25 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 15", + "(B) 16", + "(C) 17", + "(D) 18", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1848.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/219", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 37 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1653.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/220", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1667.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/221", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1669.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/222", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 42 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1670.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/223", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1684.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/224", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 37 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1685.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/225", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1716.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/226", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1788.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/227", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1802.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/228", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 36 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1803.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/229", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1847.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/230", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 24 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1855.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/231", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 25 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1901.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/232", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 6", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1601.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/233", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1593.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/234", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1592.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/235", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1585.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/236", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 35 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1560.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/237", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1557.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/238", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1546.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/239", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1544.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/240", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1542.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/241", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1539.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/242", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 22 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1536.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/243", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 40 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1506.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/244", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1486.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/245", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1447.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/246", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1437.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/247", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 45 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1400.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/248", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 48 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1342.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/249", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 45 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1339.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/250", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 50 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1334.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/251", + "Question_Type": "Single Choice", + "Text": "How many buildings with a height of over 30 meters are there in the entire picture?", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Answer Choices": [ + "(A) 0", + "(B) 1", + "(C) 2", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_605.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/252", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? 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", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_6700_5800_116.3139_39.9528_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/727", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? 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", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4900_1800_11.5575_48.1786_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/729", + "Question_type": "Single Choice", + "Text": "How many office are there in the whole picture? 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", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4000_2700_116.2979_39.9667_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/736", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 14", + "(B) 13", + "(C) 12", + "(D) 10", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_5400_5400_116.3719_39.9900_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/737", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_11700_900_11.6034_48.1816_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/738", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_13500_6300_11.6143_48.1571_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/739", + "Question_type": "Single Choice", + "Text": "How many office are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_4000_1300_11.5516_48.1810_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/740", + "Question_type": "Single Choice", + "Text": "How many hotel are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 5", + "(B) 4", + "(C) 3", + "(D) 2", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_11200_11.5648_48.1362_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/741", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_6700_19800_116.2616_39.8827_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/742", + "Question_type": "Single Choice", + "Text": "How many other are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14400_11.5641_48.1218_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/743", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_10800_3600_116.4035_39.9983_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/744", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 10", + "(B) 9", + "(C) 8", + "(D) 7", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_10800_116.3012_39.9302_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/745", + "Question_type": "Single Choice", + "Text": "How many industrial other are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_6300_14800_11.5640_48.1200_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/746", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Munich_SV1-03_L2A0001092311_8100_16600_11.5757_48.1116_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/747", + "Question_type": "Single Choice", + "Text": "How many public are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8100_1300_116.3219_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/748", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 5", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_12600_13000_116.3163_39.9320_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/749", + "Question_type": "Single Choice", + "Text": "How many residential are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4900_6700_116.3034_39.9487_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/750", + "Question_type": "Single Choice", + "Text": "How many administration are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_8500_1300_116.3242_39.9731_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/751", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092309_4500_5800_116.3010_39.9527_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/752", + "Question_type": "Single Choice", + "Text": "How many education are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 6", + "(B) 5", + "(C) 4", + "(D) 3", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_SV1-02_L2A0001092307_8500_10800_116.3903_39.9658_RGB.tif" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Counting under complex conditions/753", + "Question_type": "Single Choice", + "Text": "How many office are there in the whole picture? ", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Counting under complex conditions", + "Dataset": "UBCv1", + "L1-task": "Pedosphere", + "Answer Choices": [ + "(A) 4", + "(B) 3", + "(C) 2", + "(D) 1", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/UBCv1/images/Beijing_GF2_L1A0004822322-MSS1_20700_6700_116.3917_39.9779_RGB.tif" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Reasoning/Individual_building_height_estimation.json b/jsons/Pedosphere/Urban_Development/Reasoning/Individual_building_height_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..dc449595c8d1b10a0da81ea71fba3a4effab1d43 --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Reasoning/Individual_building_height_estimation.json @@ -0,0 +1,2931 @@ +[ + { + "Question_id": "Individual building height estimation/0000", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<183><22><191><34>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a height of36-42 meters, 17 with a height of 18-24 meters, 10 with a height of 48-54meters, and other buildings with a height below 18 meters .", + "Step 2: Boundary Box 2 is located in the upper right corner of the image.", + "Step 3: The color of bounding box 2 is blue.", + "Step 4: The height corresponding to this color is less than 18 meters.", + "Step 5: Boundary Box 2 is below 18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) Below 18 meters", + "(B) 18-24", + "(C) 24-30", + "(D) 30-36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_224.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0001", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<204><7><219><22>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with one buildingexceeding 36 meters in height, 10 buildings ranging from 12 to 24 meters inheight, and others less than 20 meters in height.", + "Step 2: Bounding box -[<204><7><219><22>] is located in the upper right corner of the pictureand is a square building.", + "Step 3: The color of Bounding Box -[<204><7><219><22>] is yellow.", + "Step 4: The height corresponding to this color is 36-48 meters.", + "Step 5: Bounding box -[<204><7><219><22>] is 36-48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 36-48", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2168.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0002", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<28><193><54><214>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 3 buildingsexceeding 54 meters in height, 1 building about 24 meters in height, and otherbuildings below 18 meters in height.", + "Step 2: Bounding box -[<28><193><54><214>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<28><193><54><214>] is red.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<28><193><54><214>] is over 54 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 54 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_228.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0003", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<239><125><256><131>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Among them, one isover 50 meters high, six are about 48 to 50 meters high, four are about 24 to40 meters high, and some are less than 24 meters high.", + "Step 2: Bounding box -[<239><125><256><131>] is located on the far right of the image. It is arectangular building and there is no building above it. There is a building alittle smaller than it beside it.", + "Step 3: The color of Bounding Box -[<239><125><256><131>] is green.", + "Step 4: The height corresponding to this color is greater than 30 meters.", + "Step 5: Bounding box -[<239><125><256><131>] is over 31 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_217.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0004", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<22><0><49><13>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, 2 of which are about 30meters high, 7 of which are less than 18 meters high, and the remainingbuildings are over 60 meters high.", + "Step 2: Bounding box -[<22><0><49><13>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<22><0><49><13>] is red.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<22><0><49><13>] is over 60 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_346.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0005", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<40><246><55><256>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Four of them are over48 meters high, another one is about 24 to 36 meters high, and the rest areless than 24 meters high.", + "Step 2: Bounding box -[<40><246><55><256>] is located at the lower left corner of the image. Itis similar to a building in the shape of a triangle. There is no building onits left, but there is one above it.", + "Step 3: The color of Bounding Box -[<40><246><55><256>] is deep red.", + "Step 4: The height corresponding to this color is greater than 50 meters.", + "Step 5: Bounding box -[<40><246><55><256>] is over 52 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 50 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2246.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0006", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<144><0><187><26>]", + "CoT": [ + "Step 1: There are about 100 buildings in the picture. Only about 20 buildingsare taller than 12 meters and shorter than 24 meters, and the remainingbuildings are all below 12 meters.", + "Step 2: Bounding box -[<144><0><187><26>] is located in the upper right of the picture and isthe largest hollow building in the image. The height of this building isapproximately 12 meters.", + "Step 3: The color of Bounding Box -[<144><0><187><26>] is blue.", + "Step 4: The height corresponding to this color is below 12 meters.", + "Step 5: Bounding box -[<144><0><187><26>] is below 12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-18", + "(B) 18-24", + "(C) 24-30", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_199.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0007", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<153><234><197><244>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Two of them are about24 to 36 meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<153><234><197><244>] is located in the bottom right corner of the image,and its shape resembles a key. To its left is a building of the same height asit.", + "Step 3: The color of Bounding Box -[<153><234><197><244>] is green.", + "Step 4: The height corresponding to this color is greater than 25 meters.", + "Step 5: Bounding box -[<153><234><197><244>] is over 26 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-36", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2568.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0008", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<244><1><252><22>]", + "CoT": [ + "Step 1: There are ten to twenty buildings in the picture, seven with aheight of 48 to 60 meters, three with a height of approximately 18 meters, andothers with a height about 0 to 12 meters.", + "Step 2: Bounding box -[<244><1><252><22>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<244><1><252><22>] is blue.", + "Step 4: The height corresponding to this color is 0 to 12 meters.", + "Step 5: Bounding box -[<244><1><252><22>] is 0 to 12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 18-24", + "(C) 24-30", + "(D) 30-36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_489.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0009", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<166><253><169><256>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Two of them are over48 meters high, another one is about 36 to 40 meters high, one is about 30meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<166><253><169><256>] is located in the lower right corner of the image, andits shape is similar to a triangle shape with no buildings around it.", + "Step 3: The color of Bounding Box -[<166><253><169><256>] is green.", + "Step 4: The height corresponding to this color is greater than 24 meters.", + "Step 5: Bounding box -[<166><253><169><256>] is over 30 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-36", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2642.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0010", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<15><0><31><4>]", + "CoT": [ + "Step 1: There are about a hundred buildings in the picture, with threebuildings measuring about 60 meters in height, one building measuring about 37meters in height, one building measuring about 30 meters in height, and onebuilding measuring about 24 meters in height. The remaining dozens ofbuildings are less than 18 meters in height.", + "Step 2: Bounding box -[<15><0><31><4>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<15><0><31><4>] is red.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<15><0><31><4>] is over 60 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_542.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0011", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<239><225><256><240>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. One is over 50 metershigh, the other four are about 36 to 42 meters high, and the rest are lessthan 18 meters high.", + "Step 2: Bounding box -[<239><225><256><240>] is located in the bottom right corner of the image,with no buildings around it and a shorter building above it.", + "Step 3: The color of Bounding Box -[<239><225><256><240>] is dark red.", + "Step 4: The height corresponding to this color is greater than 50 meters.", + "Step 5: Bounding box -[<239><225><256><240>] is over 53 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 50 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_705.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0012", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<0><13><14><23>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 7 buildingsexceeding 54 meters in height, 1 building ranging from 24 to 36 meters inheight, 6 buildings around 24 meters in height, and the remaining buildingsbelow 18 meters in height.", + "Step 2: Bounding box -[<0><13><14><23>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<0><13><14><23>] is red.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<0><13><14><23>] is over 54 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 54 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_270.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0013", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<0><20><12><31>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 6 buildingsmeasuring 48-60 meters in height, 2 buildings measuring 36-48 meters inheight, 6 buildings measuring approximately 30 meters in height, and otherbuildings measuring less than 24 meters in height.", + "Step 2: Boundary Box 2 is located in the upper left corner of the image.", + "Step 3: The color of bounding box 2 is red.", + "Step 4: The height corresponding to this color is 48-60 meters.", + "Step 5: Boundary Box 2 is approximately 50 meters long." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-24", + "(B) 24-36", + "(C) 36-48", + "(D) 48-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_111.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0014", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<90><39><105><57>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a height ofover 50 meters, two with a height of about 36 to 48 meters, and the rest witha height of less than 18 meters.", + "Step 2: Bounding box -[<90><39><105><57>] is located in the upper left corner of the image, witha rectangular shape and a road below it.", + "Step 3: The color of Bounding Box -[<90><39><105><57>] is faint yellow.", + "Step 4: The height corresponding to this color is greater than 36 meters.", + "Step 5: Bounding box -[<90><39><105><57>] is over 37 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 36-40", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_809.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0015", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<234><229><256><239>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 48 meters, 2 with a height of approximately 42 meters, andothers with a height less than 40 meters.", + "Step 2: Bounding box -[<234><229><256><239>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<234><229><256><239>] is brown.", + "Step 4: The height corresponding to this color is greater than 50 meters.", + "Step 5: Bounding box -[<234><229><256><239>] is over 50 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 50 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_208.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0016", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<142><158><147><169>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofover 50 meters, two with a height of about 26 to 32 meters, and the rest witha height of less than 24 meters.", + "Step 2: Bounding box -[<142><158><147><169>] is located in the lower right corner of the image. Itis a triangular shaped building with no buildings to its left and a shorterbuilding behind it.", + "Step 3: The color of Bounding Box -[<142><158><147><169>] is red.", + "Step 4: The height corresponding to this color is greater than 50 meters.", + "Step 5: Bounding box -[<142><158><147><169>] is over 53 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_377.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0017", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<54><242><60><246>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, four with a heightof approximately 24 meters, and others with a height less than 18 meters.", + "Step 2: Bounding box -[<54><242><60><246>] is located in the lower left corner of the image,itis the smallest building in this corner.", + "Step 3: The color of Bounding Box -[<54><242><60><246>] is blue.", + "Step 4: The height corresponding to this color is about 0 to 12 meters.", + "Step 5: Bounding box -[<54><242><60><246>] is about 0 to 12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 18-24", + "(C) 24-30", + "(D) 30-36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_218.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0018", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<147><151><165><166>]", + "CoT": [ + "Step 1: There are 32 buildings in the picture, with 7 buildings ranging from36-48 meters in height, 2 buildings ranging from 18-24 meters in height, 4buildings below 18 meters in height, and other buildings ranging from 24-36meters in height.", + "Step 2: Boundary Box 2 is located in the middle of the image.", + "Step 3: The color of bounding box 2 is yellow.", + "Step 4: The height corresponding to this color is 36-48 meters.", + "Step 5: Boundary Box 2 is approximately 40 meters long." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 36-42", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_416.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0019", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<234><0><247><8>]", + "CoT": [ + "Step 1: There are as many as dozens of buildings in the picture. Among them,ten buildings are taller than 58 meters, one is about 37 to 39 meters high,another 11 are about 30 meters high, and the rest are shorter than 24meters.", + "Step 2: Bounding box -[<234><0><247><8>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<234><0><247><8>] is blue.", + "Step 4: This color corresponds to a height range of more than 22 meters butless than 24 meters.", + "Step 5: Bounding box -[<234><0><247><8>] is greater than 22 meters but less than 24 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2071.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0020", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<124><24><177><55>]", + "CoT": [ + "Step 1: There are over a hundred buildings in the picture. One is about 48 to60 meters high, three are about 36 to 48 meters high, one is about 24 to 36meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<124><24><177><55>] is located in the middle of the upper side of theimage, in the shape of G, and there are two small buildings above it.", + "Step 3: The color of Bounding Box -[<124><24><177><55>] is yellow.", + "Step 4: The height corresponding to this color is approximately 36 to 48meters.", + "Step 5: Bounding box -[<124><24><177><55>] is approximately 36 to 48 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 36-48", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_498.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0021", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<166><186><177><201>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, six buildings are taller than 58 meters, another 18 are about 36 to 48meters in height, and the remaining buildings are shorter than 24 meters.", + "Step 2: Bounding box -[<166><186><177><201>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<166><186><177><201>] is red.", + "Step 4: The height corresponding to this color is greater than 46 and lessthan 50.", + "Step 5: Bounding box -[<166><186><177><201>] is greater than 46 and less than 50." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 40-50", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2170.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0022", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600. Bounding box: -[<217><153><256><256>]", + "CoT": [ + "Step 1: There are 8 buildings in the picture. One is about 48 to 60 metershigh and the other 7 are about 0 to 12 meters high.", + "Step 2: Bounding box -[<217><153><256><256>] is located at the lower right corner of the image. Itis the building with the largest area in the picture.", + "Step 3: The color of Bounding Box -[<217><153><256><256>] is blue.", + "Step 4: The height corresponding to this color is approximately 0 to 12meters.", + "Step 5: Bounding box -[<217><153><256><256>] is approximately 0 to 12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_285.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0023", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<189><96><211><109>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, five buildings are taller than 35 meters, while the rest are shorterthan 20 meters.", + "Step 2: Bounding box -[<189><96><211><109>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<189><96><211><109>] is yellow.", + "Step 4: The height corresponding to this color is greater than 36 meters butless than 42 meters.", + "Step 5: Bounding box -[<189><96><211><109>] is greater than 36 meters but less than 42 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 36~42", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2292.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0024", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<150><12><190><20>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, six buildings are over 58 meters in height, nine are approximately 42 to48 meters in height, three are about 25 meters in height, and the rest areless than 24 meters in height.", + "Step 2: Bounding box -[<150><12><190><20>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<150><12><190><20>] is orange-colored.", + "Step 4: The height corresponding to this color is greater than 42 and lessthan 48.", + "Step 5: Bounding box -[<150><12><190><20>] is greater than 42 and less than 48." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 42~48", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2323.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0025", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<228><229><256><237>]", + "CoT": [ + "Step 1: There are as many as dozens of buildings in the picture. Among them,three buildings are over 58 meters in height, seven are approximately 27 to 33meters in height, 19 are about 38 meters in height, and the rest are less than15 meters in height.", + "Step 2: Bounding box -[<228><229><256><237>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<228><229><256><237>] is yellow.", + "Step 4: The height corresponding to this color is greater than 36 and lessthan 42.", + "Step 5: Bounding box -[<228><229><256><237>] is greater than 36 and less than 42." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 36~42", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2611.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0026", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<23><236><43><248>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, one is over 38 meters in height, two are approximately 26 to 34 metersin height, and the rest are less than 30 meters in height.", + "Step 2: Bounding box -[<23><236><43><248>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<23><236><43><248>] is green.", + "Step 4: The height corresponding to this color is greater than 30 and lessthan 36.", + "Step 5: Bounding box -[<23><236><43><248>] is greater than 30 and less than 36." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_706.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0027", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<214><208><227><221>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, three buildings are over 58 meters in height, seven are approximately 42to 48 meters in height, four are about 30 meters in height, and the rest areless than 21 meters in height.", + "Step 2: Bounding box -[<214><208><227><221>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<214><208><227><221>] is deep red.", + "Step 4: The height corresponding to this color is greater than 42 and lessthan 48.", + "Step 5: Bounding box -[<214><208><227><221>] is greater than 42 and less than 48." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 42~48", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_815.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0028", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<176><212><183><217>]", + "CoT": [ + "Step 1: There are over 20 buildings in the picture. One is about 36 to 42meters high, seven are about 18 to 24 meters high, and the rest are less than18 meters high.", + "Step 2: Bounding box -[<176><212><183><217>] is located at the lower right corner of the image,with a very small area and no buildings around it.", + "Step 3: The color of Bounding box -[<176><212><183><217>] is dark blue.", + "Step 4: The height corresponding to this color is approximately 0 to 6meters.", + "Step 5: Bounding box -[<176><212><183><217>] is approximately 0 to 6 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-6", + "(B) 12-18", + "(C) 24-30", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2300.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0029", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<9><50><20><136>]", + "CoT": [ + "Step 1: There are over 50 buildings in the picture. One is about 36 to 42meters high, one is about 18 to 24 meters high, and the rest are less than 18meters high.", + "Step 2: Bounding box -[<9><50><20><136>] is located in a group of buildings on the left side ofthe image, and its shape is similar to a long triangle.", + "Step 3: The color of Bounding Box -[<9><50><20><136>] is dark blue.", + "Step 4: The height corresponding to this color is approximately 0 to 6meters.", + "Step 5: Bounding box -[<9><50><20><136>] is approximately 0 to 6 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-6", + "(B) 12-18", + "(C) 24-30", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2587.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0030", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<78><191><111><219>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Two of them are about36 to 42 meters high, eight are about 24 to 36 meters high, and the rest areless than 24 meters high.", + "Step 2: Bounding box -[<78><191><111><219>] is located at the lower left corner of the image andits shape is V-shaped.", + "Step 3: The color of Bounding Box -[<78><191><111><219>] is light blue.", + "Step 4: The height corresponding to this color is approximately 12 to 18meters.", + "Step 5: Bounding box -[<78><191><111><219>] is approximately 12 to 18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-18", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_704.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0031", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<70><110><160><211>]", + "CoT": [ + "Step 1: There are over 50 buildings in the picture. Nine of them are about 48to 54 meters high, two are about 42 to 48 meters high, nine are about 36 to 42meters high, four are about 24 to 36 meters high, and the rest are less than24 meters high.", + "Step 2: Bounding box -[<70><110><160><211>] is located at the center of the image, has a largearea and is in the shape of C.", + "Step 3: The color of Bounding Box -[<70><110><160><211>] is reddish-brown.", + "Step 4: The height corresponding to this color is approximately 48 to 54meters.", + "Step 5: Bounding box -[<70><110><160><211>] is approximately 48 to 54 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-54", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_750.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0032", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<131><55><180><96>]", + "CoT": [ + "Step 1: There are over 80 buildings in the picture. One is about 24 to 36meters high, another is about 18 to 24 meters high, and the rest are less than18 meters high.", + "Step 2: Bounding box -[<131><55><180><96>] is located slightly to the upper right of the centerof the image and is the building with the largest area in the picture.", + "Step 3: The color of Bounding Box -[<131><55><180><96>] is cyan blue.", + "Step 4: The height corresponding to this color is approximately 18 to 24meters.", + "Step 5: Bounding box -[<131><55><180><96>] is approximately 18 to 24 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_811.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0033", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<105><74><144><116>]", + "CoT": [ + "Step 1: There are over a hundred buildings in the picture. Two of them areabout 54 to 60 meters high, two are about 48 to 54 meters high, four are about42 to 48 meters high, one is about 36 to 42 meters high, four are about 24 to36 meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<105><74><144><116>] is located slightly above the center of the image andhas a large area.", + "Step 3: The color of Bounding Box -[<105><74><144><116>] is dark red.", + "Step 4: The height corresponding to this color is approximately 54 to 60meters.", + "Step 5: Bounding box -[<105><74><144><116>] is approximately 54 to 60 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 54-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_990.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0034", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<113><51><157><93>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. One is about 42 to 48meters high, one is about 24 to 36 meters high, and the rest are less than 24meters high.", + "Step 2: Bounding box -[<113><51><157><93>] is located slightly above the center of the image andis the building with the largest area in the picture.", + "Step 3: The color of Bounding Box -[<113><51><157><93>] is dark blue.", + "Step 4: The height corresponding to this color is approximately 0 to 6meters.", + "Step 5: Bounding box -[<113><51><157><93>] is approximately 0 to 6 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-6", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_396.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0035", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<5><48><94><157>]", + "CoT": [ + "Step 1: There are over 70 buildings in the picture. One is about 48 to 54meters high, one is about 36 to 42 meters high, three are about 24 to 36meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<5><48><94><157>] is located on the left side of the image and is thebuilding with the largest area in the picture.", + "Step 3: The color of Bounding Box -[<5><48><94><157>] is dark blue.", + "Step 4: The height corresponding to this color is approximately 0 to 6meters.", + "Step 5: Bounding box -[<5><48><94><157>] is approximately 0 to 6 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-6", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_511.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0036", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><11><12><25>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with two buildingsabove 54 meters in height and the rest below 24 meters..", + "Step 2: Bounding box -[<0><11><12><25>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<0><11><12><25>] is crimson.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<0><11><12><25>] is over 54 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 54 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2072.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0037", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite and aerial images,and provide bounding boxes for reference objects. A bounding box in the format of (xmin,ymin,xmax,ymax),where the upper left corner is (x_min,y_min) and the lower right corner is (x-max,y_max). The resolution of satellite images is 600 x 600. Bounding box:-[<18><0><59><37>]", + "CoT": [ + "Step 1:There are hundreds of buildings in the picture,11 with a height of approximately 30 meters,and the remaining buildings are all below 24 meters in height.", + "Step 2:Bounding box -[<18><0><59><37>] is located in the upper left corner of the image.", + "Step 3:The color of Bounding Box -[<18><0><59><37>] is dark blue", + "Step 4:The height corresponding to this color is lower than 24 meters.", + "Step 5:Bounding box -[<18><0><59><37>] is lower tnan 24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 0-12", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2203.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0038", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<249><142><256><154>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 30 meters, one with a height of approximately 22 meters, andothers with a height less than 18 meters.", + "Step 2: Bounding box -[<249><142><256><154>] is located in the left corner of the image.", + "Step 3: The color of Bounding Box -[<249><142><256><154>] is light biue.", + "Step 4: The height corresponding to this color is about 22 meters.", + "Step 5: Bounding box -[<249><142><256><154>] is loewr than 30 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 26-32", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_778.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0039", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<79><236><98><256>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 30 meters, another with a height of approximately about 23meters, and others with a height less than 22 meters.", + "Step 2: Bounding box -[<79><236><98><256>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<79><236><98><256>] is cyan.", + "Step 4: The height corresponding to this color is 18-24 meters.", + "Step 5: Bounding box -[<79><236><98><256>] is about 23 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_988.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0040", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<170><145><215><173>]", + "CoT": [ + "Step 1: There are many buildings in the picture, four with a height greaterthan 48 meters, , and others with a height less than 18 meters.", + "Step 2: Bounding box -[<170><145><215><173>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<170><145><215><173>] is red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<170><145><215><173>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 48 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_378.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0041", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<74><19><96><27>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 42 meters, another with a height of approximately 36-42 meters,and others with a height less than 24 meters.", + "Step 2: Bounding box -[<74><19><96><27>] is located in the upper corner of the image.", + "Step 3: The color of Bounding Box -[<74><19><96><27>] is yellow.", + "Step 4: The height corresponding to this color is greater than 36 meters.", + "Step 5: Bounding box -[<74><19><96><27>] is over 36 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 36-42", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_507.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0042", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<250><141><256><150>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, five with a heightgreater than 30 meters, 2 with a height of approximately 20 meters, and otherswith a height less than 18 meters.", + "Step 2: Bounding box -[<250><141><256><150>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<250><141><256><150>] is green.", + "Step 4: The height corresponding to this color is about 30 meters.", + "Step 5: Bounding box -[<250><141><256><150>] is 30 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-36", + "(C) 36-48", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_513.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0043", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<26><198><50><205>]", + "CoT": [ + "Step 1: There are many buildings in the picture, one with a height greaterthan 36 meters, and others with a height less than 18 meters.", + "Step 2: Bounding box -[<26><198><50><205>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<26><198><50><205>] is orange.", + "Step 4: The height corresponding to this color is greater than 36 meters.", + "Step 5: Bounding box -[<26><198><50><205>] is about 42 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 42 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_523.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0044", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<243><131><254><159>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 48 meters, six with a height of approximately 30 to 36 meters,and others with a height less than 18 meters.", + "Step 2: Bounding box -[<243><131><254><159>] is located in the right corner of the image.", + "Step 3: The color of Bounding Box -[<243><131><254><159>] is green.", + "Step 4: The height corresponding to this color is 26-34 meters.", + "Step 5: Bounding box -[<243><131><254><159>] is over 24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-24", + "(B) 26-34", + "(C) 35-44", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_565.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0045", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<10><104><38><136>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, four with a heightgreater than 25 meters,meters, and others with a height less than 24 meters.", + "Step 2: Bounding box -[<10><104><38><136>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<10><104><38><136>] is yellow.", + "Step 4: The height corresponding to this color is 36-43 meters.", + "Step 5: Bounding box -[<10><104><38><136>] is about 37 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 35-40", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_598.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0046", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<221><171><240><187>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, two buildings are over 58 meters in height, five are approximately 50 to54 meters in height, four are about 30 meters in height, and the rest are lessthan 18 meters in height.", + "Step 2: Bounding box -[<221><171><240><187>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<221><171><240><187>] is deep red.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<221><171><240><187>] is over 54 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 54 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_996.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0047", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><1><18><7>]", + "CoT": [ + "Step 1: There are as many as dozens of buildings in the picture. Among them,two are less than 18 meters in height, while the rest are taller than 54meters.", + "Step 2: Bounding box -[<0><1><18><7>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<0><1><18><7>] is deep red.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<0><1><18><7>] is over 54 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 54 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_380.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0048", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<38><79><56><98>]", + "CoT": [ + "Step 1: There are as many as several hundred buildings in the picture. Amongthem, there is one building with a height exceeding 58 meters, six buildingswith heights ranging from 36 to 48 meters, one building with a height ofapproximately 27 meters, and the rest of the buildings have heights lower than18 meters.", + "Step 2: Bounding box -[<38><79><56><98>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<38><79><56><98>] is deep red.", + "Step 4: The height corresponding to this color is greater than 58 meters.", + "Step 5: Bounding box -[<38><79><56><98>] is over 58 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 58 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_504.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0049", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<212><0><237><15>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a height ofover 50 meters, two with a height of about 36 to 48 meters, one with a heightof about 28 meters, and the rest with a height of less than 18 meters.", + "Step 2: Bounding box -[<212><0><237><15>] is located in the upper right corner of the image,resembling a Y-shaped building with no buildings around it.", + "Step 3: The color of Bounding Box -[<212><0><237><15>] is green.", + "Step 4: The height corresponding to this color is greater than 24 meters.", + "Step 5: Bounding box -[<212><0><237><15>] is over 30meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_570.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0050", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<150><154><175><218>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which have aheight not exceeding 12 meters.", + "Step 2: Bounding box -[<150><154><175><218>] is located in the bottom right corner of the image andit is located between two rectangular buildings that are similar to it.", + "Step 3: The color of Bounding Box -[<150><154><175><218>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<150><154><175><218>] is less than 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_601.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0051", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<100><105><220><256>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which are lessthan 12 meters high.", + "Step 2: Bounding box -[<100><105><220><256>] is located in the bottom right corner of the image andit is the largest rectangular building.", + "Step 3: The color of Bounding Box -[<100><105><220><256>] is blue.", + "Step 4: The height corresponding to this color shall not exceed 12 meters.", + "Step 5: Bounding box -[<100><105><220><256>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_604.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0052", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<137><125><194><177>]", + "CoT": [ + "Step 1: There are over 50 buildings in the picture. One is about 48 to 60meters high, six are about 12 to 24 meters high, and the rest are less than 12meters high.", + "Step 2: Bounding box -[<137><125><194><177>] is located slightly to the lower right of the centerof the image and is the building with the largest area in the picture.", + "Step 3: The color of Bounding Box -[<137><125><194><177>] is dark blue.", + "Step 4: The height corresponding to this color is approximately 0 to 12meters.", + "Step 5: Bounding box -[<137><125><194><177>] is approximately 0 to 12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_531.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0053", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<101><5><149><48>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofabout 24 to 36 meters, 20 with a height of about 12-24 meters, and otherbuildings with a height of less than 12 meters.", + "Step 2: Bounding box -[<101><5><149><48>] is located in the upper right corner of the image，Itis the largest semi-circular building.", + "Step 3: The color of Bounding Box -[<101><5><149><48>] is light blue.", + "Step 4: The height corresponding to this color is 12-24 meters.", + "Step 5: Bounding box -[<101><5><149><48>] is 12-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_550.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0054", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<121><188><206><228>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofover 60 meters, three with a height of about 12 to 24 meters, and the restwith a height of no more than 12 meters.", + "Step 2: Bounding box -[<121><188><206><228>] is the longest rectangular building is located in thebottom right corner of the picture.", + "Step 3: The color of Bounding Box -[<121><188><206><228>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<121><188><206><228>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_528.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0055", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<227><14><238><28>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Among them, three areover 60 meters high, another five are about 36 to 54 meters high, 20 are about24 meters high, and the rest are less than 18 meters.", + "Step 2: Bounding box -[<227><14><238><28>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<227><14><238><28>] is red.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<227><14><238><28>] is over 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_219.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0056", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<7><207><17><219>]", + "CoT": [ + "Step 1: here are dozens of buildings in the picture. Among them, five areover 12 meters high, another six are about 6 to 12 meters high, and the restare less than 6 meters.", + "Step 2: Bounding box -[<7><207><17><219>] is located at the lower left corner of the image.", + "Step 3: The color of Bounding Box -[<7><207><17><219>] is blue.", + "Step 4: The height corresponding to this color is less than 6 meters.", + "Step 5: Bounding box -[<7><207><17><219>] is less than 6 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 6 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2294.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0057", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<226><53><240><67>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Among them, three areover 42 meters high, another one is about 36 to 42 meters high, ten are about30 meters high, and the rest are between 6 and 24 meters high.", + "Step 2: Bounding box -[<226><53><240><67>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<226><53><240><67>] is blue.", + "Step 4: The height corresponding to this color is less than 6 meters.", + "Step 5: Bounding box -[<226><53><240><67>] is less than 6 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 6 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2594.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0058", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<211><20><224><23>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, all of which are lessthan 12 meters in height.", + "Step 2: Bounding box -[<211><20><224><23>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<211><20><224><23>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<211><20><224><23>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 12 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_724.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0059", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<184><9><194><17>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, all of which are lessthan 12 meters in height.", + "Step 2: Bounding box -[<184><9><194><17>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<184><9><194><17>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<184><9><194><17>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 12 meters.", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_779.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0060", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<213><23><234><27>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Among them, five areover 60 meters high, another three are about 36 to 42 meters high, two areabout 26 meters high, and the rest are less than 24 meters.", + "Step 2: Bounding box -[<213><23><234><27>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<213><23><234><27>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<213><23><234><27>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 12 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_817.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0061", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<217><35><243><59>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture. Among them, three areover 60 meters tall and the rest are less than 24 meters.", + "Step 2: Bounding box -[<217><35><243><59>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<217><35><243><59>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<217><35><243><59>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Less than 12 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_264.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0062", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<248><240><256><256>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, two with a heightabout 24 meters,others with a height of approximately 6 to 24 meters.", + "Step 2: Bounding box -[<248><240><256><256>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<248><240><256><256>] is cyan.", + "Step 4: The height corresponding to this color is about 24 meters.", + "Step 5: Bounding box -[<248><240><256><256>] is about 24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 30-36", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1214.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0063", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<246><19><256><27>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, of which eleven aremore than 24 meters high, seven are about 0 to 12 meters high, and the restare less than 12 to 18 meters high.", + "Step 2: Bounding box -[<246><19><256><27>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<246><19><256><27>] is cyan.", + "Step 4: The height corresponding to this color is greater than 24meters.", + "Step 5: Bounding box -[<246><19><256><27>] is over 24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1003.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0064", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<222><39><255><72>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, three of which are morethan 50 meters high, the other three are about 38 to 48 meters high, 16 areabout 28 meters high, and the rest are less than 24 meters high.", + "Step 2: Bounding box -[<222><39><255><72>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<222><39><255><72>] is dark yellow.", + "Step 4: The height corresponding to this color is greater than 38 meters.", + "Step 5: Bounding box -[<222><39><255><72>] is over 38 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2088.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0065", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<176><22><193><41>]", + "CoT": [ + "Step 1: There are 89 buildings in the picture, three of which are more than60 meters high, one is about 49 to 55 meters high, six are about 22 metershigh, and the rest are less than 20 meters high..", + "Step 2: Bounding box -[<176><22><193><41>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<176><22><193><41>] is brown.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<176><22><193><41>] is over 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2165.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0066", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<226><0><256><14>]", + "CoT": [ + "Step 1: There are 21 buildings in the picture, one of which is more than 42meters high, two are about 30 to 36 meters high, and the rest are less than 24meters high..", + "Step 2: Bounding box -[<226><0><256><14>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<226><0><256><14>] is blue.", + "Step 4: The height corresponding to this color is greater than 6 meters.", + "Step 5: Bounding box -[<226><0><256><14>] is over 6 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 06-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2196.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0067", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<214><0><229><17>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, six of which are morethan 18 meters high, and the rest are less than 18 meters high..", + "Step 2: Bounding box -[<214><0><229><17>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<214><0><229><17>] is light blue.", + "Step 4: The height corresponding to this color is greater than 18 meters.", + "Step 5: Bounding box -[<214><0><229><17>] is over 18 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2295.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0068", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<195><0><256><47>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one of which is morethan 24 meters high, nine are about 18 to 24 meters high, and the rest areless than 18 meters high.", + "Step 2: Bounding box -[<195><0><256><47>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<195><0><256><47>] is blue.", + "Step 4: The height corresponding to this color is greater than 18 meters.", + "Step 5: Bounding box -[<195><0><256><47>] is over 18 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2296.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0069", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><0><18><28>]", + "CoT": [ + "Step 1: There are 53 buildings in the picture, of which 2 are more than 24meters high, 5 are about 18 to 24 meters high, and the rest are less than 18meters in height..", + "Step 2: Bounding box -[<0><0><18><28>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<0><0><18><28>] is blue.", + "Step 4: The height corresponding to this color is greater than 6 meters.", + "Step 5: Bounding box -[<0><0><18><28>] is over 6 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 06-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2643.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0070", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<228><0><256><4>]", + "CoT": [ + "Step 1: There are nearly 100 buildings in the picture, of which 3 are morethan 30 meters high, one is about 24 meters high, 20 are about 18 meters high,and the rest are less than 18 meters high.", + "Step 2: Bounding box -[<228><0><256><4>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<228><0><256><4>] is blue.", + "Step 4: The height corresponding to this color is greater than 6 meters.", + "Step 5: Bounding box -[<228><0><256><4>] is over 6 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_718.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0071", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<228><0><253><15>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, four of which aremore than 60 meters high, one is about 48 to 54 meters high, one is about 42meters high, and the rest are less than 36 meters high.", + "Step 2: Bounding box -[<228><0><253><15>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<228><0><253><15>] is blue.", + "Step 4: The height corresponding to this color is greater than 12 meters.", + "Step 5: Bounding box -[<228><0><253><15>] is over 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_816.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0072", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<229><0><256><13>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, thirteen of which aremore than 60 meters high, one is about 36 to 42 meters high, two are about 36meters high, and the rest are less than 36 meters high.", + "Step 2: Bounding box -[<229><0><256><13>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<229><0><256><13>] is Light blue.", + "Step 4: The height corresponding to this color is greater than 18 meters.", + "Step 5: Bounding box -[<229><0><256><13>] is over 18 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_818.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0073", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<240><239><252><253>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a height ofover 60 meters, three with a height of about 48 to 54 meters, five with aheight of about 45 meters, and other buildings with a height of less than 24meters.", + "Step 2: Bounding box -[<240><239><252><253>] is located in the bottom right corner of the image andpresents a rectangle.", + "Step 3: The color of Bounding Box -[<240><239><252><253>] is light red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<240><239><252><253>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-54", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_218.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0074", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<82><0><90><20>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, with 14 buildingsexceeding 48 meters in height, 12 buildings ranging from 24 to 36 meters inheight, 3 buildings approximately 47 meters in height, 1 buildingapproximately 37 meters in height, and other buildings below 24 meters inheight.", + "Step 2: Bounding box -[<82><0><90><20>] is located in the upper left corner of the image.", + "Step 3: The color of Bounding Box -[<82><0><90><20>] is yellow.", + "Step 4: The height corresponding to this color is greater than 36 meters.", + "Step 5: Bounding box -[<82><0><90><20>] is over 36 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2286.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0075", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<192><163><226><189>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, with one buildingexceeding 48 meters in height, four buildings ranging from 18 to 24 meters inheight, and other buildings below 18 meters in height.", + "Step 2: Bounding box -[<192><163><226><189>] is located in the bottom right corner of the image.", + "Step 3: The color of Bounding Box -[<192><163><226><189>] is red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<192><163><226><189>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2365.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0076", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<97><46><124><53>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 13 buildingsexceeding 36 meters in height, 5 buildings exceeding 48 meters in height, 1building approximately 21 meters in height, and 6 buildings below 18 meters inheight.", + "Step 2: Bounding box -[<97><46><124><53>] is located in the upper left corner of the image andappears as a rectangle.", + "Step 3: The color of Bounding Box -[<97><46><124><53>] is red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<97><46><124><53>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2612.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0077", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<105><14><129><22>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, two of which are over60 meters high, one is about 36 to 42 meters high, and the remaining dozensare all below 24 meters.", + "Step 2: Bounding box -[<105><14><129><22>] is located in the upper left corner of the image andis a horizontal rectangle in shape.", + "Step 3: The color of Bounding Box -[<105><14><129><22>] is red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<105><14><129><22>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_717.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0078", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><251><14><256>]", + "CoT": [ + "Step 1: There are approximately 100 buildings in the picture, with 6buildings exceeding 48 meters in height, 1 building ranging from 36 to 42meters in height, over a dozen buildings below 18 meters in height, and theremaining dozens of buildings ranging from 18 to 24 meters in height.", + "Step 2: Bounding box -[<0><251><14><256>] is located in the bottom left corner of the imagebottom left.", + "Step 3: The color of Bounding Box -[<0><251><14><256>] is red.", + "Step 4: The height corresponding to this color is greater than 48 meters.", + "Step 5: Bounding box -[<0><251><14><256>] is over 48 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 48-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_819.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0079", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<21><32><40><51>]", + "CoT": [ + "Step 1: There are 16 buildings in the picture, with 6 buildings exceeding 54meters in height and 10 buildings ranging from 6 to 18 meters in height.", + "Step 2: Bounding box -[<21><32><40><51>] is located in the upper left corner of the image andhas the largest area.", + "Step 3: The color of Bounding Box -[<21><32><40><51>] is deep red.", + "Step 4: The height corresponding to this color is greater than 54 meters.", + "Step 5: Bounding box -[<21><32><40><51>] is over 54 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 54-60", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1040.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0080", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<85><14><105><32>]", + "CoT": [ + "Step 1: There are approximately 100 buildings in the picture, with 4buildings exceeding 54 meters in height.", + "Step 2: Bounding box -[<85><14><105><32>] is located in the upper left corner of the image andhas a circular shape.", + "Step 3: The color of Bounding Box -[<85><14><105><32>] is green.", + "Step 4: The height corresponding to this color is 24 to 36 meters.", + "Step 5: Boundary Box 2 meters 24 to 36 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_503.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0081", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<204><96><256><186>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, and every buildingswith a height less than 24 meters.", + "Step 2: Bounding box -[<204><96><256><186>] is located in the right side of the image.", + "Step 3: The color of Bounding Box -[<204><96><256><186>] is blue.", + "Step 4: The height corresponding to this color approach to10 meters.", + "Step 5: Bounding box -[<204><96><256><186>] is about 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2101.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0082", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><237><23><256>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, three with a heightof approximately 36 to 42 meters, rest with a height of less than 24 meters.", + "Step 2: Bounding box -[<0><237><23><256>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<0><237><23><256>] is dark blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<0><237><23><256>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 6-18", + "(B) 18-24", + "(C) 24-30", + "(D) 30-36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2167.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0083", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<49><235><62><248>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, three with a heightgreater than 36 meters, another with a height of approximately 12 to 24meters.", + "Step 2: Bounding box -[<49><235><62><248>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<49><235><62><248>] is orange.", + "Step 4: The height corresponding to this color is greater than 42 meters.", + "Step 5: Bounding box -[<49><235><62><248>] is over 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 36-48", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2257.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0084", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<231><116><241><125>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, every building with aheight less than 12 meters.", + "Step 2: Bounding box -[<231><116><241><125>] is located in the right side of the image.", + "Step 3: The color of Bounding Box -[<231><116><241><125>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<231><116><241><125>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 6-18", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2614.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0085", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><0><12><6>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 60 meters, another with a height of approximately 36 to 42meters, 10 with a height of approximately 24 meters, and others with a heightless than 18 meters.", + "Step 2: Bounding box -[<0><0><12><6>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<0><0><12><6>] is brown.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<0><0><12><6>] is about 18-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_814.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0086", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><142><25><166>]", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture, one with a heightgreater than 60 meters, another with a height of approximately 36 to 42meters, 10 with a height of approximately 24 meters, and others with a heightless than 18 meters.", + "Step 2: Bounding box -[<0><142><25><166>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<0><142><25><166>] is brown.", + "Step 4: The height corresponding to this color is greater than 60 meters.", + "Step 5: Bounding box -[<0><142><25><166>] is over 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2113.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0087", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<47><50><204><63>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofabout 12 to 24 meters, and the others with a height of less than 18 meters.", + "Step 2: Bounding box -[<47><50><204><63>] is located in the upper right corner of the image，Itis the longest rectangular building.", + "Step 3: The color of Bounding Box -[<47><50><204><63>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<47><50><204><63>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2634.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0088", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<32><0><83><82>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 2 buildingsexceeding 36 meters in height, 10 buildings ranging from 24 to 36 meters inheight, and others less than 20 meters in height.", + "Step 2: Bounding box -[<32><0><83><82>] is located in the upper left corner of the image it isthe largest rectangular building.", + "Step 3: The color of Bounding Box -[<32><0><83><82>] is light blue.", + "Step 4: The height corresponding to this color is 12-24 meters.", + "Step 5: Bounding box -[<32><0><83><82>] is 12-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_703.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0089", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<180><183><256><243>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which have aheight of no more than 12 meters.", + "Step 2: Bounding box -[<180><183><256><243>] is located in the bottom right corner of the picture,it is the largest rectangular building.", + "Step 3: The color of Bounding Box -[<180><183><256><243>] is blue.", + "Step 4: The height corresponding to this color is below 12 meters.", + "Step 5: Bounding box -[<180><183><256><243>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_728.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0090", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<116><136><168><203>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofabout 36 meters, five with a height of about 24 meters, and the others with aheight of less than 18 meters.", + "Step 2: Bounding box -[<116><136><168><203>] is located in the center of the picture is the largestL-shaped building.", + "Step 3: The color of Bounding Box -[<116><136><168><203>] is light blue", + "Step 4: The height corresponding to this color is 12-24 meters.", + "Step 5: Bounding box -[<116><136><168><203>] is 12-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 12-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_740.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0091", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<159><92><256><166>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which have aheight of no more than 12 meters.", + "Step 2: Bounding box -[<159><92><256><166>] is located in the bottom right corner of the picture,it is the largest rectangular building.", + "Step 3: The color of Bounding Box -[<159><92><256><166>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<159><92><256><166>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_777.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0092", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<97><242><126><256>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofabout 12 to 24 meters, and the height of other buildings is less than 12meters.", + "Step 2: Bounding box -[<97><242><126><256>] is located in the bottom left corner of the picture,it is the largest triangular building.", + "Step 3: The color of Bounding Box -[<97><242><126><256>] is blue.", + "Step 4: The height corresponding to this color shall not exceed 12 meters.", + "Step 5: Bounding box -[<97><242><126><256>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2395.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0093", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<85><167><131><187>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which have aheight of less than 12 meters.", + "Step 2: Bounding box -[<85><167><131><187>] is located in the center of the picture, it is thelongest rectangular building.", + "Step 3: The color of Bounding Box -[<85><167><131><187>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<85><167><131><187>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) 0-12", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2332.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0094", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<202><0><256><74>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which are lessthan 18 meters high.", + "Step 2: Bounding box -[<202><0><256><74>] is located in the upper right corner of the image andIt is the largest rectangular building.", + "Step 3: The color of Bounding Box -[<202><0><256><74>] is light blue.", + "Step 4: The corresponding color for this color is 12-24 meters.", + "Step 5: Bounding box -[<202><0><256><74>] is 12-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2251.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0095", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<148><28><186><94>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, one with a height ofabout 12 to 24 meters, and the others with a height of less than 12 meters.", + "Step 2: Bounding box -[<148><28><186><94>] is located in the upper right corner of the image.", + "Step 3: The color of Bounding Box -[<148><28><186><94>] is baby blue.", + "Step 4: This color is suitable for heights of 12-24 meters.", + "Step 5: Bounding box -[<148><28><186><94>] is 12-24 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2210.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0096", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<87><111><140><146>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 3 buildingsexceeding 60 meters in height, 2 buildings ranging from 36 to 48 meters inheight, approximately 10 buildings ranging from 12-24 meters in height, andothers less than 12 meters in height.", + "Step 2: Bounding box -[<87><111><140><146>] is an oval shaped building located in the center ofthe picture.", + "Step 3: The color of Bounding Box -[<87><111><140><146>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<87><111><140><146>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2186.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0097", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><243><25><256>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, all of which have aheight of less than 12 meters.", + "Step 2: Bounding box -[<0><243><25><256>] is located in the bottom left corner of the image.", + "Step 3: The color of Bounding Box -[<0><243><25><256>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<0><243><25><256>] is less than 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2162.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0098", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<0><107><17><185>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with 3 buildingsranging in height from 24 to 36 meters, and the rest of the buildings notexceeding 20 meters.", + "Step 2: Bounding box -[<0><107><17><185>] is located in the bottom right corner of the picture,it is the largest elliptical building.", + "Step 3: The color of Bounding Box -[<0><107><17><185>] is blue.", + "Step 4: The height corresponding to this color is less than 12 meters.", + "Step 5: Bounding box -[<0><107><17><185>] is over 60 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 18-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2150.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0099", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<98><125><126><167>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, each of which is nomore than 12 meters long.", + "Step 2: Bounding box -[<98><125><126><167>] is located in the center of the picture, it is anL-shaped building.", + "Step 3: The color of Bounding Box -[<98><125><126><167>] is blue.", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<98><125><126><167>] is not exceeding 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2096.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Individual building height estimation/0100", + "Question_Type": "Single Choice", + "Text": "Determine the actual height of the building based on satellite andaerial images, and provide bounding boxes for reference objects. A boundingbox in the format of (xmin, ymin, xmax, ymax), where the upper left corner is(x_min, y_min) and the lower right corner is (x-max, y_max). The resolution ofsatellite images is 600 x 600.Bounding box:-[<114><163><189><228>]", + "CoT": [ + "Step 1: There are dozens of buildings in the picture, with one buildingexceeding 48 meters in height and the others not exceeding 40 meters.", + "Step 2: Bounding box -[<114><163><189><228>] is The largest elliptical building is located in thebottom right corner of the picture.", + "Step 3: The color of Bounding Box -[<114><163><189><228>] is blue", + "Step 4: The height corresponding to this color does not exceed 12 meters.", + "Step 5: Bounding box -[<114><163><189><228>] does not exceed 12 meters" + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Individual building height estimation", + "Answer Choices": [ + "(A) 0-24", + "(B) 24-30", + "(C) 30-36", + "(D) Over 60 meters", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2087.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Reasoning/Overall_building_height_estimation.json b/jsons/Pedosphere/Urban_Development/Reasoning/Overall_building_height_estimation.json new file mode 100644 index 0000000000000000000000000000000000000000..5aa19d76c835d632f78a91011113042ccd65c30f --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Reasoning/Overall_building_height_estimation.json @@ -0,0 +1,2902 @@ +[ + { + "Question_id": "Overall building height estimation/0000", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1:There are hundreds of buildings in the picture.", + "Step 2:In the buildings in the picture,one is light yellow,one is green,two are red,and there are hundreds of blue buildings.", + "Step 3:The red color corresponds to a height of about 50 meters,the light yellow color corresponds to a height between 36 meters and 42 meters,and the green color corresponds to a height between 24 meters and 36 meters,light blue corresponds to a height of 24 meters,and blue corresponds to a height below 18 meters.", + "Step 4:There are hundreds of buildings in the picture,one with a height greater than 60 meters,another with a height of approximately 36 to 42 meters,10 with a height of approximately 24 meters,and others with a height less than 18 meters.", + "Step 5:The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2100.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0001", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1:There are hundreds of buildings in the picture.", + "Step 2:Among the buildings in the picture,there is one that is brown,one that is yellow and orange,ten that are light blue,and hundreds that are blue.", + "Step 3:Brown corresponds to a height of over 60 meters,yellow and orange correspond to a height of 36 to 40 meters,light blue corresponds to a height of 24 meters,and blue corresponds to a height below 18 meters.", + "Step 4:There are hundreds of buildings in the picture,one with a height greater than 60 meters,another with a height of approximately 36 to 42 meters,10 with a height of approximately 24 meters,and others with a height less than 18 meters.", + "Step 5:The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2113.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0002", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1:There are dozens of buildings in the picture.", + "Step 2:Among the buildings in the picture,one is yellow,twenty are light blue,and dozens are blue.", + "Step 3:Yellow corresponds to heights between 36 and 48 meters,light blue corresponds to 24 meters,and blue corresponds to heights below 18 meters.", + "Step 4:There are dozens of buildings in the picture,one with a height of about 36 to 48 meters,20 with a height of about 12-24 meters,and other buildings with a height of less than 12 meters.", + "Step 5:The average height of the buildings in the entire map is 6-12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2168.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0003", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1:There are hundreds of buildings in the picture.", + "Step 2:Among the buildings in this picture,hundreds are blue.", + "Step 3:Blue indicates a height of less than 18 meters.", + "Step 4:There are hundreds of buildings in the picture,all of which are less than 12 meters in height.", + "Step 5:The average height of the buildings in the entire map is 6-12 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_104.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0004", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1:There are hundreds of buildings in the picture.", + "Step 2:Among the buildings in the picture,one is dark red,six are lightorange,three are light yellow,one is green,and hundreds are blue.", + "Step 3:Deep red corresponds to a height of over 60 meters,yellow and orangeto a height between 36 and 48 meters,light blue to a height of over 24meters,and blue to a height of under 18 meters.", + "Step 4:There are hundreds of buildings in the picture,one with a height greater than 60 meters,another with a height of approximately 36 to 42 meters,10 with a height of approximately 24 meters,and others with a height less than 18 meters.", + "Step 5:The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_217.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0005", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2246.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0006", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In the picture of buildings, there are two buildings that are green,and the rest are blue.", + "Step 3: The height corresponding to green is approximately 24 to 36 meters,while the height corresponding to the rest of blue is below 24 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2568.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0007", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In the buildings in the picture, there are two buildings with a height exceeding 48 meters, one building with a height of about 38 meters,another building with a height of about 30 meters, and the remaining buildingswith a height not exceeding 24 meters.", + "Step 3: Orange corresponds to a height of about 49 meters, yellow correspondsto a height of about 38 meters, green corresponds to a height of about 30 meters, blue corresponds to a height below 18 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2642.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0008", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is dark red, four areyellow, and the others are all blue.", + "Step 3: Deep red corresponds to a height of about 50 meters, yellowcorresponds to a height of about 37 meters, light blue corresponds to a heightabove 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_705.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0009", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In the buildings in the picture, there are two green ones, two redones, one orange and yellow one, and hundreds of blue ones.", + "Step 3: The building height corresponding to green is about 30 meters, thebuilding height corresponding to red is about 48 to 60 meters, the buildingheight corresponding to orange and yellow is about 36 to 45 meters, the lightblue corresponds to a height above 24 meters, and the blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_765.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0010", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one in red, one in lightred, one in yellow, and hundreds in blue.", + "Step 3: The building height corresponding to red is about 52 meters, thebuilding height corresponding to light red is about 40 to 48 meters, thebuilding height corresponding to light yellow is about 36 to 40 meters, thebuilding height corresponding to light blue is above 24 meters, and thebuilding height corresponding to blue is below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_809.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0011", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In the buildings in the picture, one is red, two are green, and theothers are all blue.", + "Step 3: The building height corresponding to red is about 55 meters, thebuilding height corresponding to green is about 24 to 36 meters, the lightblue corresponds to a height above 24 meters, and the blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_377.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0012", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In the building in the picture, there is a light yellow one, a greenone, and the others are all blue.", + "Step 3: Light yellow corresponds to a building height of approximately 37meters or more, green corresponds to a building height of approximately 30meters or more, light blue corresponds to a height of 24 meters or more, andblue corresponds to a height of 18 meters or less.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_446.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0013", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, nine are of yellowish-greencolor and hundreds are of blue color.", + "Step 3: The corresponding height range for the yellowish-green color isbetween 27 and 36 meters, while the deep blue color corresponds to heightsbelow 15 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, nine buildings are taller than 36 meters, while the rest are shorterthan 24 meters.", + "Step 5: The average height of the buildings in the entire map is 21-27meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2151.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0014", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in this picture, there is one yellow one, threeorange ones, ten dark red ones and dozens of dark blue ones.", + "Step 3: The corresponding heights for deep red are over 58 meters, for orangethey are between 42 and 48 meters, for light blue they are 22 meters, and fordark blue they are below 15 meters.", + "Step 4: There are as many as dozens of buildings in the picture. Among them,ten buildings are taller than 58 meters, one is about 37 to 40 meters high,another 11 are about 27 meters high, and the rest are shorter than 15meters.", + "Step 5: The average height of the buildings in the entire map is 24-36meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2071.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0015", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, six are brownish-red, two areyellow and hundreds are dark blue.", + "Step 3: The height corresponding to the brownish-red color exceeds 58 meters,the height corresponding to the yellow and orange colors is between 36 and 42meters, while the height corresponding to the dark blue color is lower than 15meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, six buildings are taller than 58 meters, another 18 are about 36 to 48meters in height, and the remaining buildings are shorter than 24 meters.", + "Step 5: The average height of the buildings in the entire map is 33-39meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2170.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0016", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, four are green and hundreds areblue.", + "Step 3: The corresponding height for green is from 30 to 36 meters, whilethat for dark blue is below 15 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, four buildings are approximately 30 to 36 meters in height, while therest are less than 15 meters in height.", + "Step 5: The average height of the buildings in the entire map is 22-26meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2215.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0017", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, five are yellow and hundreds areblue.", + "Step 3: The corresponding height for yellow is from 36 to 42 meters, whilethat for blue is lower than 20 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, five buildings are taller than 35 meters, while the rest are shorterthan 20 meters.", + "Step 5: The average height of the buildings in the entire map is 24-30meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2292.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0018", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, six are brownish red, nine areyellowish orange, three are light green, and hundreds are blue.", + "Step 3: The height corresponding to the brownish-red color exceeds 58 meters,that of the yellow-orange color is between 42 and 46 meters, that of the lightgreen color is 27 meters, while that of the blue color is lower than 24meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, six buildings are over 58 meters in height, nine are approximately 42 to48 meters in height, three are about 25 meters in height, and the rest areless than 24 meters in height.", + "Step 5: The average height of the buildings in the entire map is 40-48meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2323.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0019", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in this picture, there are three that arebrownish red, nineteen that are yellow, eight that are light green, and dozensthat are blue.", + "Step 3: The height corresponding to the brownish-red color exceeds 58 meters,that of the yellow color is between 38 and 40 meters, that of the light greencolor is 27 meters, and that of the blue color is lower than 22 meters.", + "Step 4: There are as many as dozens of buildings in the picture. Among them,three buildings are over 58 meters in height, seven are approximately 27 to 33meters in height, 19 are about 38 meters in height, and the rest are less than15 meters in height.", + "Step 5: The average height of the buildings in the entire map is 38-42meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2611.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0020", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, there is one yellow one, twogreen ones and hundreds of blue ones.", + "Step 3: The corresponding heights for the colors are as follows: yellowcorresponds to 36 to 40 meters, green to 30 meters, and blue to less than 15meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, one is over 38 meters in height, two are approximately 26 to 34 metersin height, and the rest are less than 30 meters in height.", + "Step 5: The average height of the buildings in the entire map is 24-28meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_706.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0021", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, there is one that is orange,three that are yellow, three that are green, and hundreds that are blue.", + "Step 3: The orange zone corresponds to heights exceeding 45 meters, theyellow zone to heights ranging from 36 to 40 meters, the green zone to heightsof 30 meters, and the blue zone to heights lower than 18 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, one is over 45 meters in height, three others are approximately 36 to 42 meters in height, and three others are about 27 meters in height. Theremaining buildings are all less than 18 meters in height.", + "Step 5: The average height of the buildings in the entire map is 28-32meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_753.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0022", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, there are three that are darkred, three that are orange, three that are green, and hundreds that are blue.", + "Step 3: The corresponding heights for the deep red color exceed 58 meters,for the orange color it is 42 to 48 meters, for the green color it is 30meters, and for the blue color it is below 18 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, three buildings are over 58 meters in height, seven are approximately 42to 48 meters in height, four are about 30 meters in height, and the rest areless than 21 meters in height.", + "Step 5: The average height of the buildings in the entire map is 34-42meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_815.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0023", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 60 buildings in the picture.", + "Step 2: Among the buildings in the picture, two are dark red, one is red, one is brown, two are yellow, two are light blue, and the rest are blue.", + "Step 3: Deep red corresponds to heights above 60 meters, red to heights between 48 meters and 54 meters, brown to heights between 42 meters and 54 meters, yellow to heights between 36 meters and 42 meters, light blue to heights between 18 meters and 24 meters, and blue to heights below 18meters.", + "Step 4: There are over 60 buildings in the picture. Two of them are over 60meters high, one is about 48 to 54 meters high, one is about 42 to 48 metershigh, two are about 36 to 42 meters high, two are about 18 to 24 meters high,and the rest are less than 18 meters high.", + "Step 5: The average height of the buildings in the entire map is 18-24 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2025.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0024", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, two are dark red, three arebrown, one is green and the rest are blue.", + "Step 3: Deep red corresponds to a height of over 60 meters, brown to a heightbetween 42 and 48 meters, green to a height between 24 and 36 meters, and blueto a height of less than 24 meters.", + "Step 4: There are hundreds of buildings in the picture. Two are over 60meters high, three are about 42 to 48 meters high, one is about 24 to 36meters high, and the rest are less than 24 meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2198.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0025", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 20 buildings in the picture.", + "Step 2: Among the buildings in the picture, one is yellow, seven are lightblue and the rest are dark blue.", + "Step 3: Yellow corresponds to a height between 36 and 42 meters, light blueto a height between 18 and 24 meters, and dark blue to a height below 18meters.", + "Step 4: There are over 20 buildings in the picture. One is about 36 to 42 meters high, seven are about 18 to 24 meters high, and the rest are less than18 meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2300.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0026", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 50 buildings in the picture.", + "Step 2: Among the buildings in the picture, one is yellow, one is light blue,and the rest are dark blue.", + "Step 3: Yellow corresponds to a height between 36 and 42 meters, light blueto a height between 18 and 24 meters, and dark blue to a height below 18meters.", + "Step 4: There are over 50 buildings in the picture. One is about 36 to 42 meters high, one is about 18 to 24 meters high, and the rest are less than 18meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2587.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0027", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, two are yellow, eight are greenand the rest are blue.", + "Step 3: Yellow corresponds to a height between 36 and 42 meters, green to a height between 24 and 36 meters, and blue to a height below 24 meters.", + "Step 4: There are hundreds of buildings in the picture. Two of them are about36 to 42 meters high, eight are about 24 to 36 meters high, and the rest areless than 24 meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_704.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0028", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 50 buildings in the picture.", + "Step 2: Among the buildings in the picture, 9 are reddish-brown, 2 are brown,9 are yellow, 4 are green and the rest are blue.", + "Step 3: Red-brown corresponds to a height between 48 and 54 meters, brown toa height between 42 and 48 meters, yellow to a height between 36 and 42meters, green to a height between 24 and 36 meters, and blue to a height below24 meters.", + "Step 4: There are over 50 buildings in the picture. Nine of them are about 48to 54 meters high, two are about 42 to 48 meters high, nine are about 36 to 42 meters high, four are about 24 to 36 meters high, and the rest are less than24 meters high.", + "Step 5: The average height of the buildings in the entire map is 24-30meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_750.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0029", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 80 buildings in the picture.", + "Step 2: Among the buildings in the picture, one is green, one is cyan andblue, and the rest are dark blue.", + "Step 3: Green corresponds to a height between 24 and 36 meters, cyan bluecorresponds to a height between 18 and 24 meters, and dark blue corresponds toa height below 18 meters.", + "Step 4: There are over 80 buildings in the picture. One is about 24 to 36meters high, another is about 18 to 24 meters high, and the rest are less than18 meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_811.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0030", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over a hundred buildings in the picture.", + "Step 2: Among the buildings in the picture, two are dark red, two are red,four are brown, one is yellow, four are green and the rest are blue.", + "Step 3: Deep red corresponds to heights between 54 and 60 meters, red toheights between 48 and 54 meters, brown to heights between 42 and 48 meters,yellow to heights between 36 and 42 meters, green to heights between 24 and 36meters, and blue to heights below 24 meters.", + "Step 4: There are over a hundred buildings in the picture. Two of them areabout 54 to 60 meters high, two are about 48 to 54 meters high, four are about42 to 48 meters high, one is about 36 to 42 meters high, four are about 24 to36 meters high, and the rest are less than 24 meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_990.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0031", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is brown, one is green andthe rest are blue.", + "Step 3: Brown corresponds to a height between 42 and 48 meters, green to a height between 24 and 36 meters, and blue to a height below 24 meters.", + "Step 4: There are hundreds of buildings in the picture. One is about 42 to 48meters high, one is about 24 to 36 meters high, and the rest are less than 24meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_396.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0032", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 70 buildings in the picture.", + "Step 2: Among the buildings in the picture, one is red, one is yellow, threeare green and the rest are blue.", + "Step 3: Red corresponds to a height between 48 and 54 meters, yellow to a height between 36 and 42 meters, green to a height between 24 and 36 meters,and blue to a height below 24 meters.", + "Step 4: There are over 70 buildings in the picture. One is about 48 to 54meters high, one is about 36 to 42 meters high, three are about 24 to 36meters high, and the rest are less than 24 meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_511.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0033", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are two that is light blue,ten that are light blue, The rest are all dark blue.", + "Step 3:Light blue corresponds to a height of about 20 meters, navy bluecorresponds to a height of 8 to 12 meters, and deep red corresponds to a height of over 54 meters.", + "Step 4: There are hundreds of buildings in the picture, three with a heightgreater than 54 meters, two with a height of approximately 18to 23meters, andothers with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2072.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0034", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is five that is orange,eleven that are green, three that are light blue, and hundreds that are blue.", + "Step 3: Orange corresponds to a height of about 42 meters, green correspondto a height of about 30 meters, light blue corresponds to a height of 20meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, five with a heightgreater than 40 meters, 11 with a height of approximately 30 meters,Theremaining buildings are all below 24 meters in height .", + "Step 5: The average height of the buildings in the entire map is 12 to 30meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-30", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2203.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0035", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is green, onethat is light blue，and the remaining buildings are blue.", + "Step 3: Green corresponds to a height of about 30 meters, light bluecorresponds to a height of 22 meters, and blue corresponds to a height below18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a heightgreater than 30 meters, another with a height of approximately 18 to 22meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 1-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 1-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_778.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0036", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-36", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_988.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0037", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_378.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0038", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_507.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0039", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_513.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0040", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_523.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0041", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_565.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0042", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is yellow,three that is green , and hundreds that are blue.", + "Step 3: Yellow corresponds to a height of over 36 meters,green correspond toa height of 24 to 36 meters, light blue corresponds to a height of 24 meters,and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a heightgreater than 36 meters, three with a height of approximately 30 meters, andothers with a height less than 24 meters.", + "Step 5: The average height of the buildings in the entire map is 8-18meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 8-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_598.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0043", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: In this picture, there are two buildings that are dark red, eightthat are orange, four that are green, and hundreds that are blue.", + "Step 3: The corresponding heights for the deep red color exceed 58 meters,for the orange color it is 42 to 48 meters, for the green color it is 30meters, and for the blue color it is below 18 meters.", + "Step 4: There are as many as several hundred buildings in the picture. Amongthem, two buildings are over 58 meters in height, five are approximately 50 to54 meters in height, four are about 30 meters in height, and the rest are lessthan 18 meters in height.", + "Step 5: The average height of the buildings in the entire map is 31-39meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_996.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0044", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in this picture, there are two that are blue anddozens that are dark red.", + "Step 3: The deep red color corresponds to a height exceeding 54 meters, whilethe blue color corresponds to a height lower than 18 meters.", + "Step 4: There are as many as dozens of buildings in the picture. Among them,two are less than 18 meters in height, while the rest are taller than 54meters.", + "Step 5: The average height of the buildings in the entire map is 32-40meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_380.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0045", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, there is one that is dark red,two that are orange, one that is green, and hundreds that are blue.", + "Step 3: The corresponding heights for deep red are over 58 meters, for orangeit is between 42 and 48 meters, for green it is 30 meters, and for blue it isless than 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 32-40meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_504.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0046", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are 2 in red, 2 in lightyellow, 1 in green, and dozens in blue.", + "Step 3: The height corresponding to red is about 48 to 52 meters, the heightcorresponding to light yellow is about 36 to 40 meters, the heightcorresponding to green is about 24 meters or more, the height corresponding tolight blue is above 24 meters, and the height corresponding to blue is below18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_570.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0047", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue.", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, all of which have a height of no more than 12 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_601.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0048", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Of the buildings in the picture, there are 4 light blue, 15 red, anddozens more blue.", + "Step 3: Red corresponds to heights over 60 meters, light blue corresponds toheights of 18 to 24 meters, and blue corresponds to heights below 18 meters.", + "Step 4: There are dozens of buildings in the picture, of which 15 are morethan 54 meters high, 4 are about 18 meters high, and others are less than 18meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_220.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0049", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Of the buildings in the picture, 1 is green, 28 are yellow, and 20are blue.", + "Step 3: Green corresponds to a height of 30 to 36 meters, yellow and yellowcorrespond to a height of 36 to 42 meters, and blue corresponds to a height ofless than 18 meters.", + "Step 4: There are dozens of buildings in the picture, of which 28 are 36 to42 meters, another is about 30 to 36 meters high, and others are less than 18meters high.", + "Step 5: The average height of the buildings in the entire map is 30-36meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2103.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0050", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue.", + "Step 3：blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, all of which are below12 meters in height.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_604.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0051", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are over 50 buildings in the picture.", + "Step 2: Among the buildings in the picture, one is red, six are light blueand the rest are dark blue.", + "Step 3: Red corresponds to a height between 48 meters and 60 meters, lightblue to a height between 12 meters and 24 meters, and dark blue to a heightbelow 12 meters.", + "Step 4: There are over 50 buildings in the picture. One is about 48 to 60meters high, six are about 12 to 24 meters high, and the rest are less than 12meters high.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_531.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0052", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is green, 20 are light blue,and the remaining dozens are blue.", + "Step 3: Green corresponds to a height of 24-36meters, light blue correspondsto a height of 12-24 meters, and blue corresponds to a height below 12meters.", + "Step 4: There are dozens of buildings in the picture, one with a height ofabout 24 to 36 meters, 20 with a height of about 12-24 meters, and some with a height below 12 meters.", + "Step 5: The average height of the buildings in the entire map is 12-24meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-24", + "(C) 24-30", + "(D) over 30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_550.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0053", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is brown, the other is lightblue, and dozens of others are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, light bluecorresponds to a height of 12-24 meters, and blue corresponds to a heightbelow 12 meters.", + "Step 4: There are dozens of buildings in the picture, one with a height ofover 60 meters, three with a height of about 12 to 24 meters, and otherbuildings with a height of less than 12 meters", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_528.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0054", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, six are red, two are yellow andone is green. Dozens are light blue and dozens are blue.", + "Step 3: There are hundreds of buildings in the picture. Among them, three areover 60 meters high, another five are about 36 to 54 meters high, 20 are about24 meters high, and the rest are less than 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 18-24 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_219.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0055", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in this picture, five are light blue, six areblue, and the rest are dark blue.", + "Step 3: Dark blue indicates a height of less than 6 meters, blue indicates a height between 6 and 12 meters, and light blue indicates a height between 12and 18 meters.", + "Step 4: There are dozens of buildings in the picture. Among them, five areover 12 meters high, another six are about 6 to 12 meters high, and the heightof the remaining buildings is all less than 6 meters.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2294.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0056", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in this picture, six are green, one is yellow andlight green, three are orange, and dozens are blue.", + "Step 3: Green indicates a height over 30 meters, yellow and orange indicate a height between 36 and 40 meters, light green indicates a height of 24 meters,and blue indicates a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture. Among them, three areover 42 meters high, another one is about 36 to 42 meters high, ten are about30 meters high, and the rest are between 6 and 24 meters high.", + "Step 5: The average height of the buildings in the entire map is 24-30meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2594.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0057", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, hundreds are blue.", + "Step 3: Blue indicates a height of less than 18 meters.", + "Step 4: There are hundreds of buildings in the picture, all of which are lessthan 12 meters in height.", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_779.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0058", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, five are red, three are yellow,two are green, ten are light blue and hundreds are dark blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture. Among them, five areover 60 meters high, another three are about 36 to 42 meters high, two areabout 26 meters high, and the rest are less than 24 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_817.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0059", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in this picture, three are red, dozens are lightblue and ten are dark blue.", + "Step 3: Red indicates a height of over 54 meters, light blue indicates a height of 24 meters, and dark blue indicates a height of less than 18meters.", + "Step 4: There are hundreds of buildings in the picture. Among them, three areover 54 meters tall and the rest are less than 24 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_264.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0060", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1214.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0061", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are three buildings thatare red and orange and dark yellow, sixteen are green, twenty-six are lightblue, one is yellow, and the others are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 24-30meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2088.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0062", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are 21 buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is orange,three are yellow, two are green, and 15 are blue..", + "Step 3: Brown corresponds to a height of more than 42 meters, yellow andgreen correspond to a height of 36 to 30 meters, blue corresponds to a heightof 12 meters, and dark blue corresponds to a height of less than 6 meters.", + "Step 4: There are 21 buildings in the picture, one of which is more than 42meters high, three are about 36 to 42 meters high, two are about 24 to 36meters high, and the rest are less than 18 meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2196.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0063", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, six are light blue, and dozensmore are blue.", + "Step 3:The light blue one is more than 18 meters, while the blue onecorresponds to a height of less than 18 meters..", + "Step 4: There are dozens of buildings in the picture, six of which are morethan 18 meters high, and the rest are less than 18 meters high..", + "Step 5: The average height of the buildings in the entire map is 6-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_104.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0064", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, there are two that are yellow, onethat is light blue, and several dozen that are blue.", + "Step 3: Yellow corresponds to heights above 36 meters, light blue correspondsto heights below 24 meters, and blue corresponds to heights below 18 meters.", + "Step 4: There are dozens of buildings in the picture, two of which are over36 meters high, one is about 24 meters high, and the others are less than 18meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1950.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0065", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are five that are orange,three that are light red, one that is deep red, dozens that are light blue,and hundreds that are blue.", + "Step 3: Orange corresponds to heights above 42 meters, light red correspondsto heights of 48 to 54 meters, deep red corresponds to heights of 60 meters,light blue corresponds to heights of 24 meters, and blue corresponds toheights below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, five of which areover 42 meters high, three are about 48 to 54 meters high, one is about 60meters high, dozens are about 24 meters high, and the rest are less than 18meters high.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_218.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0066", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2286.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0067", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is red, fourthat are light blue, and several dozen that are blue.", + "Step 3: Red corresponds to heights above 48 meters, light blue corresponds toheights between 18-24 meters, and blue corresponds to heights below 18meters.", + "Step 4: There are hundreds of buildings in the picture, one with a heightexceeding 48 meters, four with a height of 18-24 meters, and other buildingswith a height below 18 meters.", + "Step 5: The average height of the buildings in the entire map is 6-18meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-18", + "(B) 18-30", + "(C) 30-42", + "(D) 42-54", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2365.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0068", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2612.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0069", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_717.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0070", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are approximately 100 buildings in the picture.", + "Step 2: Among the buildings in the picture, there are six that are red, onethat is yellow, about a dozen that are blue, and dozens that are light blue.", + "Step 3: Red corresponds to heights above 48 meters, yellow corresponds toheights between 36 and 40 meters, blue corresponds to heights below 18 meters,and light blue corresponds to heights between 18 and 24 meters.", + "Step 4: There are approximately 100 buildings in the picture, with 6buildings exceeding 48 meters in height, 1 building ranging from 36 to 42 meters in height, about a dozen buildings below 18 meters in height, anddozens of buildings remaining below 18 to 24 meters in height.", + "Step 5: The average height of the buildings in the entire map is 18-24 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_819.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0071", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are 16 buildings in the picture.", + "Step 2: Among the buildings in the picture, there are 6 in deep red and 10 inblue.", + "Step 3: Deep red corresponds to heights above 54 meters, and blue correspondsto heights below 18 meters.", + "Step 4: There are 16 buildings in the picture, with 6 buildings exceeding 54meters in height and 10 buildings ranging from 6 to 18 meters in height.", + "Step 5: The average height of the buildings in the entire map is 6-18meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-18", + "(B) 18-24", + "(C) 24-30", + "(D) 30-36", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1040.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0072", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_503.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0073", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are 20 that are darkblue,and rest of buildings are sky blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, 20 with a height lessthan 20 meters, another with a height of approximately 20 to 24 meters.", + "Step 5: The average height of the buildings in the entire map is 12-24meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-6", + "(B) 6-12", + "(C) 12-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_104.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0074", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2167.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0075", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2257.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0076", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, all buildings are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture,every of buildings isabout 6 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 0-12", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "C", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2614.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0077", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are seven that are brownand red, six that are yellow and orange, ten that are light blue, and hundredsthat are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, some with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, some with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "D", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_814.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0078", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, one that is yellow and orange, ten that are light blue, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orange correspond to a height of 36 to 40 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_104.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0079", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is light blue, while theother dozens are blue.", + "Step 3: light blue corresponds to a height of 12-24 meters, and bluecorresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, one with a height ofabout 12 to 24 meters, and the rest with a height below 12 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2634.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0080", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, 2 are yellow, 10 are green, 10are light blue, and the remaining dozens are blue.", + "Step 3: Green corresponds to a height of 24-36 meters, yellow corresponds toa height of 36-48 meters, light blue corresponds to a height of 12-24 meters,and blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, with 2 buildingsexceeding 36 meters in height, 10 buildings ranging from 24 to 36 meters inheight, 10 buildings ranging from 12-24 meters in height, and other buildingsbelow 12 meters in height.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_703.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0081", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue.", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are hundreds of buildings in the picture,all buildings shallnot exceed 12 meters in height.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_728.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0082", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is green, fourthat are light green, ten that are light blue, and dozens of others that areblue.", + "Step 3: Green represents a height of 24-36 meters, light green represents a height of 24 meters, light blue represents a height of 12-24 meters, and bluerepresents a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, one with a height ofabout 24 to 36 meters, three with a height of about 12-24 meters, and theothers with a height of less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_740.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0083", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue..", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, all of which have a height of less than 12 meters..", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_777.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0084", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is light blue, while theother dozens are blue.", + "Step 3: light blue corresponds to a height of 12-24 meters, and bluecorresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, one with a height ofabout 12 to 24 meters, and the others with a height of less than 12 meters. ", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2395.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0085", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue.", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, all buildings shallnot exceed 12 meters in height.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2332.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0086", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is light blue, while theother dozens are blue.", + "Step 3: Light blue corresponds to a height of 12-24 meters, while bluecorresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picturers .The height of abuilding is 12-24 meters, while the height of dozens of other buildings doesnot exceed 12 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2251.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0087", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is light blue and dozens areblue..", + "Step 3: Light blue corresponds to a height of 12-24 meters, while bluecorresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, 1 with a height ofapproximately 12-24 meters, and others with a height less than 12 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2210.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0088", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture", + "Step 2: Among the buildings in the picture, 3 are brown, 2 are yellow, 10 arelight blue, and dozens are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, yellow and orangecorrespond to a height of 36 to 48 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are dozens of buildings in the picture, one with a height greater than 60 meters, two with a height of approximately 36 to 42 meters, 10with a height of approximately 24 meters, and others with a height less than12 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2186.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0089", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all buildings are blue .", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, all of which have a height of less than 12 meters.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2162.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0090", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, there are 3 green ones, about 20light blue ones, and dozens of blue ones.", + "Step 3: Green corresponds to a height of 24 to 36 meters, light bluecorresponds to a height of 12-24 meters, and blue corresponds to a heightbelow 12 meters.", + "Step 4: There are hundreds of buildings in the picture, with 3 buildingsmeasuring approximately 24 to 36 meters in height, 20 buildings measuringapproximately 24 meters in height, and other buildings measuring less than 12meters in height..", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2150.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0091", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: In the buildings in the picture, all the buildings are blue.", + "Step 3: blue corresponds to a height below 12 meters.", + "Step 4: There are dozens of buildings in the picture, each of which is nomore than 12 meters long.", + "Step 5: The average height of the buildings in the entire map is 0-12meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 0-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "A", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2096.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0092", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, one is brown, one is yellow,several are green, and the remaining dozens are dark blue and light blue in color.", + "Step 3: Brown corresponds to a height of over 48 meters, yellow and orangecorrespond to a height of 36 to 48 meters, light blue corresponds to a height of 24 meters, and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, one with a height greater than 60 meters, another with a height of approximately 36 to 42 meters, 10 with a height of approximately 24 meters, and others with a height less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2087.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0093", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is brown, onethat is red, 4 that are orange, and hundreds that are blue.", + "Step 3: Brown corresponds to a height of over 60 meters, red correspond to a height of 48 to 54 meters, orange corresponds to a height of 36 to 42 meters,and blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, there is one that isover 60 meters, one that is 48 to 54 meters, 4 that are 36 to 42 meters, andhundreds that are less 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_646.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0094", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are dozens of buildings in the picture.", + "Step 2: Among the buildings in the picture, there is one that is green,5 thatare light blue, and others that are blue.", + "Step 3: Green corresponds to a height of 30 meters, light blue correspond toa height of 18 to 24 meters and blue corresponds to a height below 18meters.", + "Step 4: There are dozens of buildings in the picture, there is one that is 30meters, 5 that is 18 to 24 meters and others that are less 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_648.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0095", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, most buildings are blue in color.", + "Step 3: Blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, most buildings are less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_651.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0096", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, most buildings are blue in color.", + "Step 3: Blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, most buildings are less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_654.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0097", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, most buildings are blue in color.", + "Step 3: Blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, most buildings are less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_671.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0098", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, most buildings are blue in color.", + "Step 3: Blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, most buildings are less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_681.png" + ], + "Question Type": "Single Choice" + }, + { + "Question_id": "Overall building height estimation/0099", + "Question_Type": "Single Choice", + "Text": "Which interval is the main concentration of the actual height of buildings in the entire image?", + "CoT": [ + "Step 1: There are hundreds of buildings in the picture.", + "Step 2: Among the buildings in the picture, most buildings are blue in color.", + "Step 3: Blue corresponds to a height below 18 meters.", + "Step 4: There are hundreds of buildings in the picture, most buildings are less than 18 meters.", + "Step 5: The average height of the buildings in the entire map is 12-18 meters." + ], + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Overall building height estimation", + "Answer Choices": [ + "(A) 6-12", + "(B) 12-18", + "(C) 18-24", + "(D) 24-30", + "(E) Unable to decide" + ], + "Ground Truth": "B", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_685.png" + ], + "Question Type": "Single Choice" + } +] \ No newline at end of file diff --git a/jsons/Pedosphere/Urban_Development/Reasoning/Visual_grounding_under_complex_conditions.json b/jsons/Pedosphere/Urban_Development/Reasoning/Visual_grounding_under_complex_conditions.json new file mode 100644 index 0000000000000000000000000000000000000000..1401504d122d32f5a10eb1ec4b7b18483a0c347f --- /dev/null +++ b/jsons/Pedosphere/Urban_Development/Reasoning/Visual_grounding_under_complex_conditions.json @@ -0,0 +1,4052 @@ +[ + { + "Question_id": "Visual grounding under complex conditions/0000", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><62><256><71>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2100.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0001", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture, witha height of approximately 12 meters It is the smallest rectangular building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<242><247><256><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2168.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0002", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the picture, with aheight of approximately 56 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><136><15><147>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_217.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0003", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the picture, with aheight of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><159><8><169>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2246.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0004", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle-right part of the entire picture, and it isapproximately 36 meters in height.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<137><102><150><147>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_820.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0005", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the picture, with aheight of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<114><233><149><242>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2568.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0006", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture, witha height of approximately 24 meters, and is the smallest rectangle in terms ofarea", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<215><248><230><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_788.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0007", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<209><63><221><77>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2642.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0008", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle right of the entire picture, with aheight of approximately 12 meters, and is the largest rectangle in terms ofarea", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<140><64><227><148>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_973.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0009", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 37 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<222><0><256><7>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_705.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0010", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the bottom right corner of the entire map, with aheight of approximately 30 meters. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<234><239><253><247>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_936.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0011", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<184><54><201><85>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_765.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0012", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle area of the map, with a height ofapproximately 36 meters. It is the largest in area among those of the sameheight.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<132><92><171><101>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_829.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0013", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 46 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<203><122><214><133>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_809.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0014", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper part of the picture and is the largest lightblue rectangle ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<91><44><158><127>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_954.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0015", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<207><107><221><120>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_377.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0016", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:Thebuilding is located towards the top center of the picture and is the tallestbuilding in the image. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<107><17><136><62>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_817.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0017", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the picture, with aheight of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<251><150><256><165>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_446.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0018", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture, witha height of approximately 12 meters, and is the smallest rectangle in theupper left corner of the picture", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><13><85><22>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_11.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0019", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<236><56><254><70>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2151.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0020", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located on the far left of the image, and there are twobuildings above it, with a height of about 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<230><113><238><120>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_84.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0021", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<183><0><197><5>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2071.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0022", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom of the entire picture, with a height ofapproximately 13 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<26><247><34><254>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_92.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0023", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 21 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<230><0><238><3>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2170.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0024", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture and is thetallest building in this picture,with a height of approximately 48 meters. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<9><30><23><38>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_953.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0025", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the center of the entire picture, with a height ofapproximately 35 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<100><110><163><143>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2215.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0026", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the top of the entire picture and is the leftmost amongall buildings, with a height of approximately 12 meters. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<122><0><131><16>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_175.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0027", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<211><78><232><91>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2292.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0028", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is (x_min, y_min) and the bottom right corner is (x_max, y_max).Description: This building is located in the lower right corner of the entirepicture and is the only one in the picture with a height of about 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><223><256><237>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_914.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0029", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 42 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<196><11><256><26>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2323.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0030", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is on the left side of the picture, about 12 meters, and it isthe leftmost one among all the buildings.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><193><91><203>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_193.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0031", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<23><76><41><83>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2611.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0032", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the upper part of the picture, and it isthe building that occupies the largest area in the picture. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<54><8><184><70>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_91.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0033", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><252><88><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_706.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0034", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located directly above the picture on the left, with a height ofapproximately 36 meters. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<60><0><95><19>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_224.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0035", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 45 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<226><217><255><245>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_753.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0036", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture,presenting a rectangular shape with a height of approximately 12 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<70><242><85><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_228.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0037", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<180><209><193><221>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_815.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0038", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture,presenting a rectangle and being the largest in area, with a height ofapproximately 30 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<125><233><181><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_346.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0039", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 45 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<73><7><101><52>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2025.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0040", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: The cylindrical building is located in the lower left part of the picture, with aheight of approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<37><137><71><168>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_199.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0041", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<207><2><253><49>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2198.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0042", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower left corner of the entire picture, with aheight of approximately 12 meters. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<18><232><28><240>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_489.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0043", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle on the right side of the entire pictureand is approximately 38 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<216><70><256><144>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2300.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0044", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the left corner of the entire picture, presentingan X-shape with a height of approximately 60 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<32><14><50><29>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_542.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0045", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower left corner of the entire picture andclose to the center of the picture, with a height of approximately 38meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<97><155><126><186>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2587.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0046", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture,presenting a circular arc shape with a height of approximately 12 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<144><237><169><250>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_270.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0047", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left of the center of the entirepicture, with a height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<110><76><134><123>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_704.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0048", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture, witha height of less than 18 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<179><28><189><41>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_111.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0049", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the upper part of the entirepicture, with a height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<103><17><131><24>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_750.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0050", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the picture, with aheight of approximately 30 meters. Below it is a building with a similar shapeand height.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<193><17><223><25>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_208.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0051", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<197><5><225><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_811.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0052", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, andit is the biggest building in this corner,with a height of approximately 20meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<179><29><242><80>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_218.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0053", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 58 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><29><35><51>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_990.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0054", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the image and has aheight of approximately 24 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<218><224><245><246>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_280.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0055", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<238><54><256><61>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_396.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0056", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture, witha height of approximately 36-48 meters", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<244><40><256><55>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_416.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0057", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<208><53><241><84>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_511.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0058", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<50><70><82><83>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_498.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0059", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom corner of the entire picture, with aheight of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<128><193><208><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2072.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0060", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<57><0><103><9>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changzhou_285.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0061", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 10 meters，It is the largest building with arectangular area in the region.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<203><27><234><71>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2203.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0062", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the top position of the image andhas a height of approximately 60 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<90><2><131><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changsha_571.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0063", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the left corner of the entire picture, with aheight of approximately 22 meters.the building has a trapezoidal shape", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><78><32><123>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_778.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0064", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located at the bottom right of the complex and is about 12 metershigh.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<171><157><192><164>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_976.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0065", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 23 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<13><229><41><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_988.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0066", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 6 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><8><23><30>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_378.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0067", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 7 meters.This building has the largest area in thepicture", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<122><0><209><109>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_507.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0068", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 20 meters.There is a building of the same heightbelow it that is larger in area than it.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<210><7><250><16>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_513.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0069", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lowest part and has a rectangular shape ，with a height of approximately 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<90><210><121><216>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_523.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0070", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the left corner of the entire picture, with aheight of approximately 50meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><192><6><200>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_565.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0071", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom corner of the entire picture, with aheight of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<163><248><178><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_598.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0072", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 48 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<181><0><217><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_996.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0073", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><40><17><62>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_380.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0074", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<15><79><27><85>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_504.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0075", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 52 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<151><77><168><105>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_570.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0076", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture and is thelongest rectangular building, with a height of approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<103><0><185><19>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_601.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0077", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture, with aheight of approximately 12 meters It is the largest L-shaped building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<175><0><256><123>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_604.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0078", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<133><0><184><19>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_531.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0079", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the bottom in right corner of the entire picture,with a height of approximately 24-36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<201><237><241><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_550.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0080", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture, witha height of approximately 60 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<190><246><205><254>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_528.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0081", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<225><0><256><27>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1214.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0082", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 60 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<226><220><240><232>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_218.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0083", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 47 meters and represents the smallest rectangle .", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><0><6><7>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2286.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0084", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 21 meters and presents an E-shape.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<206><13><239><62>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2365.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0085", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the middle of the entire picture, with a height ofapproximately 21 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<132><133><160><152>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2612.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0086", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 37 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<199><50><213><69>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_819.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0087", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 6 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<51><251><64><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_1040.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0088", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<30><250><37><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_503.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0089", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 24 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<223><10><235><22>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2101.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0090", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<203><231><220><251>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2167.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0091", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 6 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<246><6><256><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2257.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0092", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the left side of the entire picture, with a heightof approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><58><11><111>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2614.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0093", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<234><195><256><206>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_814.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0094", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<90><164><116><186>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_789.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0095", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<143><109><185><150>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2113.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0096", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture, witha height of approximately 12-24 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<46><193><89><209>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2634.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0097", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture, witha height of approximately 36 meters It is the smallest square building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<246><0><256><17>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_703.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0098", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture, with aheight of approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<108><0><126><6>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_728.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0099", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<195><96><220><103>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_740.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0100", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is L-shaped and located in the upper right corner of the entirepicture, with a height of approximately 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<201><12><236><34>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_777.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0101", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture, witha height of approximately 20-24 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<20><0><84><56>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2395.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0102", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture, witha height of approximately 12 meters and an inverted F-shape.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<21><180><57><222>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2332.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0103", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture, witha height of approximately 12 meters It is the smallest triangular building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><189><8><215>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2251.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0104", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower right corner of the entire picture, witha height of approximately 12 meters It is the smallest building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<210><249><224><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2210.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0105", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture, witha height of approximately 12 meters It's a cone-shaped building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<10><57><69><103>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2186.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0106", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the top left corner of the entire picture, with aheight of no more than 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<28><0><70><8>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2162.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0107", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture, with aheight of approximately 30 meters, and is the smallest square building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<251><61><256><73>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2150.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0108", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture, witha height of approximately 12 meters, and is the smallest circular building.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<8><223><21><246>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2096.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0109", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture, with aheight of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><165><19><178>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2087.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0110", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<199><146><225><162>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_121.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0111", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<40><247><61><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_125.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0112", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<166><17><200><28>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_134.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0113", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<121><17><141><30>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_156.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0114", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<236><166><256><184>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_174.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0115", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 40 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<94><62><127><78>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_178.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0116", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<140><252><171><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_196.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0117", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<129><2><146><9>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_210.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0118", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<165><158><190><166>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_26.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0119", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 22 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<248><64><256><68>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_107.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0120", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 54 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<65><218><79><225>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_136.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0121", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 45 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<238><3><256><12>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_193.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0122", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the center of the entire picture, with a height ofapproximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<111><110><136><117>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_37.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0123", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 39 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<154><94><173><99>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1075.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0124", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 21 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<216><6><244><17>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1202.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0125", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 45 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<12><209><36><219>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1296.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0126", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper side of the entire picture, with aheight of approximately 54 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<118><37><135><53>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1328.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0127", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<185><246><197><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1439.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0128", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><251><14><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_122.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0129", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><217><14><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_126.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0130", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<187><240><211><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_128.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0131", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 12 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<191><0><256><10>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1152.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0132", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<138><237><150><243>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1305.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0133", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<4><250><19><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1316.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0134", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<14><156><49><204>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1321.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0135", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<52><239><67><251>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1325.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0136", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><234><19><246>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1341.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0137", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image,identify the bounding box of the object in the format (xmin,ymin,xmax,ymax),where the top-left corner is (x_min,y_min) and the bottom right corner is (x_max,y_max). Description:This building is located in the upper left corner of the entire picture and is approximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><26><15><37>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_106.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0138", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower right corner of the entire picture,close to the center of the picture, and its height is approximately 30meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<141><168><167><182>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_181.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0139", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture, closeto the center of the picture, and its height is approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<87><108><100><126>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_20.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0140", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the left side of the entire pictureand is approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><153><4><162>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_39.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0141", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the left side of the entire picture,with a height of approximately 42 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><108><6><116>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_42.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0142", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<246><70><256><88>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1006.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0143", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<231><62><256><72>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1133.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0144", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><0><11><26>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1163.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0145", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the right side of the entire pictureand is approximately 60 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<231><100><256><133>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1187.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0146", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 30 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<76><0><85><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1203.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0147", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<9><0><30><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1235.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0148", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 48 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<11><0><36><2>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1297.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0149", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the picture, with aheight of approximately 56 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<250><172><256><180>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_41.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0150", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<201><220><229><228>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_211.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0151", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<79><51><90><64>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_96.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0152", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the picture, with aheight of approximately 37 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<29><15><93><32>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1050.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0153", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the picture, with aheight of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><223><253><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1063.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0154", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the picture, with aheight of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<6><244><30><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1095.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0155", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the picture, with aheight of approximately 32 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<31><24><64><32>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1121.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0156", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building, located in the upper right corner of the picture, stands at a heightof less than 18 meters and is the largest structure in the entire image. ", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<151><15><196><71>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_646.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0157", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<5><253><20><255>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1151.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0158", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the picture and has arectangular shape.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<99><4><121><24>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_648.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0159", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is the largest in area, located in the center of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<124><109><145><127>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_651.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0160", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 32 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><37><16><63>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1160.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0161", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<177><0><223><26>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_654.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0162", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture andhas a minimum area of approximately 40 meters in height.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<28><211><34><215>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_36.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0163", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<158><23><173><59>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_671.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0164", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<126><115><155><128>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_40.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0165", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<19><54><64><80>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_681.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0166", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<89><182><107><191>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_79.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0167", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the right side of the picture, with a heightof less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<228><112><242><138>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_682.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0168", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<138><189><173><202>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/baoding_95.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0169", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<179><47><216><78>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_683.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0170", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 54 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><0><87><11>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1117.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0171", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the bottom left corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<44><132><87><154>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_685.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0172", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<31><178><45><192>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1201.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0173", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the bottom left corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<32><214><77><232>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_686.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0174", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<113><243><163><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1294.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0175", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the bottom left corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<7><214><40><238>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_687.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0176", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<169><6><208><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1310.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0177", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<226><96><256><123>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_690.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0178", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<219><254><243><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1326.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0179", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper side of the picture, with a heightof less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<100><39><125><54>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_704.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0180", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<8><26><32><35>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1389.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0181", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper side of the picture, with a heightof less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<129><3><148><23>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_706.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0182", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle left of the entire picture, with aheight of about 33 meters and the smallest area.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<79><94><92><101>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1493.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0183", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<46><55><86><68>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_708.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0184", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><36><81><43>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2046.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0185", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of less than 18 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<221><9><245><21>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_710.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0186", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottomcorner of the entire picture, with aheight of approximately 23 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<88><248><105><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2051.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0187", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<31><30><64><52>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_712.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0188", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper corner of the entire picture, with aheight of approximately 22 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<78><0><105><11>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2052.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0189", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<34><22><54><35>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_717.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0190", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<211><239><227><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2068.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0191", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of 20 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<90><8><128><51>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_721.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0192", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<128><0><150><32>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2070.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0193", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper left corner of the picture, with aheight of 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<2><27><32><52>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_723.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0194", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the central of the entire picture, with a heightof approximately 45 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<130><66><164><100>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1336.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0195", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:ThisL-shaped building is located in the upper right corner of the picture, with aheight of 12 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<208><39><231><68>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_742.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0196", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><246><10><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1537.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0197", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<1><246><17><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1603.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0198", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><247><6><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1633.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0199", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<252><250><256><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1634.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0200", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<242><241><255><255>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1635.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0201", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower right corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<242><249><256><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1636.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0202", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><245><10><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1638.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0203", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description: Thebuilding is located in the lower left corner of the entire picture and isabout 6 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<16><229><38><249>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1645.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0204", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<59><0><94><27>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1569.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0205", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<171><181><186><196>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1618.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0206", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 30 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<11><169><52><183>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1639.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0207", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<248><124><255><136>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1971.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0208", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<117><60><151><105>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2020.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0209", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<234><4><256><23>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2023.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0210", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle left of the entire picture, with aheight of approximately 42 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><118><40><134>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2037.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0211", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<169><41><187><56>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1977.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0212", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located slightly lower in the middle of the entire pictureand is approximately 28 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<114><153><147><174>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_2022.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0213", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<186><49><216><71>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1697.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0214", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 39 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<3><225><24><233>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1823.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0215", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 23 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<163><194><176><208>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1870.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0216", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the entire picture, witha height of approximately 58 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<8><40><22><54>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1941.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0217", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom left corner of the entire picture, witha height of approximately 6 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><222><26><230>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1952.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0218", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 33 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<238><38><256><67>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1978.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0219", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><12><14><20>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1708.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0220", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the bottom right corner of the entire picture,with a height of approximately 33 meters and it has the smallest area.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<253><197><256><206>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1660.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0221", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 45 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<47><0><107><35>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1298.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0222", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower right corner of the entire picture andis approximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<200><238><211><251>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1304.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0223", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower left corner of the entire picture andclose to the center of the picture, with a height of approximately 40meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<43><161><139><195>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1320.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0224", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture and isapproximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<46><246><60><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1324.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0225", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the middle of the left side of the entire picture,with a height of approximately 38 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<12><93><25><103>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1343.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0226", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 54 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<176><27><197><61>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1528.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0227", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<223><0><234><8>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1545.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0228", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 30 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<43><31><68><62>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1552.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0229", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 30 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<218><88><243><95>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1562.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0230", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 45 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<233><0><238><3>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1586.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0231", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 40 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<64><0><77><4>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1631.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0232", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower right corner of the entire picture andis approximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<223><198><256><220>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1637.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0233", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 38 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<193><0><209><16>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1643.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0234", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the lower right corner of the entire picture andis approximately 38 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<242><254><250><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1672.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0235", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the lower left corner of the entire picture and isapproximately 38 meters high.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<30><254><33><255>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1721.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0236", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper left corner of the entire picture and isapproximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<78><6><123><16>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1798.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0237", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located in the upper right corner of the entire picture andis approximately 60 meters tall.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<181><1><192><10>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1848.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0238", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<94><0><115><8>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1653.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0239", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 50 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><203><256><219>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1667.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0240", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper bottom right corner of the picture, witha height of approximately 40 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<193><239><225><249>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1669.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0241", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<221><0><250><6>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1670.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0242", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<159><225><174><233>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1684.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0243", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<169><45><208><59>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1685.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0244", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 52 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<247><203><256><218>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1716.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0245", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<150><59><205><87>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1788.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0246", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><219><16><232>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1802.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0247", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<209><145><243><163>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1803.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0248", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<40><105><77><113>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1847.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0249", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<217><65><235><75>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1855.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0250", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<244><251><256><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1901.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0251", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<136><0><158><7>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1601.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0252", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<56><187><69><196>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1593.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0253", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<125><132><146><155>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1592.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0254", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<233><234><239><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1585.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0255", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<46><67><78><78>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1560.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0256", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<239><219><256><226>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1557.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0257", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<3><30><18><39>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1546.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0258", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the middle position of the picture, with a heightof approximately 32 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<108><210><194><256>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1542.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0259", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><19><256><27>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1539.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0260", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<130><138><168><161>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1536.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0261", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<0><0><5><5>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1506.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0262", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<224><27><228><41>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1486.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0263", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper bottom right corner of the picture, witha height of approximately 40 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<239><247><253><255>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1447.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0264", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<34><244><47><255>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1437.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0265", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the picture, with aheight of approximately 37 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<80><230><91><236>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1400.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0266", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<241><120><255><127>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1342.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0267", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper left corner of the picture, with aheight of approximately 46 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<4><4><18><14>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1339.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0268", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper right corner of the entire picture, witha height of approximately 36 meters.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<74><0><93><32>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/beijing_1334.png" + ], + "Question Type": "Visual Grounding" + }, + { + "Question_id": "Visual grounding under complex conditions/0269", + "Question_Type": "Grounding", + "Text": "Given a 600x600 pixel satellite image, identify the bounding box ofthe object in theformat (xmin, ymin, xmax, ymax), where the top-left corner is(x_min, y_min) and the bottom right corner is (x_max, y_max). Description:This building is located at the upper central of the entire picture, with aheight of approximately 10 meters.This building has the largest area in thepicture.", + "Dataset": "BHbuilding", + "L1-task": "Pedosphere", + "L2-task": "Urban Development", + "L3-task": "Reasoning", + "L4-task": "Visual grounding under complex conditions", + "Ground Truth": "{<83><0><163><60>}", + "Images": [ + "raw/Pedosphere/BHbuilding/images/changchun_605.png" + ], + "Question Type": "Visual Grounding" + } +] \ No newline at end of file diff --git a/raw.tar b/raw.tar new file mode 100644 index 0000000000000000000000000000000000000000..c457eb1387b02e9c757f7610defa3008bda29c02 --- /dev/null +++ b/raw.tar @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4086edd2dd4e34428de967e98a8b1ffc8114c229a42e54bcccce079f51c5c1b +size 19805952000